WorldWideScience

Sample records for multi-spectral image analysis

  1. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  2. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

    2004-01-01

    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral dermatological images is proposed. The system is made up of an integrating sphere, light emitting diodes and a generic monochromatic camera. The system can collect up to 10 different spectral bands....... These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

  3. Semiconductor Laser Multi-Spectral Sensing and Imaging

    Directory of Open Access Journals (Sweden)

    Han Q. Le

    2010-01-01

    Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  4. Semiconductor laser multi-spectral sensing and imaging.

    Science.gov (United States)

    Le, Han Q; Wang, Yang

    2010-01-01

    Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  5. Cloud-based processing of multi-spectral imaging data

    Science.gov (United States)

    Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

    2017-03-01

    Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

  6. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  7. Multi-spectral endogenous fluorescence imaging for bacterial differentiation

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

    2017-07-01

    In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

  8. Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

    2016-09-01

    In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

  9. Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

    Science.gov (United States)

    Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

    2018-06-01

    Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

  10. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

    Science.gov (United States)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark

    2016-10-01

    Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

  11. A multi-object spectral imaging instrument

    OpenAIRE

    Gibson, G.M.; Dienerowitz, M.; Kelleher, P.A.; Harvey, A.R.; Padgett, M.J.

    2013-01-01

    We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the ...

  12. Quantitative functional optical imaging of the human skin using multi-spectral imaging

    International Nuclear Information System (INIS)

    Kainerstorfer, J. M.

    2010-01-01

    Light tissue interactions can be described by the physical principles of absorption and scattering. Based on those parameters, different tissue types and analytes can be distinguished. Extracting blood volume and oxygenation is of particular interest in clinical routines for tumor diagnostics and treatment follow up, since they are parameters of angiogenic processes. The quantification of those analytes in tissue can be done by physical modeling of light tissue interaction. The physical model used here is the random walk theory. However, for quantification and clinical usefulness, one has to account for multiple challenges. First, one must consider the effect of topology of the sample on measured physical parameters. Second, diffusion of light inside the tissue is dependent on the structure of the sample imaged. Thus, the structural conformation has to be taken into account. Third, clinical translation of imaging modalities is often hindered due to the complicated post-processing of data, not providing results in real-time. In this thesis, two imaging modalities are being utilized, where the first one, diffuse multi-spectral imaging, is based on absorption contrast and spectral characteristics and the second one, Optical Coherence Tomography (OCT), is based on scattering changes within the tissue. Multi-spectral imaging can provide spatial distributions of blood volume and blood oxygenation and OCT yields 3D structural images with micrometer resolution. In order to address the challenges mentioned above, a curvature correction algorithm for taking the topology into account was developed. Without taking curvature of the object into account, reconstruction of optical properties is not accurate. The method developed removes this artifact and recovers the underlying data, without the necessity of measuring the object's shape. The next step was to recover blood volume and oxygenation values in real time. Principal Component Analysis (PCA) on multi spectral images is

  13. Scattering and absorption measurements of cervical tissues measures using low cost multi-spectral imaging

    Science.gov (United States)

    Bernat, Amir S.; Bar-Am, Kfir; Cataldo, Leigh; Bolton, Frank J.; Kahn, Bruce S.; Levitz, David

    2018-02-01

    Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging ( 30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

  14. Multi-layer imager design for mega-voltage spectral imaging

    Science.gov (United States)

    Myronakis, Marios; Hu, Yue-Houng; Fueglistaller, Rony; Wang, Adam; Baturin, Paul; Huber, Pascal; Morf, Daniel; Star-Lack, Josh; Berbeco, Ross

    2018-05-01

    The architecture of multi-layer imagers (MLIs) can be exploited to provide megavoltage spectral imaging (MVSPI) for specific imaging tasks. In the current work, we investigated bone suppression and gold fiducial contrast enhancement as two clinical tasks which could be improved with spectral imaging. A method based on analytical calculations that enables rapid investigation of MLI component materials and thicknesses was developed and validated against Monte Carlo computations. The figure of merit for task-specific imaging performance was the contrast-to-noise ratio (CNR) of the gold fiducial when the CNR of bone was equal to zero after a weighted subtraction of the signals obtained from each MLI layer. Results demonstrated a sharp increase in the CNR of gold when the build-up component or scintillation materials and thicknesses were modified. The potential for low-cost, prompt implementation of specific modifications (e.g. composition of the build-up component) could accelerate clinical translation of MVSPI.

  15. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  16. Multi scales based sparse matrix spectral clustering image segmentation

    Science.gov (United States)

    Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

    2018-04-01

    In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

  17. High performance multi-spectral interrogation for surface plasmon resonance imaging sensors.

    Science.gov (United States)

    Sereda, A; Moreau, J; Canva, M; Maillart, E

    2014-04-15

    Surface plasmon resonance (SPR) sensing has proven to be a valuable tool in the field of surface interactions characterization, especially for biomedical applications where label-free techniques are of particular interest. In order to approach the theoretical resolution limit, most SPR-based systems have turned to either angular or spectral interrogation modes, which both offer very accurate real-time measurements, but at the expense of the 2-dimensional imaging capability, therefore decreasing the data throughput. In this article, we show numerically and experimentally how to combine the multi-spectral interrogation technique with 2D-imaging, while finding an optimum in terms of resolution, accuracy, acquisition speed and reduction in data dispersion with respect to the classical reflectivity interrogation mode. This multi-spectral interrogation methodology is based on a robust five parameter fitting of the spectral reflectivity curve which enables monitoring of the reflectivity spectral shift with a resolution of the order of ten picometers, and using only five wavelength measurements per point. In fine, such multi-spectral based plasmonic imaging system allows biomolecular interaction monitoring in a linear regime independently of variations of buffer optical index, which is illustrated on a DNA-DNA model case. © 2013 Elsevier B.V. All rights reserved.

  18. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Science.gov (United States)

    Yang, Jianping; Li, Jun

    2018-02-01

    Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

  19. Optical perception for detection of cutaneous T-cell lymphoma by multi-spectral imaging

    International Nuclear Information System (INIS)

    Hsiao, Yu-Ping; Wang, Hsiang-Chen; Chen, Shih-Hua; Tsai, Chung-Hung; Yang, Jen-Hung

    2014-01-01

    In this study, the spectrum of each picture element of the patient’s skin image was obtained by multi-spectral imaging technology. Spectra of normal or pathological skin were collected from 15 patients. Principal component analysis and principal component scores of skin spectra were employed to distinguish the spectral characteristics with different diseases. Finally, skin regions with suspected cutaneous T-cell lymphoma (CTCL) lesions were successfully predicted by evaluation and classification of the spectra of pathological skin. The sensitivity and specificity of this technique were 89.65% and 95.18% after the analysis of about 109 patients. The probability of atopic dermatitis and psoriasis patients misinterpreted as CTCL were 5.56% and 4.54%, respectively. (paper)

  20. The MIND PALACE: A Multi-Spectral Imaging and Spectroscopy Database for Planetary Science

    Science.gov (United States)

    Eshelman, E.; Doloboff, I.; Hara, E. K.; Uckert, K.; Sapers, H. M.; Abbey, W.; Beegle, L. W.; Bhartia, R.

    2017-12-01

    The Multi-Instrument Database (MIND) is the web-based home to a well-characterized set of analytical data collected by a suite of deep-UV fluorescence/Raman instruments built at the Jet Propulsion Laboratory (JPL). Samples derive from a growing body of planetary surface analogs, mineral and microbial standards, meteorites, spacecraft materials, and other astrobiologically relevant materials. In addition to deep-UV spectroscopy, datasets stored in MIND are obtained from a variety of analytical techniques obtained over multiple spatial and spectral scales including electron microscopy, optical microscopy, infrared spectroscopy, X-ray fluorescence, and direct fluorescence imaging. Multivariate statistical analysis techniques, primarily Principal Component Analysis (PCA), are used to guide interpretation of these large multi-analytical spectral datasets. Spatial co-referencing of integrated spectral/visual maps is performed using QGIS (geographic information system software). Georeferencing techniques transform individual instrument data maps into a layered co-registered data cube for analysis across spectral and spatial scales. The body of data in MIND is intended to serve as a permanent, reliable, and expanding database of deep-UV spectroscopy datasets generated by this unique suite of JPL-based instruments on samples of broad planetary science interest.

  1. Multi-Temporal vs. Hyper-Spectral Imaging for Future Land Imaging at 30 m

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to determine the information content of multi-temporal land imaging in discrete Landsat-like spectral bands at 30 m with a 360 km swath width and compare...

  2. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  3. A multi-object spectral imaging instrument

    International Nuclear Information System (INIS)

    Gibson, G M; Dienerowitz, M; Kelleher, P A; Harvey, A R; Padgett, M J

    2013-01-01

    We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the CCD for wavelength. A CMOS camera on the front port of the microscope allows the full image of the sample to be displayed and can also be used for particle tracking, providing spectra of multiple particles moving in the sample. We demonstrate the system by recording the spectra of multiple fluorescent beads in aqueous solution and from multiple points along a microscope sample channel containing a mixture of red and blue dye. (paper)

  4. Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis

    Science.gov (United States)

    Somers, B.; Asner, G. P.

    2014-09-01

    The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.

  5. A Lightweight Compact Multi-Spectral Imager Using Novel Computer-Generated Micro-Optics and Spectral-Extraction Algorithms

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this NASA Early-stage research proposal is to demonstrate an ultra-compact, lightweight broadband hyper- and multi-spectral imaging system that is...

  6. Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

  7. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  8. Using Non-Invasive Multi-Spectral Imaging to Quantitatively Assess Tissue Vasculature

    Energy Technology Data Exchange (ETDEWEB)

    Vogel, A; Chernomordik, V; Riley, J; Hassan, M; Amyot, F; Dasgeb, B; Demos, S G; Pursley, R; Little, R; Yarchoan, R; Tao, Y; Gandjbakhche, A H

    2007-10-04

    This research describes a non-invasive, non-contact method used to quantitatively analyze the functional characteristics of tissue. Multi-spectral images collected at several near-infrared wavelengths are input into a mathematical optical skin model that considers the contributions from different analytes in the epidermis and dermis skin layers. Through a reconstruction algorithm, we can quantify the percent of blood in a given area of tissue and the fraction of that blood that is oxygenated. Imaging normal tissue confirms previously reported values for the percent of blood in tissue and the percent of blood that is oxygenated in tissue and surrounding vasculature, for the normal state and when ischemia is induced. This methodology has been applied to assess vascular Kaposi's sarcoma lesions and the surrounding tissue before and during experimental therapies. The multi-spectral imaging technique has been combined with laser Doppler imaging to gain additional information. Results indicate that these techniques are able to provide quantitative and functional information about tissue changes during experimental drug therapy and investigate progression of disease before changes are visibly apparent, suggesting a potential for them to be used as complementary imaging techniques to clinical assessment.

  9. Online Multi-Spectral Meat Inspection

    DEFF Research Database (Denmark)

    Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo

    2013-01-01

    We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...

  10. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    International Nuclear Information System (INIS)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-01-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment. (paper)

  11. Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging

    Science.gov (United States)

    Wang, Hsiang-Chen; Tsai, Meng-Tsan; Chiang, Chun-Ping

    2013-05-01

    Color reproduction systems based on the multi-spectral imaging technique (MSI) for both directly estimating reflection spectra and direct visualization of oral tissues using various light sources are proposed. Images from three oral cancer patients were taken as the experimental samples, and spectral differences between pre-cancerous and normal oral mucosal tissues were calculated at three time points during 5-aminolevulinic acid photodynamic therapy (ALA-PDT) to analyze whether they were consistent with disease processes. To check the successful treatment of oral cancer with ALA-PDT, oral cavity images by swept source optical coherence tomography (SS-OCT) are demonstrated. This system can also reproduce images under different light sources. For pre-cancerous detection, the oral images after the second ALA-PDT are assigned as the target samples. By using RGB LEDs with various correlated color temperatures (CCTs) for color difference comparison, the light source with a CCT of about 4500 K was found to have the best ability to enhance the color difference between pre-cancerous and normal oral mucosal tissues in the oral cavity. Compared with the fluorescent lighting commonly used today, the color difference can be improved by 39.2% from 16.5270 to 23.0023. Hence, this light source and spectral analysis increase the efficiency of the medical diagnosis of oral cancer and aid patients in receiving early treatment.

  12. Distant Determination of Bilirubin Distribution in Skin by Multi-Spectral Imaging

    Science.gov (United States)

    Saknite, I.; Jakovels, D.; Spigulis, J.

    2011-01-01

    For mapping the bilirubin distribution in bruised skin the multi-spectral imaging technique was employed, which made it possible to observe temporal changes of the bilirubin content in skin photo-types II and III. The obtained results confirm the clinical potential of this technique for skin bilirubin diagnostics.

  13. Rayleigh imaging in spectral mammography

    Science.gov (United States)

    Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

    2016-03-01

    Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

  14. Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

    Science.gov (United States)

    Collewet, Guylaine; Moussaoui, Saïd; Deligny, Cécile; Lucas, Tiphaine; Idier, Jérôme

    2018-06-01

    Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Radical advancement in multi-spectral imaging for autonomous vehicles (UAVs, UGVs, and UUVs) using active compensation.

    Energy Technology Data Exchange (ETDEWEB)

    Clark, Brian F.; Bagwell, Brett E.; Wick, David Victor

    2007-01-01

    The purpose of this LDRD was to demonstrate a compact, multi-spectral, refractive imaging systems using active optical compensation. Compared to a comparable, conventional lens system, our system has an increased operational bandwidth, provides for spectral selectivity and, non-mechanically corrects aberrations induced by the wavelength dependent properties of a passive refractive optical element (i.e. lens). The compact nature and low power requirements of the system lends itself to small platforms such as autonomous vehicles. In addition, the broad spectral bandwidth of our system would allow optimized performance for both day/night use, and the multi-spectral capability allows for spectral discrimination and signature identification.

  16. Multi-band morpho-Spectral Component Analysis Deblending Tool (MuSCADeT): Deblending colourful objects

    Science.gov (United States)

    Joseph, R.; Courbin, F.; Starck, J.-L.

    2016-05-01

    We introduce a new algorithm for colour separation and deblending of multi-band astronomical images called MuSCADeT which is based on Morpho-spectral Component Analysis of multi-band images. The MuSCADeT algorithm takes advantage of the sparsity of astronomical objects in morphological dictionaries such as wavelets and their differences in spectral energy distribution (SED) across multi-band observations. This allows us to devise a model independent and automated approach to separate objects with different colours. We show with simulations that we are able to separate highly blended objects and that our algorithm is robust against SED variations of objects across the field of view. To confront our algorithm with real data, we use HST images of the strong lensing galaxy cluster MACS J1149+2223 and we show that MuSCADeT performs better than traditional profile-fitting techniques in deblending the foreground lensing galaxies from background lensed galaxies. Although the main driver for our work is the deblending of strong gravitational lenses, our method is fit to be used for any purpose related to deblending of objects in astronomical images. An example of such an application is the separation of the red and blue stellar populations of a spiral galaxy in the galaxy cluster Abell 2744. We provide a python package along with all simulations and routines used in this paper to contribute to reproducible research efforts. Codes can be found at http://lastro.epfl.ch/page-126973.html

  17. Exploiting physical constraints for multi-spectral exo-planet detection

    Science.gov (United States)

    Thiébaut, Éric; Devaney, Nicholas; Langlois, Maud; Hanley, Kenneth

    2016-07-01

    We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters. The residual speckles1, 2 set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE3 at the VLT, GPI4, 5 at Gemini, or SCExAO6 at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI7 are based on angular differential imaging8 (ADI), spectral differential imaging9, 10 (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation

  18. Terahertz detectors for long wavelength multi-spectral imaging.

    Energy Technology Data Exchange (ETDEWEB)

    Lyo, Sungkwun Kenneth; Wanke, Michael Clement; Reno, John Louis; Shaner, Eric Arthur; Grine, Albert D.

    2007-10-01

    The purpose of this work was to develop a wavelength tunable detector for Terahertz spectroscopy and imaging. Our approach was to utilize plasmons in the channel of a specially designed field-effect transistor called the grating-gate detector. Grating-gate detectors exhibit narrow-linewidth, broad spectral tunability through application of a gate bias, and no angular dependence in their photoresponse. As such, if suitable sensitivity can be attained, they are viable candidates for Terahertz multi-spectral focal plane arrays. When this work began, grating-gate gate detectors, while having many promising characteristics, had a noise-equivalent power (NEP) of only 10{sup -5} W/{radical}Hz. Over the duration of this project, we have obtained a true NEP of 10{sup -8} W/{radical}Hz and a scaled NEP of 10{sup -9}W/{radical}Hz. The ultimate goal for these detectors is to reach a NEP in the 10{sup -9{yields}-10}W/{radical}Hz range; we have not yet seen a roadblock to continued improvement.

  19. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available channel are boresighted with two beamsplitter windows; and • The IR system is boresighted. APPLICATION High-voltage environment • Detecting loose strands, bolts and nuts; • Detecting Corona discharges on insulator discs; • Detecting... and locating spark gaps; • Detecting and locating RIV sources; • Audit sub-stations and transmission lines for audio noise and Corona activities. RECORDINGS / APPLICATIONS REPORTING TOOL: MultiSOFT • Image handling software for grabbing, processing...

  20. Multivariate statistical analysis for x-ray photoelectron spectroscopy spectral imaging: Effect of image acquisition time

    International Nuclear Information System (INIS)

    Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.

    2004-01-01

    The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images

  1. Composite multi-lobe descriptor for cross spectral face recognition: matching active IR to visible light images

    Science.gov (United States)

    Cao, Zhicheng; Schmid, Natalia A.

    2015-05-01

    Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.

  2. Multi-material decomposition of spectral CT images

    Science.gov (United States)

    Mendonça, Paulo R. S.; Bhotika, Rahul; Maddah, Mahnaz; Thomsen, Brian; Dutta, Sandeep; Licato, Paul E.; Joshi, Mukta C.

    2010-04-01

    Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

  3. Automated road network extraction from high spatial resolution multi-spectral imagery

    Science.gov (United States)

    Zhang, Qiaoping

    For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

  4. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Science.gov (United States)

    Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

    2018-01-01

    Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

  5. Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

    Directory of Open Access Journals (Sweden)

    Liang Lu

    2018-03-01

    Full Text Available Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

  6. Identification of a murine erythroblast subpopulation enriched in enucleating events by multi-spectral imaging flow cytometry.

    Science.gov (United States)

    Konstantinidis, Diamantis G; Pushkaran, Suvarnamala; Giger, Katie; Manganaris, Stefanos; Zheng, Yi; Kalfa, Theodosia A

    2014-06-06

    Erythropoiesis in mammals concludes with the dramatic process of enucleation that results in reticulocyte formation. The mechanism of enucleation has not yet been fully elucidated. A common problem encountered when studying the localization of key proteins and structures within enucleating erythroblasts by microscopy is the difficulty to observe a sufficient number of cells undergoing enucleation. We have developed a novel analysis protocol using multiparameter high-speed cell imaging in flow (Multi-Spectral Imaging Flow Cytometry), a method that combines immunofluorescent microscopy with flow cytometry, in order to identify efficiently a significant number of enucleating events, that allows to obtain measurements and perform statistical analysis. We first describe here two in vitro erythropoiesis culture methods used in order to synchronize murine erythroblasts and increase the probability of capturing enucleation at the time of evaluation. Then, we describe in detail the staining of erythroblasts after fixation and permeabilization in order to study the localization of intracellular proteins or lipid rafts during enucleation by multi-spectral imaging flow cytometry. Along with size and DNA/Ter119 staining which are used to identify the orthochromatic erythroblasts, we utilize the parameters "aspect ratio" of a cell in the bright-field channel that aids in the recognition of elongated cells and "delta centroid XY Ter119/Draq5" that allows the identification of cellular events in which the center of Ter119 staining (nascent reticulocyte) is far apart from the center of Draq5 staining (nucleus undergoing extrusion), thus indicating a cell about to enucleate. The subset of the orthochromatic erythroblast population with high delta centroid and low aspect ratio is highly enriched in enucleating cells.

  7. Crop status sensing system by multi-spectral imaging sensor, 1: Image processing and paddy field sensing

    International Nuclear Information System (INIS)

    Ishii, K.; Sugiura, R.; Fukagawa, T.; Noguchi, N.; Shibata, Y.

    2006-01-01

    The objective of the study is to construct a sensing system for precision farming. A Multi-Spectral Imaging Sensor (MSIS), which can obtain three images (G. R and NIR) simultaneously, was used for detecting growth status of plants. The sensor was mounted on an unmanned helicopter. An image processing method for acquiring information of crop status with high accuracy was developed. Crop parameters that were measured include SPAD, leaf height, and stems number. Both direct seeding variety and transplant variety of paddy rice were adopted in the research. The result of a field test showed that crop status of both varieties could be detected with sufficient accuracy to apply to precision farming

  8. The design and application of a multi-band IR imager

    Science.gov (United States)

    Li, Lijuan

    2018-02-01

    Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

  9. Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    T. Lahousse

    2011-10-01

    Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  10. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  11. SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

    Science.gov (United States)

    Solomon, J. E.

    1994-01-01

    The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different

  12. Determining fast orientation changes of multi-spectral line cameras from the primary images

    Science.gov (United States)

    Wohlfeil, Jürgen

    2012-01-01

    Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

  13. The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

    Science.gov (United States)

    Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

    2017-09-01

    BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p quantitative data were provided. Negative predictive value also increased (68% vs. 91%, panalysis (64% vs. 86%, p data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

  14. Multi Spectral Fluorescence Imager (MSFI)

    Science.gov (United States)

    Caron, Allison

    2016-01-01

    Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

  15. Technology for detecting spectral radiance by a snapshot multi-imaging spectroradiometer

    Science.gov (United States)

    Zuber, Ralf; Stührmann, Ansgar; Gugg-Helminger, Anton; Seckmeyer, Gunther

    2017-12-01

    Technologies to determine spectral sky radiance distributions have evolved in recent years and have enabled new applications in remote sensing, for sky radiance measurements, in biological/diagnostic applications and luminance measurements. Most classical spectral imaging radiance technologies are based on mechanical and/or spectral scans. However, these methods require scanning time in which the spectral radiance distribution might change. To overcome this limitation, different so-called snapshot spectral imaging technologies have been developed that enable spectral and spatial non-scanning measurements. We present a new setup based on a facet mirror that is already used in imaging slicing spectrometers. By duplicating the input image instead of slicing it and using a specially designed entrance slit, we are able to select nearly 200 (14 × 14) channels within the field of view (FOV) for detecting spectral radiance in different directions. In addition, a megapixel image of the FOV is captured by an additional RGB camera. This image can be mapped onto the snapshot spectral image. In this paper, the mechanical setup, technical design considerations and first measurement results of a prototype are presented. For a proof of concept, the device is radiometrically calibrated and a 10 mm × 10 mm test pattern measured within a spectral range of 380 nm-800 nm with an optical bandwidth of 10 nm (full width at half maximum or FWHM). To show its potential in the UV spectral region, zenith sky radiance measurements in the UV of a clear sky were performed. Hence, the prototype was equipped with an entrance optic with a FOV of 0.5° and modified to obtain a radiometrically calibrated spectral range of 280 nm-470 nm with a FWHM of 3 nm. The measurement results have been compared to modeled data processed by UVSPEC, which showed deviations of less than 30%. This is far from being ideal, but an acceptable result with respect to available state

  16. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...

  17. Tissues segmentation based on multi spectral medical images

    Science.gov (United States)

    Li, Ya; Wang, Ying

    2017-11-01

    Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

  18. Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

    Science.gov (United States)

    Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

    2017-07-01

    A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770-810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.

  19. ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

  20. Parametric image reconstruction using spectral analysis of PET projection data

    International Nuclear Information System (INIS)

    Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat

    1998-01-01

    Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)

  1. Multi-spectral and fluorescence diffuse optical tomography of breast cancer

    Science.gov (United States)

    Corlu, Alper

    Multi-spectral and fluorescence diffuse optical tomography (DOT) techniques are explored and applied to image human breast cancer in vivo. Image reconstruction algorithms that utilize first and second order gradient information are described in detail. Breast DOT requires large computational memory and long run times. To this end, parallel computation techniques were developed appropriate to each reconstruction algorithm. A parallel plate DOT instrument developed for breast cancer imaging is described. The system relies heavily on continuous-wave (CW) transmission measurements and utilizes frequency domain (FD) measurements on the reemission side. However, traditional DOT image reconstruction methods based on CW measurements fail to separate tissue absorption and scattering uniquely. In this manuscript, multi-spectral DOT is shown to be capable of minimizing cross-talk and retrieving spectral parameters almost uniquely when the measurement wavelengths are optimized. A theoretical framework to select optimum wavelengths is provided, and tested with computer simulations. Results from phantom spectroscopy experiments and in vivo patient measurements support the notion that multi-spectral methods are superior to traditional DOT image reconstruction schemes. The same breast DOT instrument is improved and utilized to obtain the first in vivo images of human breast cancer based on fluorescence DOT (FDOT). To this end the fluorophore Indocyanine Green (ICG) is injected intravenously and fluorescence excitation and detection are accomplished in the soft-compression, parallel-plane, transmission geometry using laser sources at 786 nm and spectrally filtered CCD detection. Careful phantom and in vivo measurements are carried on to assure that the signals are due to ICG fluorescence, rather than tissue autofluorescence and excitation light leakage. An in vivo measurement protocol is designed to maximize the ICG contrast by acquiring full fluorescence tomographic scan during

  2. Optimization of compressive 4D-spatio-spectral snapshot imaging

    Science.gov (United States)

    Zhao, Xia; Feng, Weiyi; Lin, Lihua; Su, Wu; Xu, Guoqing

    2017-10-01

    In this paper, a modified 3D computational reconstruction method in the compressive 4D-spectro-volumetric snapshot imaging system is proposed for better sensing spectral information of 3D objects. In the design of the imaging system, a microlens array (MLA) is used to obtain a set of multi-view elemental images (EIs) of the 3D scenes. Then, these elemental images with one dimensional spectral information and different perspectives are captured by the coded aperture snapshot spectral imager (CASSI) which can sense the spectral data cube onto a compressive 2D measurement image. Finally, the depth images of 3D objects at arbitrary depths, like a focal stack, are computed by inversely mapping the elemental images according to geometrical optics. With the spectral estimation algorithm, the spectral information of 3D objects is also reconstructed. Using a shifted translation matrix, the contrast of the reconstruction result is further enhanced. Numerical simulation results verify the performance of the proposed method. The system can obtain both 3D spatial information and spectral data on 3D objects using only one single snapshot, which is valuable in the agricultural harvesting robots and other 3D dynamic scenes.

  3. Piecewise spectrally band-pass for compressive coded aperture spectral imaging

    International Nuclear Information System (INIS)

    Qian Lu-Lu; Lü Qun-Bo; Huang Min; Xiang Li-Bin

    2015-01-01

    Coded aperture snapshot spectral imaging (CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional (2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes, the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed three-dimensional (3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio (PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band. (paper)

  4. [Analysis of sensitive spectral bands for burning status detection using hyper-spectral images of Tiangong-01].

    Science.gov (United States)

    Qin, Xian-Lin; Zhu, Xi; Yang, Fei; Zhao, Kai-Rui; Pang, Yong; Li, Zeng-Yuan; Li, Xu-Zhi; Zhang, Jiu-Xing

    2013-07-01

    To obtain the sensitive spectral bands for detection of information on 4 kinds of burning status, i. e. flaming, smoldering, smoke, and fire scar, with satellite data, analysis was conducted to identify suitable satellite spectral bands for detection of information on these 4 kinds of burning status by using hyper-spectrum images of Tiangong-01 (TG-01) and employing a method combining statistics and spectral analysis. The results show that: in the hyper-spectral images of TG-01, the spectral bands differ obviously for detection of these 4 kinds of burning status; in all hyper-spectral short-wave infrared channels, the reflectance of flaming is higher than that of all other 3 kinds of burning status, and the reflectance of smoke is the lowest; the reflectance of smoke is higher than that of all other 3 kinds of burning status in the channels corresponding to hyper-spectral visible near-infrared and panchromatic sensors. For spectral band selection, more suitable spectral bands for flaming detection are 1 000.0-1 956.0 and 2 020.0-2 400.0 nm; the suitable spectral bands for identifying smoldering are 930.0-1 000.0 and 1 084.0-2 400.0 nm; the suitable spectral bands for smoke detection is in 400.0-920.0 nm; for fire scar detection, it is suitable to select bands with central wavelengths of 900.0-930.0 and 1 300.0-2 400.0 nm, and then to combine them to construct a detection model.

  5. Processing of spectral X-ray data with principal components analysis

    CERN Document Server

    Butler, A P H; Cook, N J; Butzer, J; Schleich, N; Tlustos, L; Scott, N; Grasset, R; de Ruiter, N; Anderson, N G

    2011-01-01

    The goal of the work was to develop a general method for processing spectral x-ray image data. Principle component analysis (PCA) is a well understood technique for multivariate data analysis and so was investigated. To assess this method, spectral (multi-energy) computed tomography (CT) data was obtained using a Medipix2 detector in a MARS-CT (Medipix All Resolution System). PCA was able to separate bone (calcium) from two elements with k-edges in the X-ray spectrum used (iodine and barium) within a mouse. This has potential clinical application in dual-energy CT systems and future Medipix3 based spectral imaging where up to eight energies can be recorded simultaneously with excellent energy resolution. (c) 2010 Elsevier B.V. All rights reserved.

  6. SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

    Science.gov (United States)

    Solomon, J. E.

    1994-01-01

    The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different

  7. Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

    Science.gov (United States)

    Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

    2017-03-01

    Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

  8. Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI Data for Burned Area Discrimination

    Directory of Open Access Journals (Sweden)

    Haiyan Huang

    2016-10-01

    Full Text Available Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance and atmospherically corrected (surface reflectance images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence and non-parametric (decision tree approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.

  9. A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    T. Kavzoglu

    2016-06-01

    Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

  10. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  11. Multi-energy spectral CT: adding value in emergency body imaging.

    Science.gov (United States)

    Punjabi, Gopal V

    2018-04-01

    Most vendors offer scanners capable of dual- or multi-energy computed tomography (CT) imaging. Advantages of multi-energy CT scanning include superior tissue characterization, detection of subtle iodine uptake differences, and opportunities to reduce contrast dose. However, utilization of this technology in the emergency department (ED) remains low. The purpose of this pictorial essay is to illustrate the value of multi-energy CT scanning in emergency body imaging.

  12. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  13. Spectral analysis of mammographic images using a multitaper method

    International Nuclear Information System (INIS)

    Wu Gang; Mainprize, James G.; Yaffe, Martin J.

    2012-01-01

    Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance. Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms). Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias. Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.

  14. Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

    Science.gov (United States)

    Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

    2015-10-01

    In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

  15. Onboard spectral imager data processor

    Science.gov (United States)

    Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

    1999-10-01

    Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

  16. A comparison of dimension reduction methods with application to multi-spectral images of sand used in concrete

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, M. E.; Ersbøll, Bjarne Kjær

    2010-01-01

    This paper presents a comparison of dimension reduction methods based on a novel machine vision application for estimating moisture content in sand used to make concrete. For the application in question it is very important to know the moisture content of the sand so as to ensure good-quality...... sand types were examined with 20-60 images for each type. To reduce the amount of data, features were extracted from the multi-spectral images; the features were summary statistics on single bands and pairs of bands as well as morphological summaries. The number of features (2,016) is high in relation...

  17. Spectral Imaging by Upconversion

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin; Pedersen, Christian; Tidemand-Lichtenberg, Peter

    2011-01-01

    We present a method to obtain spectrally resolved images using upconversion. By this method an image is spectrally shifted from one spectral region to another wavelength. Since the process is spectrally sensitive it allows for a tailored spectral response. We believe this will allow standard...... silicon based cameras designed for visible/near infrared radiation to be used for spectral images in the mid infrared. This can lead to much lower costs for such imaging devices, and a better performance....

  18. High-speed Vibrational Imaging and Spectral Analysis of Lipid Bodies by Compound Raman Microscopy

    OpenAIRE

    Slipchenko, Mikhail N.; Le, Thuc T.; Chen, Hongtao; Cheng, Ji-Xin

    2009-01-01

    Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid-droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We use a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of t...

  19. Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

    Science.gov (United States)

    Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

    2018-02-01

    In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

  20. Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

    Science.gov (United States)

    Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

    2017-05-12

    Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The

  1. Quantitative imaging of excised osteoarthritic cartilage using spectral CT

    Energy Technology Data Exchange (ETDEWEB)

    Rajendran, Kishore; Bateman, Christopher J.; Younis, Raja Aamir; De Ruiter, Niels J.A.; Ramyar, Mohsen; Anderson, Nigel G. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); Loebker, Caroline [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); University of Twente, Department of Developmental BioEngineering, Enschede (Netherlands); Schon, Benjamin S.; Hooper, Gary J.; Woodfield, Tim B.F. [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); Chernoglazov, Alex I. [University of Canterbury, Human Interface Technology Laboratory New Zealand, Christchurch (New Zealand); Butler, Anthony P.H. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); MARS Bioimaging, Christchurch (New Zealand)

    2017-01-15

    To quantify iodine uptake in articular cartilage as a marker of glycosaminoglycan (GAG) content using multi-energy spectral CT. We incubated a 25-mm strip of excised osteoarthritic human tibial plateau in 50 % ionic iodine contrast and imaged it using a small-animal spectral scanner with a cadmium telluride photon-processing detector to quantify the iodine through the thickness of the articular cartilage. We imaged both spectroscopic phantoms and osteoarthritic tibial plateau samples. The iodine distribution as an inverse marker of GAG content was presented in the form of 2D and 3D images after applying a basis material decomposition technique to separate iodine in cartilage from bone. We compared this result with a histological section stained for GAG. The iodine in cartilage could be distinguished from subchondral bone and quantified using multi-energy CT. The articular cartilage showed variation in iodine concentration throughout its thickness which appeared to be inversely related to GAG distribution observed in histological sections. Multi-energy CT can quantify ionic iodine contrast (as a marker of GAG content) within articular cartilage and distinguish it from bone by exploiting the energy-specific attenuation profiles of the associated materials. (orig.)

  2. Hyperspectral small animal fluorescence imaging: spectral selection imaging

    Science.gov (United States)

    Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul

    2008-02-01

    Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

  3. Tomographic spectral imaging: microanalysis in 3D

    International Nuclear Information System (INIS)

    Kotula, P.G.; Keenan, M.R.; Michael, J.R.

    2003-01-01

    Full text: Spectral imaging, where a series of complete x-ray spectra are typically collected from a 2D area, holds great promise for comprehensive near-surface microanalysis. There are however numerous microanalysis problems where 3D chemical information is needed as well. In the SEM, some sort of sectioning (either mechanical or with a focused ion beam (FIB) tool) followed by x-ray mapping has, in the past, been utilized in an attempt to perform 3D microanalysis. Reliance on simple mapping has the potential to miss important chemical features as well as misidentify others. In this paper we will describe the acquisition of serial-section tomographic spectral images (TSI) with a dual-beam FIB/SEM equipped with an EDS system. We will also describe the application of a modified version of our multivariate statistical analysis algorithms to TSIs. Serial sectioning was performed with a FEI DB-235 FIB/SEM. Firstly, the specimen normal was tilted to the optic axis of the FIB column and a trench was milled into the surface of the specimen. A second trench was then milled perpendicular to the first to provide visibility of the entire analysis surface to the x-ray detector. In addition, several fiducial markers were milled into the surface to allow for alignment from slice to slice. The electron column is at an angle of 52 deg to the ion column so the electron beam can 'see' the analysis surface milled by the FIB with no additional specimen tilting or rotation. Likewise the x-ray detector is at a radial angle of 45 deg to the plane of the electron and ion columns (about the electron column) and a take-off-angle of 35 deg with respect to an untilted specimen so it can 'see' the analysis surface as well with no additional sample tilting or rotation. Spectral images were acquired from regions 40 μm wide and 20μm deep for each slice. Approximately 1μm/slice was milled and 10-12 total slices were cut. Spectral images were acquired with a Thermo NORAN Vantage (Digital imaging

  4. Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis

    OpenAIRE

    Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

    2015-01-01

    In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in can...

  5. Multi sensor satellite imagers for commercial remote sensing

    Science.gov (United States)

    Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

    2005-10-01

    This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

  6. Primer on Use of Multi-Spectral and Infra Red Imaging for On-Site Inspections

    Energy Technology Data Exchange (ETDEWEB)

    Henderson, J R

    2010-10-26

    The purpose of an On-Site Inspection (OSI) is to determine whether a nuclear explosion has occurred in violation of the Comprehensive Nuclear Test Ban Treaty (CTBT), and to gather information which might assist in identifying the violator (CTBT, Article IV, Paragraph 35) Multi-Spectral and Infra Red Imaging (MSIR) is allowed by the treaty to detect observables which might help reduce the search area and thus expedite an OSI and make it more effective. MSIR is permitted from airborne measurements, and at and below the surface to search for anomalies and artifacts (CTBT, Protocol, Part II, Paragraph 69b). The three broad types of anomalies and artifacts MSIR is expected to be capable of observing are surface disturbances (disturbed earth, plant stress or anomalous surface materials), human artifacts (man-made roads, buildings and features), and thermal anomalies. The purpose of this Primer is to provide technical information on MSIR relevant to its use for OSI. It is expected that this information may be used for general background information, to inform decisions about the selection and testing of MSIR equipment, to develop operational guidance for MSIR use during an OSI, and to support the development of a training program for OSI Inspectors. References are provided so readers can pursue a topic in more detail than the summary information provided here. The following chapters will provide more information on how MSIR can support an OSI (Section 2), a short summary what Multi-Spectral Imaging and Infra Red Imaging is (Section 3), guidance from the CTBT regarding the use of MSIR (Section 4), and a description of several nuclear explosion scenarios (Section 5) and consequent observables (Section 6). The remaining sections focus on practical aspects of using MSIR for an OSI, such as specification and selection of MSIR equipment, operational considerations for deployment of MISR equipment from an aircraft, and the conduct of field exercises to mature MSIR for an OSI

  7. Hyperspectral imaging of polymer banknotes for building and analysis of spectral library

    Science.gov (United States)

    Lim, Hoong-Ta; Murukeshan, Vadakke Matham

    2017-11-01

    The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.

  8. Specialized Color Targets for Spectral Reflectance Reconstruction of Magnified Images

    Science.gov (United States)

    Kruschwitz, Jennifer D. T.

    Digital images are used almost exclusively instead of film to capture visual information across many scientific fields. The colorimetric color representation within these digital images can be relayed from the digital counts produced by the camera with the use of a known color target. In image capture of magnified images, there is currently no reliable color target that can be used at multiple magnifications and give the user a solid understanding of the color ground truth within those images. The first part of this dissertation included the design, fabrication, and testing of a color target produced with optical interference coated microlenses for use in an off-axis illumination, compound microscope. An ideal target was designed to increase the color gamut for colorimetric imaging and provide the necessary "Block Dye" spectral reflectance profiles across the visible spectrum to reduce the number of color patches necessary for multiple filter imaging systems that rely on statistical models for spectral reflectance reconstruction. There are other scientific disciplines that can benefit from a specialized color target to determine the color ground truth in their magnified images and perform spectral estimation. Not every discipline has the luxury of having a multi-filter imaging system. The second part of this dissertation developed two unique ways of using an interference coated color mirror target: one that relies on multiple light-source angles, and one that leverages a dynamic color change with time. The source multi-angle technique would be used for the microelectronic discipline where the reconstructed spectral reflectance would be used to determine a dielectric film thickness on a silicon substrate, and the time varying technique would be used for a biomedical example to determine the thickness of human tear film.

  9. The spectral combination characteristic of grating and the bi-grating diffraction imaging effect

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper reports on a new property of grating, namely spectral combination, and on bi-grating diffraction imaging that is based on spectral combination. The spectral combination characteristic of a grating is the capability of combining multiple light beams of different wavelengths incident from specific angles into a single beam. The bi-grating diffraction imaging is the formation of the image of an object with two gratings: the first grating disperses the multi-color light beams from the object and the second combines the dispersed light beams to form the image. We gave the conditions necessary for obtaining the spectral combination. We also presented the equations that relate the two gratings’ spatial frequencies, diffraction orders and positions necessary for obtaining the bi-grating diffraction imaging.

  10. A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

    Science.gov (United States)

    Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

    2018-01-01

    Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Snapshot spectral and polarimetric imaging; target identification with multispectral video

    Science.gov (United States)

    Bartlett, Brent D.; Rodriguez, Mikel D.

    2013-05-01

    As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

  12. Multi-Scale Residual Convolutional Neural Network for Haze Removal of Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Hou Jiang

    2018-06-01

    Full Text Available Haze removal is a pre-processing step that operates on at-sensor radiance data prior to the physically based image correction step to enhance hazy imagery visually. Most current haze removal methods focus on point-to-point operations and utilize information in the spectral domain, without taking consideration of the multi-scale spatial information of haze. In this paper, we propose a multi-scale residual convolutional neural network (MRCNN for haze removal of remote sensing images. MRCNN utilizes 3D convolutional kernels to extract spatial–spectral correlation information and abstract features from surrounding neighborhoods for haze transmission estimation. It takes advantage of dilated convolution to aggregate multi-scale contextual information for the purpose of improving its prediction accuracy. Meanwhile, residual learning is utilized to avoid the loss of weak information while deepening the network. Our experiments indicate that MRCNN performs accurately, achieving an extremely low validation error and testing error. The haze removal results of several scenes of Landsat 8 Operational Land Imager (OLI data show that the visibility of the dehazed images is significantly improved, and the color of recovered surface is consistent with the actual scene. Quantitative analysis proves that the dehazed results of MRCNN are superior to the traditional methods and other networks. Additionally, a comparison to haze-free data illustrates the spectral consistency after haze removal and reveals the changes in the vegetation index.

  13. COMBINED ANALYSIS OF IMAGES AND SPECTRAL ENERGY DISTRIBUTIONS OF TAURUS PROTOSTARS

    International Nuclear Information System (INIS)

    Gramajo, Luciana V.; Gomez, Mercedes; Whitney, Barbara A.; Robitaille, Thomas P.

    2010-01-01

    We present an analysis of spectral energy distributions (SEDs), near- and mid-infrared images, and Spitzer spectra of eight embedded Class I/II objects in the Taurus-Auriga molecular cloud. The initial model for each source was chosen using the grid of young stellar objects (YSOs) and SED fitting tool of Robitaille et al. Then the models were refined using the radiative transfer code of Whitney et al. to fit both the spectra and the infrared images of these objects. In general, our models agree with previous published analyses. However, our combined models should provide more reliable determinations of the physical and geometrical parameters since they are derived from SEDs, including the Spitzer spectra, covering the complete spectral range; and high-resolution near-infrared and Spitzer IRAC images. The combination of SED and image modeling better constrains the different components (central source, disk, envelope) of the YSOs. Our derived luminosities are higher, on average, than previous estimates because we account for the viewing angles (usually nearly edge-on) of most of the sources. Our analysis suggests that the standard rotating collapsing protostar model with disks and bipolar cavities works well for the analyzed sample of objects in the Taurus molecular cloud.

  14. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

    Science.gov (United States)

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  15. MultiSpec—a tool for multispectral hyperspectral image data analysis

    Science.gov (United States)

    Biehl, Larry; Landgrebe, David

    2002-12-01

    MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

  16. Geo-oculus: high resolution multi-spectral earth imaging mission from geostationary orbit

    Science.gov (United States)

    Vaillon, L.; Schull, U.; Knigge, T.; Bevillon, C.

    2017-11-01

    Geo-Oculus is a GEO-based Earth observation mission studied by Astrium for ESA in 2008-2009 to complement the Sentinel missions, the space component of the GMES (Global Monitoring for Environment & Security). Indeed Earth imaging from geostationary orbit offers new functionalities not covered by existing LEO observation missions, like real-time monitoring and fast revisit capability of any location within the huge area in visibility of the satellite. This high revisit capability is exploited by the Meteosat meteorogical satellites, but with a spatial resolution (500 m nadir for the third generation) far from most of GMES needs (10 to 100 m). To reach such ground resolution from GEO orbit with adequate image quality, large aperture instruments (> 1 m) and high pointing stability (challenges of such missions. To address the requirements from the GMES user community, the Geo-Oculus mission is a combination of routine observations (daily systematic coverage of European coastal waters) with "on-demand" observation for event monitoring (e.g. disasters, fires and oil slicks). The instrument is a large aperture imaging telescope (1.5 m diameter) offering a nadir spatial sampling of 10.5 m (21 m worst case over Europe, below 52.5°N) in a PAN visible channel used for disaster monitoring. The 22 multi-spectral channels have resolutions over Europe ranging from 40 m in UV/VNIR (0.3 to 1 μm) to 750 m in TIR (10-12 μm).

  17. High-speed vibrational imaging and spectral analysis of lipid bodies by compound Raman microscopy.

    Science.gov (United States)

    Slipchenko, Mikhail N; Le, Thuc T; Chen, Hongtao; Cheng, Ji-Xin

    2009-05-28

    Cells store excess energy in the form of cytoplasmic lipid droplets. At present, it is unclear how different types of fatty acids contribute to the formation of lipid droplets. We describe a compound Raman microscope capable of both high-speed chemical imaging and quantitative spectral analysis on the same platform. We used a picosecond laser source to perform coherent Raman scattering imaging of a biological sample and confocal Raman spectral analysis at points of interest. The potential of the compound Raman microscope was evaluated on lipid bodies of cultured cells and live animals. Our data indicate that the in vivo fat contains much more unsaturated fatty acids (FAs) than the fat formed via de novo synthesis in 3T3-L1 cells. Furthermore, in vivo analysis of subcutaneous adipocytes and glands revealed a dramatic difference not only in the unsaturation level but also in the thermodynamic state of FAs inside their lipid bodies. Additionally, the compound Raman microscope allows tracking of the cellular uptake of a specific fatty acid and its abundance in nascent cytoplasmic lipid droplets. The high-speed vibrational imaging and spectral analysis capability renders compound Raman microscopy an indispensible analytical tool for the study of lipid-droplet biology.

  18. Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

    Science.gov (United States)

    Awan, Ruqayya; Al-Maadeed, Somaya; Al-Saady, Rafif

    2018-01-01

    The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images.

  19. Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

    Science.gov (United States)

    Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

    2013-06-01

    Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

  20. Multi spectral scaling data acquisition system

    International Nuclear Information System (INIS)

    Behere, Anita; Patil, R.D.; Ghodgaonkar, M.D.; Gopalakrishnan, K.R.

    1997-01-01

    In nuclear spectroscopy applications, it is often desired to acquire data at high rate with high resolution. With the availability of low cost computers, it is possible to make a powerful data acquisition system with minimum hardware and software development, by designing a PC plug-in acquisition board. But in using the PC processor for data acquisition, the PC can not be used as a multitasking node. Keeping this in view, PC plug-in acquisition boards with on-board processor find tremendous applications. Transputer based data acquisition board has been designed which can be configured as a high count rate pulse height MCA or as a Multi Spectral Scaler. Multi Spectral Scaling (MSS) is a new technique, in which multiple spectra are acquired in small time frames and are then analyzed. This paper describes the details of this multi spectral scaling data acquisition system. 2 figs

  1. kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2018-03-01

    Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

  2. SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

    Science.gov (United States)

    Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

    2017-03-03

    Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

  3. Estimation of Melanin and Hemoglobin Using Spectral Reflectance Images Reconstructed from a Digital RGB Image by the Wiener Estimation Method

    Directory of Open Access Journals (Sweden)

    Yoshihisa Aizu

    2013-06-01

    Full Text Available A multi-spectral diffuse reflectance imaging method based on a single snap shot of Red-Green-Blue images acquired with the exposure time of 65 ms (15 fps was investigated for estimating melanin concentration, blood concentration, and oxygen saturation in human skin tissue. The technique utilizes the Wiener estimation method to deduce spectral reflectance images instantaneously from an RGB image. Using the resultant absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are numerically deduced in advance by the Monte Carlo simulations for light transport in skin. Oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments on fingers during upper limb occlusion demonstrated the ability of the method to evaluate physiological reactions of human skin.

  4. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

    Directory of Open Access Journals (Sweden)

    Nicolas eRey-Villamizar

    2014-04-01

    Full Text Available In this article, we describe use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis task, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral brain tissue images surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels, 6,000$times$10,000$times$500 voxels with 16 bits/voxel, implying image sizes exceeding 250GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analytics for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment consisting. Our Python script enables efficient data storage and movement between compute and storage servers, logging all processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  5. Spectral Imaging of Portolan Charts

    Science.gov (United States)

    France, Fenella G.; Wilson, Meghan A.; Ghez, Anita

    2018-05-01

    Spectral imaging of Portolan Charts, early nautical charts, provided extensive new information about their construction and creation. The origins of the portolan chart style have been a continual source of perplexity to numerous generations of cartographic historians. The spectral imaging system utilized incorporates a 50 megapixel mono-chrome camera with light emitting diode (LED) illumination panels that cover the range from 365 nm to 1050 nm to capture visible and non-visible information. There is little known about how portolan charts evolved, and what influenced their creation. These early nautical charts began as working navigational tools of medieval mariners, initially made in the 1300s in Italy, Portugal and Spain; however the origin and development of the portolan chart remained shrouded in mystery. Questions about these early navigational charts included whether colorants were commensurate with the time period and geographical location, and if different, did that give insight into trade routes, or possible later additions to the charts? For example; spectral data showed the red pigment on both the 1320 portolan chart and the 1565 Galapagos Islands matched vermillion, an opaque red pigment used since antiquity. The construction of these charts was also of great interest. Spectral imaging with a range of illumination modes revealed the presence of a "hidden circle" often referred to in relation to their construction. This paper will present in-depth analysis of how spectral imaging of the Portolans revealed similarities and differences, new hidden information and shed new light on construction and composition.

  6. Classification of Astaxanthin Colouration of Salmonid Fish using Spectral Imaging and Tricolour Measurement

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Dissing, Bjørn Skovlund; Nielsen, Michael Engelbrecht

    capturing, tricolour CIELAB measurement, and manual SalmoFan inspection. Furthermore it was tested whether the best predictions come from measurements of the steak or the fillet of the fish. Methods used for classication were linear discriminant analysis (LDA), quadratic discriminant analysis (QDA......The goal of this study was to investigate if it is possible to differentiate between rainbow trout (Oncorhynchus mykiss) having been fed with natural or synthetic astaxanthin. Three different techniques were used for visual inspection of the surface colour of the fish meat: multi-spectral image...

  7. Spectral autofluorescence imaging of the retina for drusen detection

    Science.gov (United States)

    Foubister, James J.; Gorman, Alistair; Harvey, Andy; Hemert, Jano van

    2018-02-01

    The presence and characteristics of drusen in retinal images, namely their size, location, and distribution, can be used to aid in the diagnosis and monitoring of Age Related Macular Degeneration (AMD); one of the leading causes for blindness in the elderly population. Current imaging techniques are effective at determining the presence and number of drusen, but fail when it comes to classifying their size and form. These distinctions are important for correctly characterising the disease, especially in the early stages where the development of just one larger drusen can indicate progression. Another challenge for automated detection is in distinguishing them from other retinal features, such as cotton wool spots. We describe the development of a multi-spectral scanning-laser ophthalmoscope that records images of retinal autofluorescence (AF) in four spectral bands. This will offer the potential to detect drusen with improved contrast based on spectral discrimination for automated classification. The resulting improved specificity and sensitivity for their detection offers more reliable characterisation of AMD. We present proof of principle images prior to further system optimisation and clinical trials for assessment of enhanced detection of drusen.

  8. Remote Sensing Image Fusion Based on the Combination Grey Absolute Correlation Degree and IHS Transform

    Directory of Open Access Journals (Sweden)

    Hui LIN

    2014-12-01

    Full Text Available An improved fusion algorithm for multi-source remote sensing images with high spatial resolution and multi-spectral capacity is proposed based on traditional IHS fusion and grey correlation analysis. Firstly, grey absolute correlation degree is used to discriminate non-edge pixels and edge pixels in high-spatial resolution images, by which the weight of intensity component is identified in order to combine it with high-spatial resolution image. Therefore, image fusion is achieved using IHS inverse transform. The proposed method is applied to ETM+ multi-spectral images and panchromatic image, and Quickbird’s multi-spectral images and panchromatic image respectively. The experiments prove that the fusion method proposed in the paper can efficiently preserve spectral information of the original multi-spectral images while enhancing spatial resolution greatly. By comparison and analysis, the proposed fusion algorithm is better than traditional IHS fusion and fusion method based on grey correlation analysis and IHS transform.

  9. Multi-scale and multi-orientation medical image analysis

    NARCIS (Netherlands)

    Haar Romenij, ter B.M.; Deserno, T.M.

    2011-01-01

    Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived

  10. Molecular spectral imaging system for quantitative immunohistochemical analysis of early diabetic retinopathy.

    Science.gov (United States)

    Li, Qingli; Zhang, Jingfa; Wang, Yiting; Xu, Guoteng

    2009-12-01

    A molecular spectral imaging system has been developed based on microscopy and spectral imaging technology. The system is capable of acquiring molecular spectral images from 400 nm to 800 nm with 2 nm wavelength increments. The basic principles, instrumental systems, and system calibration method as well as its applications for the calculation of the stain-uptake by tissues are introduced. As a case study, the system is used for determining the pathogenesis of diabetic retinopathy and evaluating the therapeutic effects of erythropoietin. Some molecular spectral images of retinal sections of normal, diabetic, and treated rats were collected and analyzed. The typical transmittance curves of positive spots stained for albumin and advanced glycation end products are retrieved from molecular spectral data with the spectral response calibration algorithm. To explore and evaluate the protective effect of erythropoietin (EPO) on retinal albumin leakage of streptozotocin-induced diabetic rats, an algorithm based on Beer-Lambert's law is presented. The algorithm can assess the uptake by histologic retinal sections of stains used in quantitative pathology to label albumin leakage and advanced glycation end products formation. Experimental results show that the system is helpful for the ophthalmologist to reveal the pathogenesis of diabetic retinopathy and explore the protective effect of erythropoietin on retinal cells of diabetic rats. It also highlights the potential of molecular spectral imaging technology to provide more effective and reliable diagnostic criteria in pathology.

  11. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  12. Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

    Science.gov (United States)

    Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

    2017-01-01

    Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples

  13. Spectral Unmixing Analysis of Time Series Landsat 8 Images

    Science.gov (United States)

    Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

    2018-05-01

    Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

  14. SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals

    Directory of Open Access Journals (Sweden)

    Jiping Xiong

    2017-03-01

    Full Text Available Although wrist-type photoplethysmographic (hereafter referred to as WPPG sensor signals can measure heart rate quite conveniently, the subjects’ hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

  15. Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

    Directory of Open Access Journals (Sweden)

    Fubiao Feng

    2017-03-01

    Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

  16. MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

    Directory of Open Access Journals (Sweden)

    Y. Di

    2017-05-01

    Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

  17. Validation of spectral methods for the seismic analysis of multi-supported structures

    International Nuclear Information System (INIS)

    Viola, B.

    1999-01-01

    There are many methodologies for the seismic analysis of buildings. When a seism occurs, structures such piping systems in nuclear power plants are subjected to motions that may be different at each support point. Therefore it is necessary to develop methods that take into account the multi-supported effect. In a first time, a bibliography analysis on the different methods that exist has been carried out. The aim was to find a particular method applicable to the study of piping systems. The second step of this work consisted in developing a program that may be used to test and make comparisons on different selected methods. So spectral methods have the advantage to give an estimation of the maximum values for strain in the structure, in reduced calculation time. The time history analysis is used as the reference for the tests. (author)

  18. Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

    Science.gov (United States)

    Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

    2018-06-01

    There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

  19. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2007-01-01

    based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

  20. WE-DE-BRA-07: Megavoltage Spectral Imaging with a Layered Detector

    Energy Technology Data Exchange (ETDEWEB)

    Myronakis, M; Rottmann, J; Berbeco, R [Brigham and Women’s Hospital, Boston, MA (United States); Hu, Y [Dana Farber Cancer Institute, Boston, MA (United States); Wang, A; Shedlock, D; Star-Lack, J [Varian Medical Systems, Palo Alto, CA (United States); Morf, D [Varian Medical Systems, Dattwil, Aargau (Switzerland)

    2016-06-15

    Purpose: The aim of the current work is to investigate the feasibility of megavoltage spectral imaging using a multiple layered detector for enhancement of low contrast detectability through material segmentation and discrimination (such as bone, markers and metal implants). Potentially the technique can be applied to improve detection and reduce dose in Megavoltage Cone Beam Computed Tomography (MV-CBCT). Methods: Experiments were performed with a prototype multi-layer imager (MLI) which has higher detective efficiency and lower noise characteristics than conventional Electronic Portal Imaging Devices (EPIDs). Images of a solid water phantom were acquired at 2.5 MV, 6MV and 6MV without flattening filter (FFF). The following materials were placed within a stack of solid water: aluminum, copper and gold. Material separation was assessed based on Contrast-to-Noise Ratio (CNR) of the weighted image, formed by a weighted subtraction of the images from two layers of the MLI. A range of weighting factors were investigated for material separation. Results: CNR can be minimized for each material by appropriate selection of the subtraction weighting factor. This is equivalent to a selective subtraction of specific materials from the image. Using multiple layers simultaneously also decreases the dose requirement and removes any registration errors. The minimum CNR for aluminum, copper and gold at the weighted image formed with 2.5MV was obtained at weighting factors equal to 0.92, 0.76 and 0.64 respectively. The corresponding values at 6MVFFF were 0.99, 0.92 and 0.78 respectively. Conclusion: In the current work, an MV spectral imaging feasibility study was attempted using a novel multi-layer prototype EPID imager. Initial results suggest that material separation based on spectral differences between different layers is possible. This spectral imaging technique has potential advantages in MV-CBCT for real-time target tracking, patient set-up imaging and adaptive radiotherapy

  1. Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer

    Science.gov (United States)

    Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun

    2018-05-01

    Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.

  2. Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin

    NARCIS (Netherlands)

    Fereidouni, F.; Bader, A.N.; Colonna, A.; Gerritsen, H.C.

    2014-01-01

    Skin contains many autofluorescent components that can be studied using spectral imaging. We employed a spectral phasor method to analyse two photon excited auto-fluorescence and second harmonic generation images of in vivo human skin. This method allows segmentation of images based on spectral

  3. Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images.

    Science.gov (United States)

    Doi, Ryoichi

    2012-09-01

    Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.

  4. Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

    Science.gov (United States)

    Diner, D.; Paradise, S.; Martonchik, J.

    1994-01-01

    In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

  5. Estimation of compound distribution in spectral images of tomatoes using independent component analysis

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.

    2003-01-01

    Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  6. From Digital Imaging to Computer Image Analysis of Fine Art

    Science.gov (United States)

    Stork, David G.

    An expanding range of techniques from computer vision, pattern recognition, image analysis, and computer graphics are being applied to problems in the history of art. The success of these efforts is enabled by the growing corpus of high-resolution multi-spectral digital images of art (primarily paintings and drawings), sophisticated computer vision methods, and most importantly the engagement of some art scholars who bring questions that may be addressed through computer methods. This paper outlines some general problem areas and opportunities in this new inter-disciplinary research program.

  7. A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska

    Science.gov (United States)

    Selkowitz, D.J.

    2010-01-01

    Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets

  8. ℓ0 -based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation

    Science.gov (United States)

    Xu, Xia; Shi, Zhenwei; Pan, Bin

    2018-07-01

    Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem which is NP-h ard, and a relaxation is often used. In this paper, we attempt to deal with ℓ0 problem directly via a multi-objective based method, which is a non-convex manner. The characteristics of hyperspectral images are integrated into the proposed method, which leads to a new spectra and multi-objective based sparse unmixing method (SMoSU). In order to solve the ℓ0 norm optimization problem, the spectral library is encoded in a binary vector, and a bit-wise flipping strategy is used to generate new individuals in the evolution process. However, a multi-objective method usually produces a number of non-dominated solutions, while sparse unmixing requires a single solution. How to make the final decision for sparse unmixing is challenging. To handle this problem, we integrate the spectral characteristic of hyperspectral images into SMoSU. By considering the spectral correlation in hyperspectral data, we improve the Tchebycheff decomposition function in SMoSU via a new regularization item. This regularization item is able to enforce the individual divergence in the evolution process of SMoSU. In this way, the diversity and convergence of population is further balanced, which is beneficial to the concentration of individuals. In the experiments part, three synthetic datasets and one real-world data are used to analyse the effectiveness of SMoSU, and several state-of-art sparse unmixing algorithms are compared.

  9. Multi-channel imaging cytometry with a single detector

    Science.gov (United States)

    Locknar, Sarah; Barton, John; Entwistle, Mark; Carver, Gary; Johnson, Robert

    2018-02-01

    Multi-channel microscopy and multi-channel flow cytometry generate high bit data streams. Multiple channels (both spectral and spatial) are important in diagnosing diseased tissue and identifying individual cells. Omega Optical has developed techniques for mapping multiple channels into the time domain for detection by a single high gain, high bandwidth detector. This approach is based on pulsed laser excitation and a serial array of optical fibers coated with spectral reflectors such that up to 15 wavelength bins are sequentially detected by a single-element detector within 2.5 μs. Our multichannel microscopy system uses firmware running on dedicated DSP and FPGA chips to synchronize the laser, scanning mirrors, and sampling clock. The signals are digitized by an NI board into 14 bits at 60MHz - allowing for 232 by 174 pixel fields in up to 15 channels with 10x over sampling. Our multi-channel imaging cytometry design adds channels for forward scattering and back scattering to the fluorescence spectral channels. All channels are detected within the 2.5 μs - which is compatible with fast cytometry. Going forward, we plan to digitize at 16 bits with an A-toD chip attached to a custom board. Processing these digital signals in custom firmware would allow an on-board graphics processing unit to display imaging flow cytometry data over configurable scanning line lengths. The scatter channels can be used to trigger data buffering when a cell is present in the beam. This approach enables a low cost mechanically robust imaging cytometer.

  10. Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Zhigao Zeng

    2016-01-01

    Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

  11. Biologically-inspired data decorrelation for hyper-spectral imaging

    Directory of Open Access Journals (Sweden)

    Ghita Ovidiu

    2011-01-01

    Full Text Available Abstract Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA, linear discriminant analysis (LDA, wavelet decomposition (WD, or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

  12. Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

    Science.gov (United States)

    Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

    2015-08-01

    A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

  13. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Directory of Open Access Journals (Sweden)

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  14. Front-end vision and multi-scale image analysis multi-scale computer vision theory and applications, written in Mathematica

    CERN Document Server

    Romeny, Bart M Haar

    2008-01-01

    Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective

  15. Multi-spectral optical scanners for commercial earth observation missions

    Science.gov (United States)

    Schröter, Karin; Engel, Wolfgang; Berndt, Klaus

    2017-11-01

    In recent years, a number of commercial Earth observation missions have been initiated with the aim to gather data in the visible and near-infrared wavelength range. Some of these missions aim at medium resolution (5 to 10 m) multi-spectral imaging with the special background of daily revisiting. Typical applications aim at monitoring of farming area for growth control and harvest prediction, irrigation control, or disaster monitoring such as hail damage in farming, or flood survey. In order to arrive at profitable business plans for such missions, it is mandatory to establish the space segment, i.e. the spacecraft with their opto -electronic payloads, at minimum cost while guaranteeing maximum reliability for mission success. As multiple spacecraft are required for daily revisiting, the solutions are typically based on micro-satellites. This paper presents designs for multi-spectral opto-electric scanners for this type of missions. These designs are drive n by minimum mass and power budgets of microsatellites, and the need for minimum cost. As a consequence, it is mandatory to arrive at thermally robust, compact telescope designs. The paper gives a comparison between refractive, catadioptric, and TMA optics. For mirror designs, aluminium and Zerodur mirror technologies are briefly discussed. State-of-the art focal plane designs are presented. The paper also addresses the choice of detector technologies such as CCDs and CMOS Active Pixel Sensors. The electronics of the multi-spectral scanners represent the main design driver regarding power consumption, reliability, and (most often) cost. It can be subdivided into the detector drive electronics, analog and digital data processing chains, the data mass memory unit, formatting and down - linking units, payload control electronics, and local power supply. The paper gives overviews and trade-offs between data compression strategies and electronics solutions, mass memory unit designs, and data formatting approaches

  16. Endoscopic hyperspectral imaging: light guide optimization for spectral light source

    Science.gov (United States)

    Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

    2018-02-01

    Hyperspectral imaging (HSI) is a technology used in remote sensing, food processing and documentation recovery. Recently, this approach has been applied in the medical field to spectrally interrogate regions of interest within respective substrates. In spectral imaging, a two (spatial) dimensional image is collected, at many different (spectral) wavelengths, to sample spectral signatures from different regions and/or components within a sample. Here, we report on the use of hyperspectral imaging for endoscopic applications. Colorectal cancer is the 3rd leading cancer for incidences and deaths in the US. One factor of severity is the miss rate of precancerous/flat lesions ( 65% accuracy). Integrating HSI into colonoscopy procedures could minimize misdiagnosis and unnecessary resections. We have previously reported a working prototype light source with 16 high-powered light emitting diodes (LEDs) capable of high speed cycling and imaging. In recent testing, we have found our current prototype is limited by transmission loss ( 99%) through the multi-furcated solid light guide (lightpipe) and the desired framerate (20-30 fps) could not be achieved. Here, we report on a series of experimental and modeling studies to better optimize the lightpipe and the spectral endoscopy system as a whole. The lightpipe was experimentally evaluated using an integrating sphere and spectrometer (Ocean Optics). Modeling the lightpipe was performed using Monte Carlo optical ray tracing in TracePro (Lambda Research Corp.). Results of these optimization studies will aid in manufacturing a revised prototype with the newly designed light guide and increased sensitivity. Once the desired optical output (5-10 mW) is achieved then the HIS endoscope system will be able to be implemented without adding onto the procedure time.

  17. SPECTRAL FILTRATION OF IMAGES BY MEANS OF DISPERSIVE SYSTEMS

    Directory of Open Access Journals (Sweden)

    I. M. Gulis

    2016-01-01

    Full Text Available Instruments for spectral filtration of images are an important element of the systems used in remote sensing, medical diagnostics, in-process measurements. The aim of this study is analysis of the functional features and characteristics of the proposed two image monochromator versions which are based on dispersive spectral filtering. The first is based on the use of a dispersive monochromator, where collimating and camera lenses form a telescopic system, the dispersive element of which is within the intermediate image plane. The second version is based on an imaging double monochromator with dispersion subtraction by back propagation. For the telescopic system version, the spectral and spatial resolutions are estimated, the latter being limited by aberrations and diffraction from the entrance slit. The device has been numerically simulated and prototyped. It is shown that for the spectral bandwidth 10 nm (visible spectral range, the aberration-limited spot size is from 10–20 μm at the image center to about 30 μm at the image periphery for the image size 23–27 mm. The monochromator with dispersion subtraction enables one to vary the spectral resolution (up to 1 nm and higher by changing the intermediate slit width. But the distinctive feature is a significant change in the selected central wavelength over the image field. The considered designs of dispersive image monochromators look very promising due to the particular advantages over the systems based on tunable filters as regards the spectral resolution, fast tuning, and the spectral contrast. The monochromator based on a telescopic system has a simple design and a rather large image field but it also has a limited light throughput due to small aperture size. The monochromator with dispersion subtraction has higher light throughput, can provide high spectral resolution when recording a full data cube in a series of measuring acts for different dispersive element positions. 

  18. Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

    Science.gov (United States)

    Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

    2018-06-01

    Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.

  19. Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

    International Nuclear Information System (INIS)

    Chen, Q G; Xu, Y; Zhu, H H; Chen, H; Lin, B

    2015-01-01

    A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565–750 nm. The spectral parameter, defined as the ratio of wavebands at 565–750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66–1.06, 1.06–1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems. (paper)

  20. Remote Sensing of Landscapes with Spectral Images

    Science.gov (United States)

    Adams, John B.; Gillespie, Alan R.

    2006-05-01

    Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures

  1. Vegetation index analysis of multi-source remote sensing data in coal mine wasteland

    Energy Technology Data Exchange (ETDEWEB)

    Han, Y.X.; Li, M.Z.; Li, D.L. [China Agricultural University, Beijing (China)

    2007-12-15

    Thirty-six soil samples were collected and their hyperspectral data used to calculate vegetation indices such as a normalised difference vegetation index (NDVI) and a difference vegetation index (DVI). These were evaluated for typical surface object features within the wastelands around Haizhou Opencast Coal Mine in Fuxin city. A principal component analysis to the hyperspectral data was performed, and the result showed that the first and the second principal components satisfactorily accounted for the multi-spectral image information. The panchromatic and multi-spectral images of SPOT5 were then merged. The panchromatic image replaced the first principal component to improve spatial resolution of the image. In addition, the multispectral images and the NDVI image were classified into six types using the unsupervised classification method. The linear quantitative models were built up and the highest correlation coefficients were obtained between the hyperspectral vegetation index and the vegetation index data from the SPOT5 image. The results show that the hyperspectral data and remote sensing images can be used for quantitative estimation of soil nutrients in coal mine wasteland. They can also provide large area surface information for fast and effective decision making regarding revegetation and the monitoring of dynamic change.

  2. Contrast-enhanced spectral mammography vs. mammography and MRI - clinical performance in a multi-reader evaluation

    NARCIS (Netherlands)

    Fallenberg, E.M.; Schmitzberger, F.F.; Amer, H.; Ingold-Heppner, B.; Balleyguier, C.; Diekmann, F.; Engelken, F.; Mann, R.M.; Renz, D.M.; Bick, U.; Hamm, B.; Dromain, C.

    2017-01-01

    OBJECTIVES: To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) to digital mammography (MG) and magnetic resonance imaging (MRI) in a prospective two-centre, multi-reader study. METHODS: One hundred seventy-eight women (mean age 53 years) with invasive breast

  3. PIXE-quantified AXSIA: Elemental mapping by multivariate spectral analysis

    International Nuclear Information System (INIS)

    Doyle, B.L.; Provencio, P.P.; Kotula, P.G.; Antolak, A.J.; Ryan, C.G.; Campbell, J.L.; Barrett, K.

    2006-01-01

    Automated, nonbiased, multivariate statistical analysis techniques are useful for converting very large amounts of data into a smaller, more manageable number of chemical components (spectra and images) that are needed to describe the measurement. We report the first use of the multivariate spectral analysis program AXSIA (Automated eXpert Spectral Image Analysis) developed at Sandia National Laboratories to quantitatively analyze micro-PIXE data maps. AXSIA implements a multivariate curve resolution technique that reduces the spectral image data sets into a limited number of physically realizable and easily interpretable components (including both spectra and images). We show that the principal component spectra can be further analyzed using conventional PIXE programs to convert the weighting images into quantitative concentration maps. A common elemental data set has been analyzed using three different PIXE analysis codes and the results compared to the cases when each of these codes is used to separately analyze the associated AXSIA principal component spectral data. We find that these comparisons are in good quantitative agreement with each other

  4. Particulate characterization by PIXE multivariate spectral analysis

    International Nuclear Information System (INIS)

    Antolak, Arlyn J.; Morse, Daniel H.; Grant, Patrick G.; Kotula, Paul G.; Doyle, Barney L.; Richardson, Charles B.

    2007-01-01

    Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media

  5. Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

    Science.gov (United States)

    Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

    2016-01-01

    The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

  6. Spectral analysis of multi-dimensional self-similar Markov processes

    International Nuclear Information System (INIS)

    Modarresi, N; Rezakhah, S

    2010-01-01

    In this paper we consider a discrete scale invariant (DSI) process {X(t), t in R + } with scale l > 1. We consider a fixed number of observations in every scale, say T, and acquire our samples at discrete points α k , k in W, where α is obtained by the equality l = α T and W = {0, 1, ...}. We thus provide a discrete time scale invariant (DT-SI) process X(.) with the parameter space {α k , k in W}. We find the spectral representation of the covariance function of such a DT-SI process. By providing the harmonic-like representation of multi-dimensional self-similar processes, spectral density functions of them are presented. We assume that the process {X(t), t in R + } is also Markov in the wide sense and provide a discrete time scale invariant Markov (DT-SIM) process with the above scheme of sampling. We present an example of the DT-SIM process, simple Brownian motion, by the above sampling scheme and verify our results. Finally, we find the spectral density matrix of such a DT-SIM process and show that its associated T-dimensional self-similar Markov process is fully specified by {R H j (1), R j H (0), j = 0, 1, ..., T - 1}, where R H j (τ) is the covariance function of jth and (j + τ)th observations of the process.

  7. Automated daily quality control analysis for mammography in a multi-unit imaging center.

    Science.gov (United States)

    Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

    2018-01-01

    Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

  8. Characterisation and geostatistical analysis of clay rocks in underground facilities using hyper-spectral images

    International Nuclear Information System (INIS)

    Becker, J.K.; Marschall, P.; Brunner, P.; Cholet, C.; Renard, P.; Buckley, S.; Kurz, T.

    2012-01-01

    , and are readily available as spectral libraries for use in software processing packages. Since rocks are composites of minerals, their spectra represent a mixture of spectra of the constituent minerals concerning the reflectance. In general, imaging spectrometry allows a semi-quantitative analysis of mineral abundances from rock spectra, for example by analysing the intensity of absorption bands. In many cases a mineral with a unique absorption signature can be correlated to a specific lithological unit, which can be used to trace and map the lithology. Additionally, abundance and spatial variation can be determined from the rock spectra. Common reflection features in sedimentary rocks are typically related to carbonate and clay minerals, hydroxyl, water or iron-bearing material and weathering products. A number of physical properties can influence the intensity of features in the spectral curves of minerals and rocks, such as particle size, angle of incidence, porosity and surface roughness, though the wavelength positions of the absorption features are not changed. Next to the obvious ability to use the hyper-spectral images to 'visually' correlate layers within a rock over a certain distance they can also be used for a more rigorous approach of geostatistical correlation. We have developed a work flow for this approach using the hyper-spectral image classifications: 1. In a first step, image reconstruction must be performed. During the scanning and possibly also later during classification, some areas of the hyper-spectral images may not be completely usable or some pixels may not have been classified. In this case, the 'holes' should be filled using multiple-point geostatistical techniques. 2. In the present example, images at three different resolutions have been taken. It is envisaged to use the high resolution images and simulate the high resolution over the entire rock face in a way that the high resolution simulations are guided by the low resolution images

  9. Information-efficient spectral imaging sensor

    Science.gov (United States)

    Sweatt, William C.; Gentry, Stephen M.; Boye, Clinton A.; Grotbeck, Carter L.; Stallard, Brian R.; Descour, Michael R.

    2003-01-01

    A programmable optical filter for use in multispectral and hyperspectral imaging. The filter splits the light collected by an optical telescope into two channels for each of the pixels in a row in a scanned image, one channel to handle the positive elements of a spectral basis filter and one for the negative elements of the spectral basis filter. Each channel for each pixel disperses its light into n spectral bins, with the light in each bin being attenuated in accordance with the value of the associated positive or negative element of the spectral basis vector. The spectral basis vector is constructed so that its positive elements emphasize the presence of a target and its negative elements emphasize the presence of the constituents of the background of the imaged scene. The attenuated light in the channels is re-imaged onto separate detectors for each pixel and then the signals from the detectors are combined to give an indication of the presence or not of the target in each pixel of the scanned scene. This system provides for a very efficient optical determination of the presence of the target, as opposed to the very data intensive data manipulations that are required in conventional hyperspectral imaging systems.

  10. Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

    Science.gov (United States)

    Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

    2013-11-20

    Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

  11. Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

    Science.gov (United States)

    Likens, W. C.; Wrigley, R. C.

    1984-01-01

    Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

  12. Image Segmentation Based on Constrained Spectral Variance Difference and Edge Penalty

    Directory of Open Access Journals (Sweden)

    Bo Chen

    2015-05-01

    Full Text Available Segmentation, which is usually the first step in object-based image analysis (OBIA, greatly influences the quality of final OBIA results. In many existing multi-scale segmentation algorithms, a common problem is that under-segmentation and over-segmentation always coexist at any scale. To address this issue, we propose a new method that integrates the newly developed constrained spectral variance difference (CSVD and the edge penalty (EP. First, initial segments are produced by a fast scan. Second, the generated segments are merged via a global mutual best-fitting strategy using the CSVD and EP as merging criteria. Finally, very small objects are merged with their nearest neighbors to eliminate the remaining noise. A series of experiments based on three sets of remote sensing images, each with different spatial resolutions, were conducted to evaluate the effectiveness of the proposed method. Both visual and quantitative assessments were performed, and the results show that large objects were better preserved as integral entities while small objects were also still effectively delineated. The results were also found to be superior to those from eCongnition’s multi-scale segmentation.

  13. Color sensitivity of the multi-exposure HDR imaging process

    Science.gov (United States)

    Lenseigne, Boris; Jacobs, Valéry Ann; Withouck, Martijn; Hanselaer, Peter; Jonker, Pieter P.

    2013-04-01

    Multi-exposure high dynamic range(HDR) imaging builds HDR radiance maps by stitching together different views of a same scene with varying exposures. Practically, this process involves converting raw sensor data into low dynamic range (LDR) images, estimate the camera response curves, and use them in order to recover the irradiance for every pixel. During the export, applying white balance settings and image stitching, which both have an influence on the color balance in the final image. In this paper, we use a calibrated quasi-monochromatic light source, an integrating sphere, and a spectrograph in order to evaluate and compare the average spectral response of the image sensor. We finally draw some conclusion about the color consistency of HDR imaging and the additional steps necessary to use multi-exposure HDR imaging as a tool to measure the physical quantities such as radiance and luminance.

  14. The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

    KAUST Repository

    Schillinger, Dominik

    2013-07-01

    The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.

  15. Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

    Science.gov (United States)

    Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

    2017-10-01

    Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

  16. Deep multi-scale convolutional neural network for hyperspectral image classification

    Science.gov (United States)

    Zhang, Feng-zhe; Yang, Xia

    2018-04-01

    In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

  17. Room temperature mid-IR single photon spectral imaging

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

    2012-01-01

    Spectral imaging and detection of mid-infrared (mid-IR) wavelengths are emerging as an enabling technology of great technical and scientific interest; primarily because important chemical compounds display unique and strong mid-IR spectral fingerprints revealing valuable chemical information. Whi...... 20 % for polarized incoherent light at 3 \\mum. The proposed method is relevant for existing and new mid-IR applications like gas analysis and medical diagnostics....

  18. High frame rate multi-resonance imaging refractometry with distributed feedback dye laser sensor

    DEFF Research Database (Denmark)

    Vannahme, Christoph; Dufva, Martin; Kristensen, Anders

    2015-01-01

    imaging refractometry without moving parts is presented. DFB dye lasers are low-cost and highly sensitive refractive index sensors. The unique multi-wavelength DFB laser structure presented here comprises several areas with different grating periods. Imaging in two dimensions of space is enabled...... by analyzing laser light from all areas in parallel with an imaging spectrometer. With this multi-resonance imaging refractometry method, the spatial position in one direction is identified from the horizontal, i.e., spectral position of the multiple laser lines which is obtained from the spectrometer charged...

  19. A Cost Effective Multi-Spectral Scanner for Natural Gas Detection

    Energy Technology Data Exchange (ETDEWEB)

    Yudaya Sivathanu; Jongmook Lim; Vinoo Narayanan; Seonghyeon Park

    2005-12-07

    The objective of this project is to design, fabricate and demonstrate a cost effective, multi-spectral scanner for natural gas leak detection in transmission and distribution pipelines. During the first year of the project, a laboratory version of the multi-spectral scanner was designed, fabricated, and tested at EnUrga Inc. The multi-spectral scanner was also evaluated using a blind Department of Energy study at the Rocky Mountain Oilfield Testing Center. The performance of the scanner was inconsistent during the blind study. However, most of the leaks were outside the view of the multi-spectral scanner that was developed during the first year of the project. Therefore, a definite evaluation of the capability of the scanner was not obtained. Despite the results, sufficient number of plumes was detected fully confirming the feasibility of the multi-spectral scanner. During the second year, the optical design of the scanner was changed to improve the sensitivity of the system. Laboratory tests show that the system can reliably detect small leaks (20 SCFH) at 30 to 50 feet. A prototype scanner was built and evaluated during the second year of the project. Only laboratory evaluations were completed during the second year. The laboratory evaluations show the feasibility of using the scanner to determine natural gas pipeline leaks. Further field evaluations and optimization of the scanner are required before commercialization of the scanner can be initiated.

  20. [Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

    Science.gov (United States)

    Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

    2015-10-01

    Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

  1. Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

    Science.gov (United States)

    Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

    2012-02-01

    Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

  2. ANALYSIS OF CAMOUFLAGE COVER SPECTRAL CHARACTERISTICS BY IMAGING SPECTROMETER

    Directory of Open Access Journals (Sweden)

    A. Y. Kouznetsov

    2016-03-01

    Full Text Available Subject of Research.The paper deals with the problems of detection and identification of objects in hyperspectral imagery. The possibility of object type determination by statistical methods is demonstrated. The possibility of spectral image application for its data type identification is considered. Method. Researching was done by means of videospectral equipment for objects detection at "Fregat" substrate. The postprocessing of hyperspectral information was done with the use of math model of pattern recognition system. The vegetation indexes TCHVI (Three-Channel Vegetation Index and NDVI (Normalized Difference Vegetation Index were applied for quality control of object recognition. Neumann-Pearson criterion was offered as a tool for determination of objects differences. Main Results. We have carried out analysis of the spectral characteristics of summer-typecamouflage cover (Germany. We have calculated the density distribution of vegetation indexes. We have obtained statistical characteristics needed for creation of mathematical model for pattern recognition system. We have shown the applicability of vegetation indices for detection of summer camouflage cover on averdure background. We have presented mathematical model of object recognition based on Neumann-Pearson criterion. Practical Relevance. The results may be useful for specialists in the field of hyperspectral data processing for surface state monitoring.

  3. A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-11-01

    Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

  4. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

    Science.gov (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  5. Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

    Science.gov (United States)

    Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

    2018-06-01

    Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

  6. Multi-wavelength Spectral Analysis of Ellerman Bombs Observed by FISS and IRIS

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Jie; Ding, M. D. [School of Astronomy and Space Science, Nanjing University, Nanjing 210023 (China); Cao, Wenda, E-mail: dmd@nju.edu.cn [Big Bear Solar Observatory, New Jersey Institute of Technology, 40386 North Shore Lane, Big Bear City, CA 92314-9672 (United States)

    2017-04-01

    Ellerman bombs (EBs) are a kind of solar activity that is suggested to occur in the lower solar atmosphere. Recent observations using the Interface Region Imaging Spectrograph (IRIS) show connections between EBs and IRIS bombs (IBs), which imply that EBs might be heated to a much higher temperature (8 × 10{sup 4} K) than previous results. Here we perform a spectral analysis of EBs simultaneously observed by the Fast Imaging Solar Spectrograph and IRIS. The observational results show clear evidence of heating in the lower atmosphere, indicated by the wing enhancement in H α , Ca ii 8542 Å, and Mg ii triplet lines and also by brightenings in images of the 1700 Å and 2832 Å ultraviolet continuum channels. Additionally, the intensity of the Mg ii triplet line is correlated with that of H α when an EB occurs, suggesting the possibility of using the triplet as an alternative way to identify EBs. However, we do not find any signal in IRIS hotter lines (C ii and Si iv). For further analysis, we employ a two-cloud model to fit the two chromospheric lines (H α and Ca ii 8542 Å) simultaneously, and obtain a temperature enhancement of 2300 K for a strong EB. This temperature is among the highest of previous modeling results, albeit still insufficient to produce IB signatures at ultraviolet wavelengths.

  7. Exploiting High Resolution Multi-Seasonal Textural Measures and Spectral Information for Reedbed Mapping

    Directory of Open Access Journals (Sweden)

    Alex Okiemute Onojeghuo

    2016-02-01

    Full Text Available Reedbeds across the UK are amongst the most important habitats for rare and endangered birds, wildlife and organisms. However, over the past century, this valued wetland habitat has experienced a drastic reduction in quality and spatial coverage due to pressures from human related activities. To this end, conservation organisations across the UK have been charged with the task of conserving and expanding this threatened habitat. With this backdrop, the study aimed to develop a methodology for accurate reedbed mapping through the combined use of multi-seasonal texture measures and spectral information contained in high resolution QuickBird satellite imagery. The key objectives were to determine the most effective single-date (autumn or summer and multi-seasonal QuickBird imagery suitable for reedbed mapping over the study area; to evaluate the effectiveness of combining multi-seasonal texture measures and spectral information for reedbed mapping using a variety of combinations; and to evaluate the most suitable classification technique for reedbed mapping from three selected classification techniques, namely maximum likelihood classifier, spectral angular mapper and artificial neural network. Using two selected grey-level co-occurrence textural measures (entropy and angular second moment, a series of experiments were conducted using varied combinations of single-date and multi-seasonal QuickBird imagery. Overall, the results indicate the multi-seasonal pansharpened multispectral bands (eight layers combined with all eight grey level co-occurrence matrix texture measures (entropy and angular second moment computed using windows 3 × 3 and 7 × 7 produced the optimal reedbed (76.5% and overall classification (78.1% accuracies using the maximum likelihood classifier technique. Using the optimal 16 layer multi-seasonal pansharpened multispectral and texture combined image dataset, a total reedbed area of 9.8 hectares was successfully mapped over the

  8. Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

    Science.gov (United States)

    Rendon Santillan, Jojene; Makinano-Santillan, Meriam

    2018-04-01

    We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

  9. Spectral analysis of full field digital mammography data

    International Nuclear Information System (INIS)

    Heine, John J.; Velthuizen, Robert P.

    2002-01-01

    The spectral content of mammograms acquired from using a full field digital mammography (FFDM) system are analyzed. Fourier methods are used to show that the FFDM image power spectra obey an inverse power law; in an average sense, the images may be considered as 1/f fields. Two data representations are analyzed and compared (1) the raw data, and (2) the logarithm of the raw data. Two methods are employed to analyze the power spectra (1) a technique based on integrating the Fourier plane with octave ring sectioning developed previously, and (2) an approach based on integrating the Fourier plane using rings of constant width developed for this work. Both methods allow theoretical modeling. Numerical analysis indicates that the effects due to the transformation influence the power spectra measurements in a statistically significant manner in the high frequency range. However, this effect has little influence on the inverse power law estimation for a given image regardless of the data representation or the theoretical analysis approach. The analysis is presented from two points of view (1) each image is treated independently with the results presented as distributions, and (2) for a given representation, the entire image collection is treated as an ensemble with the results presented as expected values. In general, the constant ring width analysis forms the foundation for a spectral comparison method for finding spectral differences, from an image distribution sense, after applying a nonlinear transformation to the data. The work also shows that power law estimation may be influenced due to the presence of noise in the higher frequency range, which is consistent with the known attributes of the detector efficiency. The spectral modeling and inverse power law determinations obtained here are in agreement with that obtained from the analysis of digitized film-screen images presented previously. The form of the power spectrum for a given image is approximately 1/f 2

  10. Airborne Multi-Spectral Minefield Survey

    Science.gov (United States)

    2005-05-01

    Swedish Defence Research Agency), GEOSPACE (Austria), GTD ( Ingenieria de Sistemas y Software Industrial, Spain), IMEC (Ineruniversity MicroElectronic...RTO-MP-SET-092 18 - 1 UNCLASSIFIED/UNLIMITED UNCLASSIFIED/UNLIMITED Airborne Multi-Spectral Minefield Survey Dirk-Jan de Lange, Eric den...actions is the severe lack of baseline information. To respond to this in a rapid way, cost-efficient data acquisition methods are a key issue. de

  11. Analysis of multi-layered films. [determining dye densities by applying a regression analysis to the spectral response of the composite transparency

    Science.gov (United States)

    Scarpace, F. L.; Voss, A. W.

    1973-01-01

    Dye densities of multi-layered films are determined by applying a regression analysis to the spectral response of the composite transparency. The amount of dye in each layer is determined by fitting the sum of the individual dye layer densities to the measured dye densities. From this, dye content constants are calculated. Methods of calculating equivalent exposures are discussed. Equivalent exposures are a constant amount of energy over a limited band-width that will give the same dye content constants as the real incident energy. Methods of using these equivalent exposures for analysis of photographic data are presented.

  12. The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna

    NARCIS (Netherlands)

    Weimar Acerbi, F.; Clevers, J.G.P.W.; Schaepman, M.E.

    2006-01-01

    Multi-sensor image fusion using the wavelet approach provides a conceptual framework for the improvement of the spatial resolution with minimal distortion of the spectral content of the source image. This paper assesses whether images with a large ratio of spatial resolution can be fused, and

  13. Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation.

    Science.gov (United States)

    Urban, Philipp; Rosen, Mitchell R; Berns, Roy S

    2009-08-01

    Reconstruction of spectral images from camera responses is investigated using an edge preserving spatio-spectral Wiener estimation. A Wiener denoising filter and a spectral reconstruction Wiener filter are combined into a single spatio-spectral filter using local propagation of the noise covariance matrix. To preserve edges the local mean and covariance matrix of camera responses is estimated by bilateral weighting of neighboring pixels. We derive the edge-preserving spatio-spectral Wiener estimation by means of Bayesian inference and show that it fades into the standard Wiener reflectance estimation shifted by a constant reflectance in case of vanishing noise. Simulation experiments conducted on a six-channel camera system and on multispectral test images show the performance of the filter, especially for edge regions. A test implementation of the method is provided as a MATLAB script at the first author's website.

  14. Calibrating spectral images using penalized likelihood

    NARCIS (Netherlands)

    Heijden, van der G.W.A.M.; Glasbey, C.

    2003-01-01

    A new method is presented for automatic correction of distortions and for spectral calibration (which band corresponds to which wavelength) of spectral images recorded by means of a spectrograph. The method consists of recording a bar-like pattern with an illumination source with spectral bands

  15. Multi-spectral CCD camera system for ocean water color and seacoast observation

    Science.gov (United States)

    Zhu, Min; Chen, Shiping; Wu, Yanlin; Huang, Qiaolin; Jin, Weiqi

    2001-10-01

    One of the earth observing instruments on HY-1 Satellite which will be launched in 2001, the multi-spectral CCD camera system, is developed by Beijing Institute of Space Mechanics & Electricity (BISME), Chinese Academy of Space Technology (CAST). In 798 km orbit, the system can provide images with 250 m ground resolution and a swath of 500 km. It is mainly used for coast zone dynamic mapping and oceanic watercolor monitoring, which include the pollution of offshore and coast zone, plant cover, watercolor, ice, terrain underwater, suspended sediment, mudflat, soil and vapor gross. The multi- spectral camera system is composed of four monocolor CCD cameras, which are line array-based, 'push-broom' scanning cameras, and responding for four spectral bands. The camera system adapts view field registration; that is, each camera scans the same region at the same moment. Each of them contains optics, focal plane assembly, electrical circuit, installation structure, calibration system, thermal control and so on. The primary features on the camera system are: (1) Offset of the central wavelength is better than 5 nm; (2) Degree of polarization is less than 0.5%; (3) Signal-to-noise ratio is about 1000; (4) Dynamic range is better than 2000:1; (5) Registration precision is better than 0.3 pixel; (6) Quantization value is 12 bit.

  16. Pattern-based compression of multi-band image data for landscape analysis

    CERN Document Server

    Myers, Wayne L; Patil, Ganapati P

    2006-01-01

    This book describes an integrated approach to using remotely sensed data in conjunction with geographic information systems for landscape analysis. Remotely sensed data are compressed into an analytical image-map that is compatible with the most popular geographic information systems as well as freeware viewers. The approach is most effective for landscapes that exhibit a pronounced mosaic pattern of land cover. The image maps are much more compact than the original remotely sensed data, which enhances utility on the internet. As value-added products, distribution of image-maps is not affected by copyrights on original multi-band image data.

  17. ANALYSIS OF IN-SITU SPECTRAL REFLECTANCE OF SAGO AND OTHER PALMS: IMPLICATIONS FOR THEIR DETECTION IN OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    J. R. Santillan

    2018-04-01

    Full Text Available We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345–1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2. Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

  18. An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

    Science.gov (United States)

    Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

    2017-09-01

    Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

  19. Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

    Science.gov (United States)

    Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

    2013-08-01

    With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

  20. Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

    Directory of Open Access Journals (Sweden)

    Zhongwen Hu

    2016-02-01

    Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

  1. Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

    KAUST Repository

    Zhu, Xiaofeng; Xie, Qing; Zhu, Yonghua; Liu, Xingyi; Zhang, Shichao

    2015-01-01

    This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple

  2. Molecular cytogenetic analysis of human blastocysts andcytotrophoblasts by multi-color FISH and Spectra Imaging analyses

    Energy Technology Data Exchange (ETDEWEB)

    Weier, Jingly F.; Ferlatte, Christy; Baumgartner, Adolf; Jung,Christine J.; Nguyen, Ha-Nam; Chu, Lisa W.; Pedersen, Roger A.; Fisher,Susan J.; Weier, Heinz-Ulrich G.

    2006-02-08

    Numerical chromosome aberrations in gametes typically lead to failed fertilization, spontaneous abortion or a chromosomally abnormal fetus. By means of preimplantation genetic diagnosis (PGD), we now can screen human embryos in vitro for aneuploidy before transferring the embryos to the uterus. PGD allows us to select unaffected embryos for transfer and increases the implantation rate in in vitro fertilization programs. Molecular cytogenetic analyses using multi-color fluorescence in situ hybridization (FISH) of blastomeres have become the major tool for preimplantation genetic screening of aneuploidy. However, current FISH technology can test for only a small number of chromosome abnormalities and hitherto failed to increase the pregnancy rates as expected. We are in the process of developing technologies to score all 24 chromosomes in single cells within a 3 day time limit, which we believe is vital to the clinical setting. Also, human placental cytotrophoblasts (CTBs) at the fetal-maternal interface acquire aneuploidies as they differentiate to an invasive phenotype. About 20-50% of invasive CTB cells from uncomplicated pregnancies were found aneuploidy, suggesting that the acquisition of aneuploidy is an important component of normal placentation, perhaps limiting the proliferative and invasive potential of CTBs. Since most invasive CTBs are interphase cells and possess extreme heterogeneity, we applied multi-color FISH and repeated hybridizations to investigate individual CTBs. In summary, this study demonstrates the strength of Spectral Imaging analysis and repeated hybridizations, which provides a basis for full karyotype analysis of single interphase cells.

  3. Multi-Resolution Wavelet-Transformed Image Analysis of Histological Sections of Breast Carcinomas

    Directory of Open Access Journals (Sweden)

    Hae-Gil Hwang

    2005-01-01

    Full Text Available Multi-resolution images of histological sections of breast cancer tissue were analyzed using texture features of Haar- and Daubechies transform wavelets. Tissue samples analyzed were from ductal regions of the breast and included benign ductal hyperplasia, ductal carcinoma in situ (DCIS, and invasive ductal carcinoma (CA. To assess the correlation between computerized image analysis and visual analysis by a pathologist, we created a two-step classification system based on feature extraction and classification. In the feature extraction step, we extracted texture features from wavelet-transformed images at 10× magnification. In the classification step, we applied two types of classifiers to the extracted features, namely a statistics-based multivariate (discriminant analysis and a neural network. Using features from second-level Haar transform wavelet images in combination with discriminant analysis, we obtained classification accuracies of 96.67 and 87.78% for the training and testing set (90 images each, respectively. We conclude that the best classifier of carcinomas in histological sections of breast tissue are the texture features from the second-level Haar transform wavelet images used in a discriminant function.

  4. ANALYSIS OF MOBILE LASER SCANNING DATA AND MULTI-VIEW IMAGE RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    C. Briese

    2012-07-01

    Full Text Available The combination of laser scanning (LS, active, direct 3D measurement of the object surface and photogrammetry (high geometric and radiometric resolution is widely applied for object reconstruction (e.g. architecture, topography, monitoring, archaeology. Usually the results are a coloured point cloud or a textured mesh. The geometry is typically generated from the laser scanning point cloud and the radiometric information is the result of image acquisition. In the last years, next to significant developments in static (terrestrial LS and kinematic LS (airborne and mobile LS hardware and software, research in computer vision and photogrammetry lead to advanced automated procedures in image orientation and image matching. These methods allow a highly automated generation of 3D geometry just based on image data. Founded on advanced feature detector techniques (like SIFT (Scale Invariant Feature Transform very robust techniques for image orientation were established (cf. Bundler. In a subsequent step, dense multi-view stereo reconstruction algorithms allow the generation of very dense 3D point clouds that represent the scene geometry (cf. Patch-based Multi-View Stereo (PMVS2. Within this paper the usage of mobile laser scanning (MLS and simultaneously acquired image data for an advanced integrated scene reconstruction is studied. For the analysis the geometry of a scene is generated by both techniques independently. Then, the paper focuses on the quality assessment of both techniques. This includes a quality analysis of the individual surface models and a comparison of the direct georeferencing of the images using positional and orientation data of the on board GNSS-INS system and the indirect georeferencing of the imagery by automatic image orientation. For the practical evaluation a dataset from an archaeological monument is utilised. Based on the gained knowledge a discussion of the results is provided and a future strategy for the integration of

  5. Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

    Science.gov (United States)

    Sakamoto, M.; Honda, Y.; Kondo, A.

    2016-06-01

    From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.

  6. Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS).

    Energy Technology Data Exchange (ETDEWEB)

    Speed, Ann Elizabeth; Spahn, Olga Blum; Hsu, Alan Yuan-Chun

    2009-09-01

    Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

  7. Spectral analysis for evaluation of myocardial tracers for medical imaging

    International Nuclear Information System (INIS)

    Huesman, Ronald H.; Reutter, Bryan W.; Marshall, Robert C.

    2000-01-01

    Kinetic analysis of dynamic tracer data is performed with the goal of evaluating myocardial radiotracers for cardiac nuclear medicine imaging. Data from experiments utilizing the isolated rabbit heart model are acquired by sampling the venous blood after introduction of a tracer of interest and a reference tracer. We have taken the approach that the kinetics are properly characterized by an impulse response function which describes the difference between the reference molecule (which does not leave the vasculature) and the molecule of interest which is transported across the capillary boundary and is made available to the cell. Using this formalism we can model the appearance of the tracer of interest in the venous output of the heart as a convolution of the appearance of the reference tracer with the impulse response. In this work we parameterize the impulse response function as the sum of a large number of exponential functions whose predetermined decay constants form a spectrum, and each is required only to have a nonnegative coefficient. This approach, called spectral analysis, has the advantage that it allows conventional compartmental analysis without prior knowledge of the number of compartments which the physiology may require or which the data will support

  8. Skin condition measurement by using multispectral imaging system (Conference Presentation)

    Science.gov (United States)

    Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

    2017-02-01

    There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

  9. A NEW MULTI-SPECTRAL THRESHOLD NORMALIZED DIFFERENCE WATER INDEX (MST-NDWI WATER EXTRACTION METHOD – A CASE STUDY IN YANHE WATERSHED

    Directory of Open Access Journals (Sweden)

    Y. Zhou

    2018-05-01

    Full Text Available Accurate remote sensing water extraction is one of the primary tasks of watershed ecological environment study. Since the Yanhe water system has typical characteristics of a small water volume and narrow river channel, which leads to the difficulty for conventional water extraction methods such as Normalized Difference Water Index (NDWI. A new Multi-Spectral Threshold segmentation of the NDWI (MST-NDWI water extraction method is proposed to achieve the accurate water extraction in Yanhe watershed. In the MST-NDWI method, the spectral characteristics of water bodies and typical backgrounds on the Landsat/TM images have been evaluated in Yanhe watershed. The multi-spectral thresholds (TM1, TM4, TM5 based on maximum-likelihood have been utilized before NDWI water extraction to realize segmentation for a division of built-up lands and small linear rivers. With the proposed method, a water map is extracted from the Landsat/TM images in 2010 in China. An accuracy assessment is conducted to compare the proposed method with the conventional water indexes such as NDWI, Modified NDWI (MNDWI, Enhanced Water Index (EWI, and Automated Water Extraction Index (AWEI. The result shows that the MST-NDWI method generates better water extraction accuracy in Yanhe watershed and can effectively diminish the confusing background objects compared to the conventional water indexes. The MST-NDWI method integrates NDWI and Multi-Spectral Threshold segmentation algorithms, with richer valuable information and remarkable results in accurate water extraction in Yanhe watershed.

  10. Biomarkers and Biological Spectral Imaging

    Science.gov (United States)

    2001-01-23

    G. Sowa, H. H. Mantsch, National Research Council Canada; S. L. Zhang, Unilever Research (USA) 85 Brain tissue charcterization using spectral imaging...image registration and of the expert staff of Hill Top Research in Winnipeg for hosting the hydration study. Financial assistance from Unilever Research

  11. Variational Multi-Scale method with spectral approximation of the sub-scales.

    KAUST Repository

    Dia, Ben Mansour

    2015-01-07

    A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a nite number of modes.

  12. Development of motion image prediction method using principal component analysis

    International Nuclear Information System (INIS)

    Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma

    2012-01-01

    Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)

  13. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-01-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  14. MARS spectral molecular imaging of lamb tissue: data collection and image analysis

    CERN Document Server

    Aamir, R; Bateman, C.J.; Butler, A.P.H.; Butler, P.H.; Anderson, N.G.; Bell, S.T.; Panta, R.K.; Healy, J.L.; Mohr, J.L.; Rajendran, K.; Walsh, M.F.; Ruiter, N.de; Gieseg, S.P.; Woodfield, T.; Renaud, P.F.; Brooke, L.; Abdul-Majid, S.; Clyne, M.; Glendenning, R.; Bones, P.J.; Billinghurst, M.; Bartneck, C.; Mandalika, H.; Grasset, R.; Schleich, N.; Scott, N.; Nik, S.J.; Opie, A.; Janmale, T.; Tang, D.N.; Kim, D.; Doesburg, R.M.; Zainon, R.; Ronaldson, J.P.; Cook, N.J.; Smithies, D.J.; Hodge, K.

    2014-01-01

    Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20 to 140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we ...

  15. Variational Multi-Scale method with spectral approximation of the sub-scales.

    KAUST Repository

    Dia, Ben Mansour; Chá con-Rebollo, Tomas

    2015-01-01

    A variational multi-scale method where the sub-grid scales are computed by spectral approximations is presented. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base

  16. Spectral detector CT-derived virtual non-contrast images: comparison of attenuation values with unenhanced CT.

    Science.gov (United States)

    Ananthakrishnan, Lakshmi; Rajiah, Prabhakar; Ahn, Richard; Rassouli, Negin; Xi, Yin; Soesbe, Todd C; Lewis, Matthew A; Lenkinski, Robert E; Leyendecker, John R; Abbara, Suhny

    2017-03-01

    To assess virtual non-contrast (VNC) images obtained on a detection-based spectral detector CT scanner and determine how attenuation on VNC images derived from various phases of enhanced CT compare to those obtained from true unenhanced images. In this HIPAA compliant, IRB approved prospective multi-institutional study, 46 patients underwent pre- and post-contrast imaging on a prototype dual-layer spectral detector CT between October 2013 and November 2015, yielding 84 unenhanced and VNC pairs (25 arterial, 39 portal venous/nephrographic, 20 urographic). Mean attenuation was measured by one of three readers in the liver, spleen, kidneys, psoas muscle, abdominal aorta, and subcutaneous fat. Equivalence testing was used to determine if the mean difference between unenhanced and VNC attenuation was less than 5, 10, or 15 HU. VNC image quality was assessed on a 5 point scale. Mean difference between unenhanced and VNC attenuation was VNC attenuation were equivalent in all tissues except fat using a threshold of VNC overestimated the HU relative to unenhanced images. VNC image quality was rated as excellent or good in 84% of arterial phase and 85% of nephrographic phase cases, but only 40% of urographic phase. VNC images derived from novel dual layer spectral detector CT demonstrate attenuation values similar to unenhanced images in all tissues evaluated except for subcutaneous fat. Further study is needed to determine if attenuation thresholds currently used clinically for common pathology should be adjusted, particularly for lesions containing fat.

  17. Spectral and dual-energy X-ray imaging for medical applications

    Science.gov (United States)

    Fredenberg, Erik

    2018-01-01

    Spectral imaging is an umbrella term for energy-resolved X-ray imaging in medicine. The technique makes use of the energy dependence of X-ray attenuation to either increase the contrast-to-noise ratio, or to provide quantitative image data and reduce image artefacts by so-called material decomposition. Spectral imaging is not new, but has gained interest in recent years because of rapidly increasing availability of spectral and dual-energy CT and the dawn of energy-resolved photon-counting detectors. This review examines the current technological status of spectral and dual-energy imaging and a number of practical applications of the technology in medicine.

  18. Active spectral imaging nondestructive evaluation (SINDE) camera

    Energy Technology Data Exchange (ETDEWEB)

    Simova, E.; Rochefort, P.A., E-mail: eli.simova@cnl.ca [Canadian Nuclear Laboratories, Chalk River, Ontario (Canada)

    2016-06-15

    A proof-of-concept video camera for active spectral imaging nondestructive evaluation has been demonstrated. An active multispectral imaging technique has been implemented in the visible and near infrared by using light emitting diodes with wavelengths spanning from 400 to 970 nm. This shows how the camera can be used in nondestructive evaluation to inspect surfaces and spectrally identify materials and corrosion. (author)

  19. Microscopic validation of whole mouse micro-metastatic tumor imaging agents using cryo-imaging and sliding organ image registration

    OpenAIRE

    Liu, Yiqiao; Zhou, Bo; Qutaish, Mohammed; Wilson, David L.

    2016-01-01

    We created a metastasis imaging, analysis platform consisting of software and multi-spectral cryo-imaging system suitable for evaluating emerging imaging agents targeting micro-metastatic tumor. We analyzed CREKA-Gd in MRI, followed by cryo-imaging which repeatedly sectioned and tiled microscope images of the tissue block face, providing anatomical bright field and molecular fluorescence, enabling 3D microscopic imaging of the entire mouse with single metastatic cell sensitivity. To register ...

  20. Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

    Science.gov (United States)

    Chiang, Y.; Chen, K.

    2013-12-01

    This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  1. SNAPSHOT SPECTRAL AND COLOR IMAGING USING A REGULAR DIGITAL CAMERA WITH A MONOCHROMATIC IMAGE SENSOR

    Directory of Open Access Journals (Sweden)

    J. Hauser

    2017-10-01

    Full Text Available Spectral imaging (SI refers to the acquisition of the three-dimensional (3D spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. Snapshot spectral imaging (SSI refers to the instantaneous acquisition (in a single shot of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL, weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i an added diffusing and dispersing phase-only static optical element at the entrance pupil (diffuser and (ii tailored compressed sensing (CS methods for digital processing of the diffused and dispersed (DD image recorded on the image sensor. The diffuser is designed to mix the spectral cube data spectrally and spatially and thus to enable convergence in its reconstruction by CS-based algorithms. In addition to performing SSI, this SSI camera is capable to perform color imaging using a monochromatic or gray-scale image sensor without color filter arrays.

  2. Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

    Science.gov (United States)

    Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

    2017-04-01

    Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

  3. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  4. Recent progress of push-broom infrared hyper-spectral imager in SITP

    Science.gov (United States)

    Wang, Yueming; Hu, Weida; Shu, Rong; Li, Chunlai; Yuan, Liyin; Wang, Jianyu

    2017-02-01

    In the past decades, hyper-spectral imaging technologies were well developed in SITP, CAS. Many innovations for system design and key parts of hyper-spectral imager were finished. First airborne hyper-spectral imager operating from VNIR to TIR in the world was emerged in SITP. It is well known as OMIS(Operational Modular Imaging Spectrometer). Some new technologies were introduced to improve the performance of hyper-spectral imaging system in these years. A high spatial space-borne hyper-spectral imager aboard Tiangong-1 spacecraft was launched on Sep.29, 2011. Thanks for ground motion compensation and high optical efficiency prismatic spectrometer, a large amount of hyper-spectral imagery with high sensitivity and good quality were acquired in the past years. Some important phenomena were observed. To diminish spectral distortion and expand field of view, new type of prismatic imaging spectrometer based curved prism were proposed by SITP. A prototype of hyper-spectral imager based spherical fused silica prism were manufactured, which can operate from 400nm 2500nm. We also made progress in the development of LWIR hyper-spectral imaging technology. Compact and low F number LWIR imaging spectrometer was designed, manufactured and integrated. The spectrometer operated in a cryogenically-cooled vacuum box for background radiation restraint. The system performed well during flight experiment in an airborne platform. Thanks high sensitivity FPA and high performance optics, spatial resolution and spectral resolution and SNR of system are improved enormously. However, more work should be done for high radiometric accuracy in the future.

  5. Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

    Science.gov (United States)

    Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

    2012-11-01

    Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

  6. Review of spectral imaging technology in biomedical engineering: achievements and challenges.

    Science.gov (United States)

    Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

    2013-10-01

    Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

  7. Spatio-spectral analysis of ionization times in high-harmonic generation

    Energy Technology Data Exchange (ETDEWEB)

    Soifer, Hadas, E-mail: hadas.soifer@weizmann.ac.il [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Dagan, Michal; Shafir, Dror; Bruner, Barry D. [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel); Ivanov, Misha Yu. [Department of Physics, Imperial College London, South Kensington Campus, SW7 2AZ London (United Kingdom); Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Serbinenko, Valeria; Barth, Ingo; Smirnova, Olga [Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy, Max-Born-Strasse 2A, D-12489 Berlin (Germany); Dudovich, Nirit [Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100 (Israel)

    2013-03-12

    Graphical abstract: A spatio-spectral analysis of the two-color oscillation phase allows us to accurately separate short and long trajectories and reconstruct their ionization times. Highlights: ► We perform a complete spatio-spectral analysis of the high harmonic generation process. ► We analyze the ionization times across the entire spatio-spectral plane of the harmonics. ► We apply this analysis to reconstruct the ionization times of both short and long trajectories. - Abstract: Recollision experiments have been very successful in resolving attosecond scale dynamics. However, such schemes rely on the single atom response, neglecting the macroscopic properties of the interaction and the effects of using multi-cycle laser fields. In this paper we perform a complete spatio-spectral analysis of the high harmonic generation process and resolve the distribution of the subcycle dynamics of the recolliding electron. Specifically, we focus on the measurement of ionization times. Recently, we have demonstrated that the addition of a weak, crossed polarized second harmonic field allows us to resolve the moment of ionization (Shafir, 2012) [1]. In this paper we extend this measurement and perform a complete spatio-spectral analysis. We apply this analysis to reconstruct the ionization times of both short and long trajectories showing good agreement with the quantum path analysis.

  8. Acquisition and visualization techniques for narrow spectral color imaging.

    Science.gov (United States)

    Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

    2013-06-01

    This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

  9. IMPROVEMENT AND EXTENSION OF SHAPE EVALUATION CRITERIA IN MULTI-SCALE IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    M. Sakamoto

    2016-06-01

    Full Text Available From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region’s shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape’s diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape’s reproducibility.

  10. Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

    Science.gov (United States)

    Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

    2013-01-01

    Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

  11. Multi-scale analysis of lung computed tomography images

    CERN Document Server

    Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C

    2007-01-01

    A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.

  12. [Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

    Science.gov (United States)

    Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

    2015-11-01

    With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

  13. [Research on Spectral Polarization Imaging System Based on Static Modulation].

    Science.gov (United States)

    Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

    2015-04-01

    The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

  14. BATMAN: Bayesian Technique for Multi-image Analysis

    Science.gov (United States)

    Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

    2017-04-01

    This paper describes the Bayesian Technique for Multi-image Analysis (BATMAN), a novel image-segmentation technique based on Bayesian statistics that characterizes any astronomical data set containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (I.e. identical signal within the errors). We illustrate its operation and performance with a set of test cases including both synthetic and real integral-field spectroscopic data. The output segmentations adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. The quality of the recovered signal represents an improvement with respect to the input, especially in regions with low signal-to-noise ratio. However, the algorithm may be sensitive to small-scale random fluctuations, and its performance in presence of spatial gradients is limited. Due to these effects, errors may be underestimated by as much as a factor of 2. Our analysis reveals that the algorithm prioritizes conservation of all the statistically significant information over noise reduction, and that the precise choice of the input data has a crucial impact on the results. Hence, the philosophy of BaTMAn is not to be used as a 'black box' to improve the signal-to-noise ratio, but as a new approach to characterize spatially resolved data prior to its analysis. The source code is publicly available at http://astro.ft.uam.es/SELGIFS/BaTMAn.

  15. Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

    KAUST Repository

    Zhu, Xiaofeng

    2015-05-28

    This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.

  16. Regularized image denoising based on spectral gradient optimization

    International Nuclear Information System (INIS)

    Lukić, Tibor; Lindblad, Joakim; Sladoje, Nataša

    2011-01-01

    Image restoration methods, such as denoising, deblurring, inpainting, etc, are often based on the minimization of an appropriately defined energy function. We consider energy functions for image denoising which combine a quadratic data-fidelity term and a regularization term, where the properties of the latter are determined by a used potential function. Many potential functions are suggested for different purposes in the literature. We compare the denoising performance achieved by ten different potential functions. Several methods for efficient minimization of regularized energy functions exist. Most are only applicable to particular choices of potential functions, however. To enable a comparison of all the observed potential functions, we propose to minimize the objective function using a spectral gradient approach; spectral gradient methods put very weak restrictions on the used potential function. We present and evaluate the performance of one spectral conjugate gradient and one cyclic spectral gradient algorithm, and conclude from experiments that both are well suited for the task. We compare the performance with three total variation-based state-of-the-art methods for image denoising. From the empirical evaluation, we conclude that denoising using the Huber potential (for images degraded by higher levels of noise; signal-to-noise ratio below 10 dB) and the Geman and McClure potential (for less noisy images), in combination with the spectral conjugate gradient minimization algorithm, shows the overall best performance

  17. Detecting early stage pressure ulcer on dark skin using multispectral imager

    Science.gov (United States)

    Kong, Linghua; Sprigle, Stephen; Yi, Dingrong; Wang, Chao; Wang, Fengtao; Liu, Fuhan; Wang, Jiwu; Zhao, Futing

    2009-10-01

    This paper introduces a novel idea, innovative technology in building multi spectral imaging based device. The benefit from them is people can have low cost, handheld and standing alone device which makes acquire multi spectral images real time with just a snapshot. The paper for the first time publishes some images got from such prototyped miniaturized multi spectral imager.

  18. Wide-band IR imaging in the NIR-MIR-FIR regions for in situ analysis of frescoes

    Science.gov (United States)

    Daffara, C.; Pezzati, L.; Ambrosini, D.; Paoletti, D.; Di Biase, R.; Mariotti, P. I.; Frosinini, C.

    2011-06-01

    Imaging methods offer several advantages in the field of conservation allowing to perform non-invasive inspection of works of art. In particular, non-invasive techniques based on imaging in different infrared (IR) regions are widely used for the investigation of paintings. Using radiation beyond the visible range, different characteristics of the inspected artwork may be revealed according to the bandwidth acquired. In this paper we present the recent results of a joint project among the two research institutes DIMEG and CNR-INO, and the restoration facility Opificio delle Pietre Dure, concerning the wide-band integration of IR imaging techniques, in the spectral ranges NIR 0.8-2.5 μm, MIR 3-5 μm, and FIR 8-12 μm, for in situ analysis of artworks. A joint, multi-mode use of reflection and thermal bands is proposed for the diagnostics of mural paintings, and it is demonstrated to be an effective tool in inspecting the layered structure. High resolution IR reflectography and, to a greater extent, IR imaging in the 3-5 μm band, are effectively used to characterize the superficial layer of the fresco and to analyze the stratigraphy of different pictorial layers. IR thermography in the 8-12 μm band is used to characterize the support deep structure. The integration of all the data provides a multi- layered and multi-spectral representation of the fresco that yields a comprehensive analysis.

  19. Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis

    Directory of Open Access Journals (Sweden)

    A. Ahmad

    2012-06-01

    Full Text Available Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA of Moderate Resolution Imaging Spectroradiometer (MODIS data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4, three thermal bands (29, 31 and 32, the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect clouds. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.

  20. Canny Edge Detection in Cross-Spectral Fused Images

    Directory of Open Access Journals (Sweden)

    Patricia Suárez

    2017-02-01

    Full Text Available Considering that the images of different spectra provide an ample information that helps a lo in the process of identification and distinction of objects that have unique spectral signatures. In this paper, the use of cross-spectral images in the process of edge detection is evaluated. This study aims to assess the Canny edge detector with two variants. The first relates to the use of merged cross-spectral images and the second the inclusion of morphological filters. To ensure the quality of the data used in this study the GQM (Goal-Question- Metrics, framework, was applied to reduce noise and increase the entropy on images. The metrics obtained in the experiments confirm that the quantity and quality of the detected edges increases significantly after the inclusion of a morphological filter and a channel of near infrared spectrum in the merged images.

  1. GALILEO NIMS SPECTRAL IMAGE CUBES: JUPITER OPERATIONS

    Data.gov (United States)

    National Aeronautics and Space Administration — The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images'...

  2. GALILEO NIMS SPECTRAL IMAGE TUBES: JUPITER OPERATIONS

    Data.gov (United States)

    National Aeronautics and Space Administration — The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images'...

  3. The spectral imaging facility: Setup characterization

    Energy Technology Data Exchange (ETDEWEB)

    De Angelis, Simone, E-mail: simone.deangelis@iaps.inaf.it; De Sanctis, Maria Cristina; Manzari, Paola Olga [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Ammannito, Eleonora [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, Los Angeles, California 90095-1567 (United States); Di Iorio, Tatiana [ENEA, UTMEA-TER, Rome (Italy); Liberati, Fabrizio [Opto Service SrL, Campagnano di Roma (RM) (Italy); Tarchi, Fabio; Dami, Michele; Olivieri, Monica; Pompei, Carlo [Selex ES, Campi Bisenzio (Italy); Mugnuolo, Raffaele [Italian Space Agency, ASI, Spatial Geodesy Center, Matera (Italy)

    2015-09-15

    The SPectral IMager (SPIM) facility is a laboratory visible infrared spectrometer developed to support space borne observations of rocky bodies of the solar system. Currently, this laboratory setup is used to support the DAWN mission, which is in its journey towards the asteroid 1-Ceres, and to support the 2018 Exo-Mars mission in the spectral investigation of the Martian subsurface. The main part of this setup is an imaging spectrometer that is a spare of the DAWN visible infrared spectrometer. The spectrometer has been assembled and calibrated at Selex ES and then installed in the facility developed at the INAF-IAPS laboratory in Rome. The goal of SPIM is to collect data to build spectral libraries for the interpretation of the space borne and in situ hyperspectral measurements of planetary materials. Given its very high spatial resolution combined with the imaging capability, this instrument can also help in the detailed study of minerals and rocks. In this paper, the instrument setup is first described, and then a series of test measurements, aimed to the characterization of the main subsystems, are reported. In particular, laboratory tests have been performed concerning (i) the radiation sources, (ii) the reference targets, and (iii) linearity of detector response; the instrumental imaging artifacts have also been investigated.

  4. Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

    Science.gov (United States)

    Liu, Min; Wang, Xueping; Zhang, Hongzhong

    2018-03-01

    In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Self-training-based spectral image reconstruction for art paintings with multispectral imaging.

    Science.gov (United States)

    Xu, Peng; Xu, Haisong; Diao, Changyu; Ye, Zhengnan

    2017-10-20

    A self-training-based spectral reflectance recovery method was developed to accurately reconstruct the spectral images of art paintings with multispectral imaging. By partitioning the multispectral images with the k-means clustering algorithm, the training samples are directly extracted from the art painting itself to restrain the deterioration of spectral estimation caused by the material inconsistency between the training samples and the art painting. Coordinate paper is used to locate the extracted training samples. The spectral reflectances of the extracted training samples are acquired indirectly with a spectroradiometer, and the circle Hough transform is adopted to detect the circle measuring area of the spectroradiometer. Through simulation and a practical experiment, the implementation of the proposed method is explained in detail, and it is verified to have better reflectance recovery performance than that using the commercial target and is comparable to the approach using a painted color target.

  6. Improving image quality in portal venography with spectral CT imaging

    International Nuclear Information System (INIS)

    Zhao, Li-qin; He, Wen; Li, Jian-ying; Chen, Jiang-hong; Wang, Ke-yang; Tan, Li

    2012-01-01

    Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

  7. Improving image quality in portal venography with spectral CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Li-qin, E-mail: zhaolqzr@sohu.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); He, Wen, E-mail: hewen1724@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Li, Jian-ying, E-mail: jianying.li@med.ge.com [CT Advanced Application and Research, GE Healthcare, 100176 China (China); Chen, Jiang-hong, E-mail: chenjianghong1973@hotmail.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Wang, Ke-yang, E-mail: ke7ke@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Tan, Li, E-mail: Litan@ge.com [CT product, GE Healthcare, 100176 China (China)

    2012-08-15

    Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

  8. FUNSTAT and statistical image representations

    Science.gov (United States)

    Parzen, E.

    1983-01-01

    General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

  9. Simultaneous scoring of 10 chromosomes (9,13,14,15,16,18,21,22,X, and Y) in interphase nuclei by using spectral imaging

    Science.gov (United States)

    Fung, Jingly; Weier, Heinz-Ulli G.; Goldberg, James D.; Pedersen, Roger A.

    1999-06-01

    Numerical aberrations involving parts of or entire chromosomes have detrimental effects on mammalian embryonic, and perinatal development. Only few fetuses with chromosomal imbalances survive to term, and their abnormalities lead to stillbirth or cause severely altered phenotypes in the offspring (such as trisomies involving chromosomes 13, 18, 21, and anomalies of X, and Y). Because aneuploidy of any of the 24 chromosomes will have significant consequences, an optimized preimplantation and prenatal genetic diagnosis (PGD) test will score all the chromosomes. Since most cells to be analyzed will be in interphase rather than metaphase, we developed a rapid procedure for the analysis of interphase cells such as lymphocytes, amniocytes, or early embryonic cells (blastomeres). Our approach was based on in situ hybridization of chromosome-specific non-isotopically labeled DNA probes and Spectral Imaging. The Spectral Imaging system uses an interferometer instead of standard emission filters in a fluorescence microscope to record high resolution spectra from fluorescently stained specimens. This bio-imaging system combines the techniques of fluorescence optical microscopy, charged coupled device imaging, Fourier spectroscopy, light microscopy, and powerful analysis software. The probe set used here allowed simultaneous detection of 10 chromosomes (9, 13, 14, 15, 16, 18, 21, 22, X, Y) in interphase nuclei. Probes were obtained commercially or prepared in-house. Following 16 - 40 h hybridization to interphase cells and removal of unbound probes, image spectra (range 450 - 850 nm, resolution 10 nm) were recorded and analyzed using an SD200 Spectral Imaging system (ASI, Carlsbad, CA). Initially some amniocytes were unscoreable due to their thickness, and fixation protocols had to be modified to achieve satisfactory results. In summary, this study shows the simultaneous detection of at least 10 different chromosomes in interphase cells using a novel approach for multi

  10. A New Multichannel Spectral Imaging Laser Scanning Confocal Microscope

    Directory of Open Access Journals (Sweden)

    Yunhai Zhang

    2013-01-01

    Full Text Available We have developed a new multichannel spectral imaging laser scanning confocal microscope for effective detection of multiple fluorescent labeling in the research of biological tissues. In this paper, the design and key technologies of the system are introduced. Representative results on confocal imaging, 3-dimensional sectioning imaging, and spectral imaging are demonstrated. The results indicated that the system is applicable to multiple fluorescent labeling in biological experiments.

  11. Multi-dimensional imaging

    CERN Document Server

    Javidi, Bahram; Andres, Pedro

    2014-01-01

    Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and

  12. Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM

    International Nuclear Information System (INIS)

    Stamatikos, Michael; Sakamoto, Taka; Band, David L.

    2008-01-01

    We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT's spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade.

  13. Correlative Spectral Analysis of Gamma-Ray Bursts using Swift-BAT and GLAST-GBM

    International Nuclear Information System (INIS)

    Stamatikos, Michael; Sakamoto, Takanori; Band, David L.

    2008-01-01

    We discuss the preliminary results of spectral analysis simulations involving anticipated correlated multi-wavelength observations of gamma-ray bursts (GRBs) using Swift's Burst Alert Telescope (BAT) and the Gamma-Ray Large Area Space Telescope's (GLAST) Burst Monitor (GLAST-GBM), resulting in joint spectral fits, including characteristic photon energy (E peak ) values, for a conservative annual estimate of ∼30 GRBs. The addition of BAT/s spectral response will (i) complement in-orbit calibration efforts of GBM's detector response matrices, (ii) augment GLAST's low energy sensitivity by increasing the ∼20-100 keV effective area, (iii) facilitate ground-based follow-up efforts of GLAST GRBs by increasing GBM's source localization precision, and (iv) help identify a subset of non-triggered GRBs discovered via off-line GBM data analysis. Such multi-wavelength correlative analyses, which have been demonstrated by successful joint-spectral fits of Swift-BAT GRBs with other higher energy detectors such as Konus-WIND and Suzaku-WAM, would enable the study of broad-band spectral and temporal evolution of prompt GRB emission over three energy decades, thus potentially increasing science return without placing additional demands upon mission resources throughout their contemporaneous orbital tenure over the next decade

  14. Spectral mixture analysis for water quality assessment over the Amazon floodplain using Hyperion/EO-1 images

    Directory of Open Access Journals (Sweden)

    Lênio Soares Galvão

    2006-12-01

    Full Text Available Water composition undergoes complex spatial and temporal variations throughout the central Amazon floodplain. This study analyzed the spectral mixtures of the optically active substances (OASs in water with spaceborne hyperspectral images. The test site was located upstream the confluence of Amazon (white water and Tapajós (clear-water rivers, where two Hyperion images were acquired from the Earth Observing One (EO-1 satellite. The first image was acquired on September 16, 2001, during the falling water period of the Amazon River. The second image was acquired on June 23, 2005, at the end of the high water period. The images were pre-processed to remove stripes of anomalous pixels, convert radiance-calibrated data to surface reflectance, mask land, clouds and macrophytes targets, and spectral subset the data within the range of 457-885nm. A sequential procedure with the techniques Minimum Noise Fraction (MNF, Pixel Purity Index (PPI and n-dimensional visualization of the MNF feature space was employed to select end-members from both images. A single set of end-members was gathered to represent the following spectrally unique OASs: clear-water; dissolved organic matter; suspended sediments; and phytoplankton. The Linear Spectral Unmixing algorithm was applied to each Hyperion image in order to map the spatial distribution of these constituents, in terms of sub-pixel fractional abundances. Results showed three patterns of changes in the water quality from high to falling flood periods: decrease of suspended inorganic matter concentration in the Amazon River; increase of suspended inorganic matter and phytoplankton concentrations in varzea lakes; and increase of phytoplankton concentration in the Tapajós River.

  15. Spectral mixture analysis for water quality assessment over the Amazon floodplain using Hyperion/EO-1 images

    Directory of Open Access Journals (Sweden)

    Lênio Soares Galvão

    2007-06-01

    Full Text Available Water composition undergoes complex spatial and temporal variations throughout the central Amazon floodplain. This study analyzed the spectral mixtures of the optically active substances (OASs in water with spaceborne hyperspectral images. The test site was located upstream the confluence of Amazon (white water and Tapajós (clear-water rivers, where two Hyperion images were acquired from the Earth Observing One (EO-1 satellite. The first image was acquired on September 16, 2001, during the falling water period of the Amazon River. The second image was acquired on June 23, 2005, at the end of the high water period. The images were pre-processed to remove stripes of anomalous pixels, convert radiance-calibrated data to surface reflectance, mask land, clouds and macrophytes targets, and spectral subset the data within the range of 457-885nm. A sequential procedure with the techniques Minimum Noise Fraction (MNF, Pixel Purity Index (PPI and n-dimensional visualization of the MNF feature space was employed to select end-members from both images. A single set of end-members was gathered to represent the following spectrally unique OASs: clear-water; dissolved organic matter; suspended sediments; and phytoplankton. The Linear Spectral Unmixing algorithm was applied to each Hyperion image in order to map the spatial distribution of these constituents, in terms of sub-pixel fractional abundances. Results showed three patterns of changes in the water quality from high to falling flood periods: decrease of suspended inorganic matter concentration in the Amazon River; increase of suspended inorganic matter and phytoplankton concentrations in varzea lakes; and increase of phytoplankton concentration in the Tapajós River.

  16. Image enhancement by spectral-error correction for dual-energy computed tomography.

    Science.gov (United States)

    Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

    2011-01-01

    Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

  17. Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

  18. The fabrication of a multi-spectral lens array and its application in assisting color blindness

    Science.gov (United States)

    Di, Si; Jin, Jian; Tang, Guanrong; Chen, Xianshuai; Du, Ruxu

    2016-01-01

    This article presents a compact multi-spectral lens array and describes its application in assisting color-blindness. The lens array consists of 9 microlens, and each microlens is coated with a different color filter. Thus, it can capture different light bands, including red, orange, yellow, green, cyan, blue, violet, near-infrared, and the entire visible band. First, the fabrication process is described in detail. Second, an imaging system is setup and a color blindness testing card is selected as the sample. By the system, the vision results of normal people and color blindness can be captured simultaneously. Based on the imaging results, it is possible to be used for helping color-blindness to recover normal vision.

  19. Fluvial particle characterization using artificial neural network and spectral image processing

    Science.gov (United States)

    Shrestha, Bim Prasad; Gautam, Bijaya; Nagata, Masateru

    2008-03-01

    Sand, chemical waste, microbes and other solid materials flowing with the water bodies are of great significance to us as they cause substantial impact to different sectors including drinking water management, hydropower generation, irrigation, aquatic life preservation and various other socio-ecological factors. Such particles can't completely be avoided due to the high cost of construction and maintenance of the waste-treatment methods. A detailed understanding of solid particles in surface water system can have benefit in effective, economic, environmental and social management of water resources. This paper describes an automated system of fluvial particle characterization based on spectral image processing that lead to the development of devices for monitoring flowing particles in river. Previous research in coherent field has shown that it is possible to automatically classify shapes and sizes of solid particles ranging from 300-400 μm using artificial neural networks (ANN) and image processing. Computer facilitated with hyper spectral and multi spectral images using ANN can further classify fluvial materials into organic, inorganic, biodegradable, bio non degradable and microbes. This makes the method attractive for real time monitoring of particles, sand and microorganism in water bodies at strategic locations. Continuous monitoring can be used to determine the effect of socio-economic activities in upstream rivers, or to monitor solid waste disposal from treatment plants and industries or to monitor erosive characteristic of sand and its contribution to degradation of efficiency of hydropower plant or to identify microorganism, calculate their population and study the impact of their presence. Such system can also be used to characterize fluvial particles for planning effective utilization of water resources in micro-mega hydropower plant, irrigation, aquatic life preservation etc.

  20. Spectral Imaging for Intracranial Stents and Stent Lumen.

    Science.gov (United States)

    Weng, Chi-Lun; Tseng, Ying-Chi; Chen, David Yen-Ting; Chen, Chi-Jen; Hsu, Hui-Ling

    2016-01-01

    Application of computed tomography for monitoring intracranial stents is limited because of stent-related artifacts. Our purpose was to evaluate the effect of gemstone spectral imaging on the intracranial stent and stent lumen. In vitro, we scanned Enterprise stent phantom and a stent-cheese complex using the gemstone spectral imaging protocol. Follow-up gemstone spectral images of 15 consecutive patients with placement of Enterprise from January 2013 to September 2014 were also retrospectively reviewed. We used 70-keV, 140-keV, iodine (water), iodine (calcium), and iodine (hydroxyapatite) images to evaluate their effect on the intracranial stent and stent lumen. Two regions of interest were individually placed in stent lumen and adjacent brain tissue. Contrast-to-noise ratio was measured to determine image quality. The maximal diameter of stent markers was also measured to evaluate stent-related artifact. Two radiologists independently graded the visibility of the lumen at the maker location by using a 4-point scale. The mean of grading score, contrast/noise ratio and maximal diameter of stent markers were compared among all modes. All results were analyzed by SPSS version 20. In vitro, iodine (water) images decreased metallic artifact of stent makers to the greatest degree. The most areas of cheese were observed on iodine (water) images. In vivo, iodine (water) images had the smallest average diameter of stent markers (0.33 ± 0.17mm; P stent lumen (160.03 ±37.79; P stent-related artifacts of Enterprise and enhance contrast of in-stent lumen. Spectral imaging may be considered a noninvasive modality for following-up patients with in-stent stenosis.

  1. Landsat sattelite multi-spectral image classification of land cover and land use changes for GIS-based urbanization analysis in irrigation districts of lower Rio Grande Valley of Texas

    Science.gov (United States)

    The Lower Rio Grande Valley in the south of Texas is experiencing rapid increase of population to bring up urban growth that continues influencing on the irrigation districts in the region. This study evaluated the Landsat satellite multi-spectral imagery to provide information for GIS-based urbaniz...

  2. Classification of high-resolution remote sensing images based on multi-scale superposition

    Science.gov (United States)

    Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

    2017-07-01

    Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

  3. Arcsecond and Sub-arcsedond Imaging with X-ray Multi-Image Interferometer and Imager for (very) small sattelites

    Science.gov (United States)

    Hayashida, K.; Kawabata, T.; Nakajima, H.; Inoue, S.; Tsunemi, H.

    2017-10-01

    The best angular resolution of 0.5 arcsec is realized with the X-ray mirror onborad the Chandra satellite. Nevertheless, further better or comparable resolution is anticipated to be difficult in near future. In fact, the goal of ATHENA telescope is 5 arcsec in the angular resolution. We propose a new type of X-ray interferometer consisting simply of an X-ray absorption grating and an X-ray spectral imaging detector, such as X-ray CCDs or new generation CMOS detectors, by stacking the multi images created with the Talbot interferenece (Hayashida et al. 2016). This system, now we call Multi Image X-ray Interferometer Module (MIXIM) enables arcseconds resolution with very small satellites of 50cm size, and sub-arcseconds resolution with small sattellites. We have performed ground experiments, in which a micro-focus X-ray source, grating with pitch of 4.8μm, and 30 μm pixel detector placed about 1m from the source. We obtained the self-image (interferometirc fringe) of the grating for wide band pass around 10keV. This result corresponds to about 2 arcsec resolution for parrallel beam incidence. The MIXIM is usefull for high angular resolution imaging of relatively bright sources. Search for super massive black holes and resolving AGN torus would be the targets of this system.

  4. A Wide Spectral Range Reflectance and Luminescence Imaging System

    Directory of Open Access Journals (Sweden)

    Tapani Hirvonen

    2013-10-01

    Full Text Available In this study, we introduce a wide spectral range (200–2500 nm imaging system with a 250 μm minimum spatial resolution, which can be freely modified for a wide range of resolutions and measurement geometries. The system has been tested for reflectance and luminescence measurements, but can also be customized for transmittance measurements. This study includes the performance results of the developed system, as well as examples of spectral images. Discussion of the system relates it to existing systems and methods. The wide range spectral imaging system that has been developed is however highly customizable and has great potential in many practical applications.

  5. Hyperspectral image analysis for the determination of alteration minerals in geothermal fields: Çürüksu (Denizli) Graben, Turkey

    Science.gov (United States)

    Uygur, Merve; Karaman, Muhittin; Kumral, Mustafa

    2016-04-01

    Çürüksu (Denizli) Graben hosts various geothermal fields such as Kızıldere, Yenice, Gerali, Karahayıt, and Tekkehamam. Neotectonic activities, which are caused by extensional tectonism, and deep circulation in sub-volcanic intrusions are heat sources of hydrothermal solutions. The temperature of hydrothermal solutions is between 53 and 260 degree Celsius. Phyllic, argillic, silicic, and carbonatization alterations and various hydrothermal minerals have been identified in various research studies of these areas. Surfaced hydrothermal alteration minerals are one set of potential indicators of geothermal resources. Developing the exploration tools to define the surface indicators of geothermal fields can assist in the recognition of geothermal resources. Thermal and hyperspectral imaging and analysis can be used for defining the surface indicators of geothermal fields. This study tests the hypothesis that hyperspectral image analysis based on EO-1 Hyperion images can be used for the delineation and definition of surfaced hydrothermal alteration in geothermal fields. Hyperspectral image analyses were applied to images covering the geothermal fields whose alteration characteristic are known. To reduce data dimensionality and identify spectral endmembers, Kruse's multi-step process was applied to atmospherically and geometrically-corrected hyperspectral images. Minimum Noise Fraction was used to reduce the spectral dimensions and isolate noise in the images. Extreme pixels were identified from high order MNF bands using the Pixel Purity Index. n-Dimensional Visualization was utilized for unique pixel identification. Spectral similarities between pixel spectral signatures and known endmember spectrum (USGS Spectral Library) were compared with Spectral Angle Mapper Classification. EO-1 Hyperion hyperspectral images and hyperspectral analysis are sensitive to hydrothermal alteration minerals, as their diagnostic spectral signatures span the visible and shortwave

  6. Spectral Skyline Separation: Extended Landmark Databases and Panoramic Imaging

    Directory of Open Access Journals (Sweden)

    Dario Differt

    2016-09-01

    Full Text Available Evidence from behavioral experiments suggests that insects use the skyline as a cue for visual navigation. However, changes of lighting conditions, over hours, days or possibly seasons, significantly affect the appearance of the sky and ground objects. One possible solution to this problem is to extract the “skyline” by an illumination-invariant classification of the environment into two classes, ground objects and sky. In a previous study (Insect models of illumination-invariant skyline extraction from UV (ultraviolet and green channels, we examined the idea of using two different color channels available for many insects (UV and green to perform this segmentation. We found out that for suburban scenes in temperate zones, where the skyline is dominated by trees and artificial objects like houses, a “local” UV segmentation with adaptive thresholds applied to individual images leads to the most reliable classification. Furthermore, a “global” segmentation with fixed thresholds (trained on an image dataset recorded over several days using UV-only information is only slightly worse compared to using both the UV and green channel. In this study, we address three issues: First, to enhance the limited range of environments covered by the dataset collected in the previous study, we gathered additional data samples of skylines consisting of minerals (stones, sand, earth as ground objects. We could show that also for mineral-rich environments, UV-only segmentation achieves a quality comparable to multi-spectral (UV and green segmentation. Second, we collected a wide variety of ground objects to examine their spectral characteristics under different lighting conditions. On the one hand, we found that the special case of diffusely-illuminated minerals increases the difficulty to reliably separate ground objects from the sky. On the other hand, the spectral characteristics of this collection of ground objects covers well with the data collected

  7. Accuracy in mineral identification: image spectral and spatial resolutions and mineral spectral properties

    Directory of Open Access Journals (Sweden)

    L. Pompilio

    2006-06-01

    Full Text Available Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed.

  8. The optimal algorithm for Multi-source RS image fusion.

    Science.gov (United States)

    Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

    2016-01-01

    In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

  9. Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging.

    Science.gov (United States)

    Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R

    2017-11-01

    The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues.

  10. iSpectra: An Open Source Toolbox For The Analysis of Spectral Images Recorded on Scanning Electron Microscopes.

    Science.gov (United States)

    Liebske, Christian

    2015-08-01

    iSpectra is an open source and system-independent toolbox for the analysis of spectral images (SIs) recorded on energy-dispersive spectroscopy (EDS) systems attached to scanning electron microscopes (SEMs). The aim of iSpectra is to assign pixels with similar spectral content to phases, accompanied by cumulative phase spectra with superior counting statistics for quantification. Pixel-to-phase assignment starts with a threshold-based pre-sorting of spectra to create groups of pixels with identical elemental budgets, similar to a method described by van Hoek (2014). Subsequent merging of groups and re-assignments of pixels using elemental or principle component histogram plots enables the user to generate chemically and texturally plausible phase maps. A variety of standard image processing algorithms can be applied to groups of pixels to optimize pixel-to-phase assignments, such as morphology operations to account for overlapping excitation volumes over pixels located at phase boundaries. iSpectra supports batch processing and allows pixel-to-phase assignments to be applied to an unlimited amount of SIs, thus enabling phase mapping of large area samples like petrographic thin sections.

  11. Enzyme activity measurement via spectral evolution profiling and PARAFAC

    DEFF Research Database (Denmark)

    Baum, Andreas; Meyer, Anne S.; Garcia, Javier Lopez

    2013-01-01

    The recent advances in multi-way analysis provide new solutions to traditional enzyme activity assessment. In the present study enzyme activity has been determined by monitoring spectral changes of substrates and products in real time. The method relies on measurement of distinct spectral...... fingerprints of the reaction mixture at specific time points during the course of the whole enzyme catalyzed reaction and employs multi-way analysis to detect the spectral changes. The methodology is demonstrated by spectral evolution profiling of Fourier Transform Infrared (FTIR) spectral fingerprints using...

  12. Compact Micro-Imaging Spectrometer (CMIS): Investigation of Imaging Spectroscopy and Its Application to Mars Geology and Astrobiology

    Science.gov (United States)

    Staten, Paul W.

    2005-01-01

    Future missions to Mars will attempt to answer questions about Mars' geological and biological history. The goal of the CMIS project is to design, construct, and test a capable, multi-spectral micro-imaging spectrometer use in such missions. A breadboard instrument has been constructed with a micro-imaging camera and Several multi-wavelength LED illumination rings. Test samples have been chosen for their interest to spectroscopists, geologists and astrobiologists. Preliminary analysis has demonstrated the advantages of isotropic illumination and micro-imaging spectroscopy over spot spectroscopy.

  13. Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

    Science.gov (United States)

    Ghrefat, Habes A.; Goodell, Philip C.

    2011-08-01

    The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen

  14. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    Directory of Open Access Journals (Sweden)

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  15. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    user

    2010-10-04

    Oct 4, 2010 ... Available online at http://www.academicjournals.org/AJEST ... robust technique for predicting optimal image resolution for the mapping of savannah ecosystems was developed. .... whether to purchase multi-spectral imagery acquired by GeoEye-2 ..... Analysis of the spectral behaviour of the pasture class in.

  16. TimeLapseAnalyzer: Multi-target analysis for live-cell imaging and time-lapse microscopy

    DEFF Research Database (Denmark)

    Huth, Johannes; Buchholz, Malte; Kraus, Johann M.

    2011-01-01

    The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in...... counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uniulm. de/ni/mitarbeiter/HKestler/tla......., we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell...

  17. Multi-focus Image Fusion Using Epifluorescence Microscopy for Robust Vascular Segmentation

    OpenAIRE

    Pelapur, Rengarajan; Prasath, Surya; Palaniappan, Kannappan

    2014-01-01

    We are building a computerized image analysis system for Dura Mater vascular network from fluorescence microscopy images. We propose a system that couples a multi-focus image fusion module with a robust adaptive filtering based segmentation. The robust adaptive filtering scheme handles noise without destroying small structures, and the multi focal image fusion considerably improves the overall segmentation quality by integrating information from multiple images. Based on the segmenta...

  18. Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

    Science.gov (United States)

    Itoh, Kazuyoshi

    2015-12-01

    Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

  19. Design of a modified endoscope illuminator for spectral imaging of colorectal tissues

    Science.gov (United States)

    Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

    2017-02-01

    The gold standard for locating colonic polyps is a white light endoscope in a colonoscopy, however, polyps smaller than 5 mm can be easily missed. Modified procedures such as narrow band imaging have shown only marginal increases in detection rates. Spectral imaging is a potential solution to improve the sensitivity and specificity of colonoscopies by providing the ability to distinguish molecular fluorescence differences in tissues. The goal of this work is to implement a spectral endoscopic light source to acquire spectral image data of colorectal tissues. A beta-version endoscope light source was developed, by retrofitting a white light endoscope light source (Olympus, CLK-4) with 16 narrow band LEDs. This redesigned, beta-prototype uses high-power LEDs with a minimum output of 500 mW to provide sufficient spectral output (0.5 mW) through the endoscope. A mounting apparatus was designed to provide sufficient heat dissipation. Here, we report recent results of our tests to characterize the intensity output through the light source and endoscope to determine the flat spectral output for imaging and intensity losses through the endoscope. We also report preliminary spectral imaging data from transverse pig colon that demonstrates the ability to result in working practical spectral data. Preliminary results of this revised prototype spectral endoscope system demonstrate that there is sufficient power to allow the imaging process to continue and potentially determine spectral differences in cancerous and normal tissue from imaging ex vivo pairs. Future work will focus on building a spectral library for the colorectal region and refining the user interface the system for in vivo use.

  20. A novel and compact spectral imaging system based on two curved prisms

    Science.gov (United States)

    Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

    2013-09-01

    As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

  1. Application of computed tomography virtual noncontrast spectral imaging in evaluation of hepatic metastases: a preliminary study.

    Science.gov (United States)

    Tian, Shi-Feng; Liu, Ai-Lian; Liu, Jing-Hong; Sun, Mei-Yu; Wang, He-Qing; Liu, Yi-Jun

    2015-03-05

    The objective was to qualitatively and quantitatively evaluate hepatic metastases using computed tomography (CT) virtual noncontrast (VNC) spectral imaging in a retrospective analysis. Forty hepatic metastases patients underwent CT scans including the conventional true noncontrast (TNC) and the tri-phasic contrast-enhanced dual energy spectral scans in the hepatic arterial, portal venous, and equilibrium phases. The tri-phasic spectral CT images were used to obtain three groups of VNC images including in the arterial (VNCa), venous (VNCv), and equilibrium (VNCe) phase by the material decomposition process using water and iodine as a base material pair. The image quality and the contrast-to-noise ratio (CNR) of metastasis of the four groups were compared with ANOVA analysis. The metastasis detection rates with the four nonenhanced image groups were calculated and compared using the Chi-square test. There were no significant differences in image quality among TNC, VNCa and VNCv images (P > 0.05). The quality of VNCe images was significantly worse than that of other three groups (P 0.05). The metastasis detection rate of the four nonenhanced groups with no statistically significant difference (P > 0.05). The quality of VNCa and VNCv images is identical to that of TNC images, and the metastasis detection rate in VNC images is similar to that in TNC images. VNC images obtained from arterial phase show metastases more clearly. Thus, VNCa imaging may be a surrogate to TNC imaging in hepatic metastasis diagnosis.

  2. Application of Computed Tomography Virtual Noncontrast Spectral Imaging in Evaluation of Hepatic Metastases: A Preliminary Study

    Directory of Open Access Journals (Sweden)

    Shi-Feng Tian

    2015-01-01

    Full Text Available Objective: The objective was to qualitatively and quantitatively evaluate hepatic metastases using computed tomography (CT virtual noncontrast (VNC spectral imaging in a retrospective analysis. Methods: Forty hepatic metastases patients underwent CT scans including the conventional true noncontrast (TNC and the tri-phasic contrast-enhanced dual energy spectral scans in the hepatic arterial, portal venous, and equilibrium phases. The tri-phasic spectral CT images were used to obtain three groups of VNC images including in the arterial (VNCa, venous (VNCv, and equilibrium (VNCe phase by the material decomposition process using water and iodine as a base material pair. The image quality and the contrast-to-noise ratio (CNR of metastasis of the four groups were compared with ANOVA analysis. The metastasis detection rates with the four nonenhanced image groups were calculated and compared using the Chi-square test. Results: There were no significant differences in image quality among TNC, VNCa and VNCv images (P > 0.05. The quality of VNCe images was significantly worse than that of other three groups (P 0.05. The metastasis detection rate of the four nonenhanced groups with no statistically significant difference (P > 0.05. Conclusions: The quality of VNCa and VNCv images is identical to that of TNC images, and the metastasis detection rate in VNC images is similar to that in TNC images. VNC images obtained from arterial phase show metastases more clearly. Thus, VNCa imaging may be a surrogate to TNC imaging in hepatic metastasis diagnosis.

  3. Upconversion based spectral imaging in 6 to 8 μm spectral regime

    DEFF Research Database (Denmark)

    Junaid, Saher; Tidemand-Lichtenberg, Peter; Pedersen, Christian

    2017-01-01

    Spectral imaging in the 6 to 8μm range has great potential for medical diagnostics. Here a novel technique based on frequency upconversion of the infrared images to the near visible for subsequent acquisition using a Si-CCD camera is investigated. The upconversion unit consists of an AgGaS2 crystal...

  4. Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2011-01-01

    In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

  5. Detection of Fusarium in single wheat kernels using spectral Imaging

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Waalwijk, C.; Young, I.T.

    2005-01-01

    Fusarium head blight (FHB) is a harmful fungal disease that occurs in small grains. Non-destructive detection of this disease is traditionally done using spectroscopy or image processing. In this paper the combination of these two in the form of spectral imaging is evaluated. Transmission spectral

  6. Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

    Science.gov (United States)

    August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

    2016-03-01

    Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

  7. ANALYZING SPECTRAL CHARACTERISTICS OF SHADOW AREA FROM ADS-40 HIGH RADIOMETRIC RESOLUTION AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    Y.-T. Hsieh

    2016-06-01

    Full Text Available The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i The DN values in shadow area are much lower than in nonshadow area; (ii DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv The shadow area NIR of vegetation category also shows a strong reflection; (v Generally, vegetation indexes (NDVI still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40 is potential for the extract land cover information of shadow areas.

  8. Spectral CT imaging in the differential diagnosis of necrotic hepatocellular carcinoma and hepatic abscess

    International Nuclear Information System (INIS)

    Yu, Y.; Guo, L.; Hu, C.; Chen, K.

    2014-01-01

    Aim: To explore the value of CT spectral imaging in the differential diagnosis of necrotic hepatocellular carcinoma (nHCC) and hepatic abscess (HA) during the arterial phase (AP) and portal venous phase (PP). Materials and methods: Sixty patients with 36 nHCCs and 24 HAs underwent spectral CT during AP and PP. Iodine or water concentration were measured and the normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) were calculated. The two-sample t-test was used to compare quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Sensitivity and specificity were compared between the qualitative and quantitative studies. Results: NIC and LNR in the AP for the wall of nHCC (0.14 ± 0.04 mg/ml; 2.77 ± 0.74) were higher than those of HA (0.13 ± 0.02 mg/ml; 1.4 ± 0.9). NIC and LNR in the PP for the wall of HA (0.66 ± 0.05 mg/ml; 1.2 ± 0.2) were higher than those of nHCC (0.5 ± 0.11 mg/ml; 0.94 ± 0.12). The differences in NIC in the AP were not significant but the differences in LNR in AP, and NIC and LNR in the PP were significant. The best quantitative parameter was LNR in AP, and a threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively, for differentiating nHCC from HA. Conclusion: CT spectral imaging with quantitative iodine concentration analysis may help to increase the accuracy of differentiating nHCC from HA. - Highlights: • We preliminarily investigate the usefulness of CT spectral imaging in differentiating nHCC from HA. • CT spectral imaging may help differentiate necrotic hepatocellular carcinoma from hepatic abscess. • CT spectral imaging can evaluate the blood supply and necrotic degree of lesions. • Quantitative analysis of iodine concentration provides greater diagnostic confidence

  9. Multimodal ophthalmic imaging using handheld spectrally encoded coherence tomography and reflectometry (SECTR)

    Science.gov (United States)

    Leeburg, Kelsey C.; El-Haddad, Mohamed T.; Malone, Joseph D.; Terrones, Benjamin D.; Tao, Yuankai K.

    2018-02-01

    Scanning laser ophthalmoscopy (SLO) provides high-speed, noninvasive en face imaging of the retinal fundus. Optical coherence tomography (OCT) is the current "gold-standard" for ophthalmic diagnostic imaging and enables depth-resolved visualization of ophthalmic structures and image-based surrogate biomarkers of disease. We present a compact optical and mechanical design for handheld spectrally encoded coherence tomography and reflectometry (SECTR) for multimodality en face spectrally encoded reflectometry (SER) and cross-sectional OCT imaging. We custom-designed a double-pass telecentric scan lens, which halves the size of 4-f optical relays and allowed us to reduce the footprint of our SECTR scan-head by a factor of >2.7x (volume) over our previous design. The double-pass scan lens was optimized for diffraction-limited performance over a +/-10° scan field. SECTR optics and optomechanics were combined in a compact rapid-prototyped enclosure with dimensions 87 x 141.8 x 137 mm (w x h x d). SECTR was implemented using a custom-built 400 kHz 1050 nm swept-source. OCT and SER were simultaneously digitized on dual input channels of a 4 GS/s digitizer at 1.4 GS/s per channel. In vivo human en face SER and cross-sectional OCT images were acquired at 350 fps. OCT volumes of 1000 B-scans were acquired in 2.86 s. We believe clinical translation of our compact handheld design will benefit point-of-care ophthalmic diagnostics in patients who are unable to be imaged on conventional slit-lamp based systems, such as infants and the bedridden. When combined with multi-volumetric registration methods, handheld SECTR will have advantages in motion-artifact free imaging over existing handheld technologies.

  10. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    Science.gov (United States)

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  11. Near-IR Spectral Imaging of Semiconductor Absorption Sites in Integrated Circuits

    Directory of Open Access Journals (Sweden)

    E. C. Samson

    2004-12-01

    Full Text Available We derive spectral maps of absorption sites in integrated circuits (ICs by varying the wavelength of the optical probe within the near-IR range. This method has allowed us to improve the contrast of the acquired images by revealing structures that have a different optical absorption from neighboring sites. A false color composite image from those acquired at different wavelengths is generated from which the response of each semiconductor structure can be deduced. With the aid of the spectral maps, nonuniform absorption was also observed in a semiconductor structure located near an electrical overstress defect. This method may prove important in failure analysis of ICs by uncovering areas exhibiting anomalous absorption, which could improve localization of defective edifices in the semiconductor parts of the microchip

  12. Spectrally constrained NIR tomography for breast imaging: simulations and clinical results

    Science.gov (United States)

    Srinivasan, Subhadra; Pogue, Brian W.; Jiang, Shudong; Dehghani, Hamid; Paulsen, Keith D.

    2005-04-01

    A multi-spectral direct chromophore and scattering reconstruction for frequency domain NIR tomography has been implemented using constraints of the known molar spectra of the chromophores and a Mie theory approximation for scattering. This was tested in a tumor-simulating phantom containing an inclusion with higher hemoglobin, lower oxygenation and contrast in scatter. The recovered images were quantitatively accurate and showed substantial improvement over existing methods; and in addition, showed robust results tested for up to 5% noise in amplitude and phase measurements. When applied to a clinical subject with fibrocystic disease, the tumor was visible in hemoglobin and water, but no decrease in oxygenation was observed, making oxygen saturation, a potential diagnostic indicator.

  13. Radiometric Normalization of Temporal Images Combining Automatic Detection of Pseudo-Invariant Features from the Distance and Similarity Spectral Measures, Density Scatterplot Analysis, and Robust Regression

    Directory of Open Access Journals (Sweden)

    Ana Paula Ferreira de Carvalho

    2013-05-01

    Full Text Available Radiometric precision is difficult to maintain in orbital images due to several factors (atmospheric conditions, Earth-sun distance, detector calibration, illumination, and viewing angles. These unwanted effects must be removed for radiometric consistency among temporal images, leaving only land-leaving radiances, for optimum change detection. A variety of relative radiometric correction techniques were developed for the correction or rectification of images, of the same area, through use of reference targets whose reflectance do not change significantly with time, i.e., pseudo-invariant features (PIFs. This paper proposes a new technique for radiometric normalization, which uses three sequential methods for an accurate PIFs selection: spectral measures of temporal data (spectral distance and similarity, density scatter plot analysis (ridge method, and robust regression. The spectral measures used are the spectral angle (Spectral Angle Mapper, SAM, spectral correlation (Spectral Correlation Mapper, SCM, and Euclidean distance. The spectral measures between the spectra at times t1 and t2 and are calculated for each pixel. After classification using threshold values, it is possible to define points with the same spectral behavior, including PIFs. The distance and similarity measures are complementary and can be calculated together. The ridge method uses a density plot generated from images acquired on different dates for the selection of PIFs. In a density plot, the invariant pixels, together, form a high-density ridge, while variant pixels (clouds and land cover changes are spread, having low density, facilitating its exclusion. Finally, the selected PIFs are subjected to a robust regression (M-estimate between pairs of temporal bands for the detection and elimination of outliers, and to obtain the optimal linear equation for a given set of target points. The robust regression is insensitive to outliers, i.e., observation that appears to deviate

  14. The SiC hardware of the Sentinel-2 multi spectral instrument

    Science.gov (United States)

    Bougoin, Michel; Lavenac, Jérôme

    2017-11-01

    The Sentinel-2 mission is a major part of the GMES (Global Monitoring for Environment and Security) program which has been set up by the European Union, on a joint initiative with the European Space Agency. A pair of identical satellites will observe the earth from a sun-synchronous orbit at 786 km altitude. Astrium is the prime contractor of the satellites and their payload. The MultiSpectral Instrument features a "all-SiC" TMA (Three Mirror Anastygmat) telescope. MSI will provide optical images in 13 spectral bands, in the visible and also the near infra-red range, with a 10 to 60 m resolution and a 290 km wide swath. The Boostec® SiC material is used mainly for its high specific stiffness (Youngs modulus / density) and its high thermal stability (thermal conductivity / coefficient of thermal expansion) which allow to reduce the distortions induced by thermo-elastic stresses. Its high mechanical properties as well as the relevant technology enable to make not only the mirrors but also the structure which holds them and the elements of the focal plane (including some detectors packaging). Due to the required large size, accuracy and shape complexity, developing and manufacturing some of these SiC parts required innovative manufacturing approach. It is reviewed in the present paper.

  15. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  16. Spectral differential imaging detection of planets about nearby stars

    International Nuclear Information System (INIS)

    Smith, W.H.

    1987-01-01

    Direct ground-based optical imaging of planets in orbit about nearby stars may be accomplished by spectral differential imaging using multiple passband acoustooptic filters with a CCD. This technique provides two essential results. First, it provides a means to modulate the stellar flux reflected from a planet while leaving the flux from the star and other sources in the same field of view unmodulated. Second, spectral differential imaging enables the CCD detector to achieve a sufficiently high dynamic range to locate planets near a star in spite of an integrated brightness differential of 5 x 10 8 . Spectral differential imaging at nearby diffraction limited imaging conditions with telescope apodization can reduce the time to conduct a sensitive planetary search to a few hours in some cases. The feasibility of this idea is discussed here and shown to provide, in principle, the discrimination and sensitivity to detect a Jovian-class planet about stars at distances of about 10 parsecs. The detection of brown dwarfs is shown to be feasible as well. 31 references

  17. Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA. Part 2: Novel system Architecture, Information/Knowledge Representation, Algorithm Design and Implementation

    Directory of Open Access Journals (Sweden)

    Luigi Boschetti

    2012-09-01

    Full Text Available According to literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA systems and three-stage iterative geographic object-oriented image analysis (GEOOIA systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the Quality Indexes of Operativeness (OQIs of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO guidelines, this methodological work is split into two parts. Based on an original multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT analysis of the GEOBIA/GEOOIA approaches, the first part of this work promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS image understanding system (RS-IUS, from sub-symbolic statistical model-based (inductive image segmentation to symbolic physical model-based (deductive image preliminary classification capable of accomplishing image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the present second part of this work, a novel hybrid (combined deductive and inductive RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a computational theory (system design, (b information/knowledge representation, (c algorithm design and (d implementation. As proof-of-concept of symbolic physical model-based pre-attentive vision first stage, the spectral knowledge-based, operational, near real-time, multi-sensor, multi-resolution, application-independent Satellite Image Automatic Mapper™ (SIAM™ is selected from existing literature. To the best of these authors’ knowledge, this is the first time a symbolic syntactic inference system, like SIAM™, is made available to the RS community for operational use in a RS-IUS pre-attentive vision first stage

  18. Fast analysis of spectral data using neural networks

    International Nuclear Information System (INIS)

    Roach, C.M.

    1992-01-01

    Fast analysis techniques are highly desirable in experiments where measurements are recorded at high rates. In fusion experiments the processing required to obtain plasma parameters is usually orders of magnitude slower than the data acquisition. Spectroscopic diagnostics suffer greatly from this problem. The extraction of plasma parameters from a measured spectrum typically corresponds to a nonlinear mapping between distinct multi-dimensional spaces. Where no analytic expression for the mapping exists, conventional analysis methods (e.g. least squares) are usually iterative and therefore slow. With this concern in mind a fast spectral analysis method involving neural networks has been investigated. (author) 6 refs., 3 figs

  19. Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections

    Science.gov (United States)

    Duann, Jeng-Ren; Jan, Chia-Ing; Ou-Yang, Mang; Lin, Chia-Yi; Mo, Jen-Feng; Lin, Yung-Jiun; Tsai, Ming-Hsui; Chiou, Jin-Chern

    2013-12-01

    Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).

  20. Automated classification and visualization of healthy and pathological dental tissues based on near-infrared hyper-spectral imaging

    Science.gov (United States)

    Usenik, Peter; Bürmen, Miran; Vrtovec, Tomaž; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

    2011-03-01

    Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots which are difficult to diagnose. If detected early enough, such demineralization can be arrested and reversed by non-surgical means through well established dental treatments (fluoride therapy, anti-bacterial therapy, low intensity laser irradiation). Near-infrared (NIR) hyper-spectral imaging is a new promising technique for early detection of demineralization based on distinct spectral features of healthy and pathological dental tissues. In this study, we apply NIR hyper-spectral imaging to classify and visualize healthy and pathological dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized areas. For this purpose, a standardized teeth database was constructed consisting of 12 extracted human teeth with different degrees of natural dental lesions imaged by NIR hyper-spectral system, X-ray and digital color camera. The color and X-ray images of teeth were presented to a clinical expert for localization and classification of the dental tissues, thereby obtaining the gold standard. Principal component analysis was used for multivariate local modeling of healthy and pathological dental tissues. Finally, the dental tissues were classified by employing multiple discriminant analysis. High agreement was observed between the resulting classification and the gold standard with the classification sensitivity and specificity exceeding 85 % and 97 %, respectively. This study demonstrates that NIR hyper-spectral imaging has considerable diagnostic potential for imaging hard dental tissues.

  1. Stable multi-domain spectral penalty methods for fractional partial differential equations

    Science.gov (United States)

    Xu, Qinwu; Hesthaven, Jan S.

    2014-01-01

    We propose stable multi-domain spectral penalty methods suitable for solving fractional partial differential equations with fractional derivatives of any order. First, a high order discretization is proposed to approximate fractional derivatives of any order on any given grids based on orthogonal polynomials. The approximation order is analyzed and verified through numerical examples. Based on the discrete fractional derivative, we introduce stable multi-domain spectral penalty methods for solving fractional advection and diffusion equations. The equations are discretized in each sub-domain separately and the global schemes are obtained by weakly imposed boundary and interface conditions through a penalty term. Stability of the schemes are analyzed and numerical examples based on both uniform and nonuniform grids are considered to highlight the flexibility and high accuracy of the proposed schemes.

  2. The source of multi spectral energy of solar energetic electron

    Energy Technology Data Exchange (ETDEWEB)

    Herdiwijaya, Dhani [Astronomy Division and Bosscha Observatory, Faculty Mathematics and Natural Sciences, Intitute Technology of Bandung, Ganesha 10, Bandung, Indonesia 40132 dhani@as.itb.ac.id (Indonesia)

    2015-04-16

    We study the solar energetic electron distribution obtained from ACE and GOES satellites which have different altitudes and electron spectral energy during the year 1997 to 2011. The electron spectral energies were 0.038–0.315 MeV from EPAM instrument onboard ACE satellite and >2 MeV from GOES satellite. We found that the low electron energy has no correlation with high energy. In spite of we have corrected to the altitude differences. It implied that they originated from time dependent events with different sources and physical processes at the solar atmosphere. The sources of multi spectral energetic electron were related to flare and CME phenomena. However, we also found that high energetic electron comes from coronal hole.

  3. Real-time detection of natural objects using AM-coded spectral matching imager

    Science.gov (United States)

    Kimachi, Akira

    2005-01-01

    This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

  4. MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH

    Data.gov (United States)

    National Aeronautics and Space Administration — MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Multispectral remote sensing images have...

  5. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  6. AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data

    Directory of Open Access Journals (Sweden)

    Daniel Scheffler

    2017-07-01

    Full Text Available Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software, a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.

  7. Applications of cost-effective spectral imaging microscopy in cancer research

    International Nuclear Information System (INIS)

    Barber, P R; Vojnovic, B; Atkin, G; Daley, F M; Everett, S A; Wilson, G D; Gilbey, J D

    2003-01-01

    The application of a cost-effective spectral imager to spatially segmenting absorptive and fluorescent chemical probes on the basis of their spectral characteristics has been demonstrated. The imager comprises a computer-controlled spectrally selective element that allows random access to a bandwidth of 15 nm between 400 and 700 nm. Further, the use of linear un-mixing of the spectral response of a sample at a single pixel has been facilitated using non-negative least squares fitting. Examples are given showing the separation of dye distributions, such as immunohistochemical markers for tumour hypoxia, from multiply stained thin tissue sections, imaged by trans-illumination microscopy. A quantitative study is also presented that shows a correlation between staining intensity and normal versus tumour tissue, and the advantage of reducing the amount of data captured for a particular study is also demonstrated. An example of the application to fluorescence microscopy is also given, showing the separation of green fluorescent protein, Cy3 and Cy5 at a single pixel. The system has been validated against samples of known optical density and of known overlapping combinations of coloured filters. These results confirm the ability of this technique to separate spectral responses that cannot be resolved with conventional colour imaging

  8. Information Retrieval from SAGE II and MFRSR Multi-Spectral Extinction Measurements

    Science.gov (United States)

    Lacis, Andrew A.; Hansen, James E. (Technical Monitor)

    2001-01-01

    Direct beam spectral extinction measurements of solar radiation contain important information on atmospheric composition in a form that is essentially free from multiple scattering contributions that otherwise tend to complicate the data analysis and information retrieval. Such direct beam extinction measurements are available from the solar occultation satellite-based measurements made by the Stratospheric and Aerosol Gas Experiment (SAGE II) instrument and by ground-based Multi-Filter Shadowband Radiometers (MFRSRs). The SAGE II data provide cross-sectional slices of the atmosphere twice per orbit at seven wavelengths between 385 and 1020 nm with approximately 1 km vertical resolution, while the MFRSR data provide atmospheric column measurements at six wavelengths between 415 and 940 nm but at one minute time intervals. We apply the same retrieval technique of simultaneous least-squares fit to the observed spectral extinctions to retrieve aerosol optical depth, effective radius and variance, and ozone, nitrogen dioxide, and water vapor amounts from the SAGE II and MFRSR measurements. The retrieval technique utilizes a physical model approach based on laboratory measurements of ozone and nitrogen dioxide extinction, line-by-line and numerical k-distribution calculations for water vapor absorption, and Mie scattering constraints on aerosol spectral extinction properties. The SAGE II measurements have the advantage of being self-calibrating in that deep space provides an effective zero point for the relative spectral extinctions. The MFRSR measurements require periodic clear-day Langley regression calibration events to maintain accurate knowledge of instrument calibration.

  9. Analysis of a multi-frequency electromagnetic imaging functional for thin, crack-like electromagnetic inclusions

    OpenAIRE

    Park, Won-Kwang

    2012-01-01

    Recently, a non-iterative multi-frequency subspace migration imaging algorithm was developed based on an asymptotic expansion formula for thin, curve-like electromagnetic inclusions and the structure of singular vectors in the Multi-Static Response (MSR) matrix. The present study examines the structure of subspace migration imaging functional and proposes an improved imaging functional weighted by the frequency. We identify the relationship between the imaging functional and Bessel functions ...

  10. Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

    Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

  11. Quantitative spectral K-edge imaging in preclinical photon-counting x-ray computed tomography.

    Science.gov (United States)

    de Vries, Anke; Roessl, Ewald; Kneepkens, Esther; Thran, Axel; Brendel, Bernhard; Martens, Gerhard; Proska, Roland; Nicolay, Klaas; Grüll, Holger

    2015-04-01

    The objective of this study was to investigate the feasibility and the accuracy of spectral computed tomography (spectral CT) to determine the tissue concentrations and localization of high-attenuation, iodine-based contrast agents in mice. Iodine tissue concentrations determined with spectral CT are compared with concentrations measured with single-photon emission computed tomography (SPECT) and inductively coupled plasma mass spectrometry (ICP-MS). All animal procedures were performed according to the US National Institutes of Health principles of laboratory animal care and were approved by the ethical review committee of Maastricht, The Netherlands. Healthy Swiss mice (n = 4) were injected with an iodinated emulsion radiolabeled with indium as multimodal contrast agent for CT and SPECT. The CT and SPECT scans were acquired using a dedicated small-animal SPECT/CT system. Subsequently, scans were performed with a preclinical spectral CT scanner equipped with a photon-counting detector and 6 energy threshold levels. Quantitative data analysis of SPECT and spectral CT scans were obtained using 3-dimensional volumes-of-interest drawing methods. The ICP-MS on dissected organs was performed to determine iodine uptake per organ and was compared with the amounts determined from spectral CT and SPECT. Iodine concentrations obtained with image-processed spectral CT data correlated well with data obtained either with noninvasive SPECT imaging (slope = 0.96, r = 0.75) or with ICP-MS (slope = 0.99, r = 0.89) in tissue samples. This preclinical proof-of-concept study shows the in vivo quantification of iodine concentrations in tissues using spectral CT. Our multimodal imaging approach with spectral CT and SPECT using radiolabeled iodinated emulsions together with ICP-based quantification allows a direct comparison of all methods. Benchmarked against ICP-MS data, spectral CT in the present implementation shows a slight underestimation of organ iodine concentrations compared

  12. Multi-Scale Pattern Recognition for Image Classification and Segmentation

    NARCIS (Netherlands)

    Li, Y.

    2013-01-01

    Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basis

  13. Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

    Science.gov (United States)

    Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

    2017-10-01

    Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

  14. Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.

    Science.gov (United States)

    Sogani, Julie; Morris, Elizabeth A; Kaplan, Jennifer B; D'Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S; Jochelson, Maxine S

    2017-01-01

    Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material-enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board-approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%-76%) and MR imaging (69%-76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55-0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P spectral mammographic and MR images. © RSNA, 2016.

  15. Laser-induced fluorescence imaging of subsurface tissue structures with a volume holographic spatial-spectral imaging system.

    Science.gov (United States)

    Luo, Yuan; Gelsinger-Austin, Paul J; Watson, Jonathan M; Barbastathis, George; Barton, Jennifer K; Kostuk, Raymond K

    2008-09-15

    A three-dimensional imaging system incorporating multiplexed holographic gratings to visualize fluorescence tissue structures is presented. Holographic gratings formed in volume recording materials such as a phenanthrenquinone poly(methyl methacrylate) photopolymer have narrowband angular and spectral transmittance filtering properties that enable obtaining spatial-spectral information within an object. We demonstrate this imaging system's ability to obtain multiple depth-resolved fluorescence images simultaneously.

  16. Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging.

    Science.gov (United States)

    Mo, Changyeun; Kim, Giyoung; Lim, Jongguk; Kim, Moon S; Cho, Hyunjeong; Cho, Byoung-Kwan

    2015-11-20

    Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the 400-1000 nm wavelength range. The optimal wavebands for discriminating between discolored and sound lettuce surfaces were determined using one-way analysis of variance. Multi-spectral imaging algorithms developed using ratio and subtraction functions resulted in enhanced classification accuracy of above 99.9% for discolored and sound areas on both adaxial and abaxial lettuce surfaces. Ratio imaging (RI) and subtraction imaging (SI) algorithms at wavelengths of 552/701 nm and 557-701 nm, respectively, exhibited better classification performances compared to results obtained for all possible two-waveband combinations. These results suggest that hyperspectral reflectance imaging techniques can potentially be used to discriminate between discolored and sound fresh-cut lettuce.

  17. SPECTRAL SMILE CORRECTION IN CRISM HYPERSPECTRAL IMAGES

    Science.gov (United States)

    Ceamanos, X.; Doute, S.

    2009-12-01

    The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is affected by a common artifact in "push-broom" sensors, the so-called "spectral smile". As a consequence, both central wavelength and spectral width of the spectral response vary along the across-track dimension, thus giving rise to a shifting and smoothing of spectra (see Fig. 1 (left)). In fact, both effects are greater for spectra on the edges, while they are minimum for data acquired by central detectors, the so-called "sweet spot". The prior artifacts become particularly critical for Martian observations which contain steep spectra such as CO2 ice-rich polar images. Fig. 1 (right) shows the horizontal brightness gradient which appears in every band corresponding to a steep portion of spectra. The correction of CRISM spectral smile is addressed using a two-step method which aims at modifying data sensibly in order to mimic the optimal CRISM response. First, all spectra, which are previously interpolated by cubic splines, are resampled to the "sweet spot" wavelengths in order to overcome the spectra shift. Secondly, the non-uniform spectral width is overcome by mimicking an increase of spectral resolution thanks to a spectral sharpening. In order to minimize noise, only bands particularly suffering from smile are selected. First, bands corresponding to the outliers of the Minimum Noise Transformation (MNF) eigenvector, which corresponds to the MNF band related to smile (MNF-smile), are selected. Then, a spectral neighborhood Θi, which takes into account the local spectral convexity or concavity, is defined for every selected band in order to maximize spectral shape preservation. The proposed sharpening technique takes into account both the instrument parameters and the observed spectra. First, every reflectance value belonging to a Θi is reevaluated by a sharpening which depends on a ratio of the spectral width of the current detector and the "sweet spot" one. Then, the optimal degree of

  18. DETERMINING SPECTRAL REFLECTANCE COEFFICIENTS FROM HYPERSPECTRAL IMAGES OBTAINED FROM LOW ALTITUDES

    Directory of Open Access Journals (Sweden)

    P. Walczykowski

    2016-06-01

    Full Text Available Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based, object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor

  19. Determining Spectral Reflectance Coefficients from Hyperspectral Images Obtained from Low Altitudes

    Science.gov (United States)

    Walczykowski, P.; Jenerowicz, A.; Orych, A.; Siok, K.

    2016-06-01

    Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based), object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor mounted on an

  20. Mapping Infected Area after a Flash-Flooding Storm Using Multi Criteria Analysis and Spectral Indices

    Science.gov (United States)

    Al-Akad, S.; Akensous, Y.; Hakdaoui, M.

    2017-11-01

    This research article is summarize the applications of remote sensing and GIS to study the urban floods risk in Al Mukalla. Satellite acquisition of a flood event on October 2015 in Al Mukalla (Yemen) by using flood risk mapping techniques illustrate the potential risk present in this city. Satellite images (The Landsat and DEM images data were atmospherically corrected, radiometric corrected, and geometric and topographic distortions rectified.) are used for flood risk mapping to afford a hazard (vulnerability) map. This map is provided by applying image-processing techniques and using geographic information system (GIS) environment also the application of NDVI, NDWI index, and a method to estimate the flood-hazard areas. Four factors were considered in order to estimate the spatial distribution of the hazardous areas: flow accumulation, slope, land use, geology and elevation. The multi-criteria analysis, allowing to deal with vulnerability to flooding, as well as mapping areas at the risk of flooding of the city Al Mukalla. The main object of this research is to provide a simple and rapid method to reduce and manage the risks caused by flood in Yemen by take as example the city of Al Mukalla.

  1. The high throughput virtual slit enables compact, inexpensive Raman spectral imagers

    Science.gov (United States)

    Gooding, Edward; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

    2018-02-01

    Raman spectral imaging is increasingly becoming the tool of choice for field-based applications such as threat, narcotics and hazmat detection; air, soil and water quality monitoring; and material ID. Conventional fiber-coupled point source Raman spectrometers effectively interrogate a small sample area and identify bulk samples via spectral library matching. However, these devices are very slow at mapping over macroscopic areas. In addition, the spatial averaging performed by instruments that collect binned spectra, particularly when used in combination with orbital raster scanning, tends to dilute the spectra of trace particles in a mixture. Our design, employing free space line illumination combined with area imaging, reveals both the spectral and spatial content of heterogeneous mixtures. This approach is well suited to applications such as detecting explosives and narcotics trace particle detection in fingerprints. The patented High Throughput Virtual Slit1 is an innovative optical design that enables compact, inexpensive handheld Raman spectral imagers. HTVS-based instruments achieve significantly higher spectral resolution than can be obtained with conventional designs of the same size. Alternatively, they can be used to build instruments with comparable resolution to large spectrometers, but substantially smaller size, weight and unit cost, all while maintaining high sensitivity. When used in combination with laser line imaging, this design eliminates sample photobleaching and unwanted photochemistry while greatly enhancing mapping speed, all with high selectivity and sensitivity. We will present spectral image data and discuss applications that are made possible by low cost HTVS-enabled instruments.

  2. Multi-object segmentation framework using deformable models for medical imaging analysis.

    Science.gov (United States)

    Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

    2016-08-01

    Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

  3. Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA. Part 1: Introduction

    Directory of Open Access Journals (Sweden)

    Andrea Baraldi

    2012-09-01

    Full Text Available According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA systems and three-stage iterative geographic object-oriented image analysis (GEOOIA systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accuracy, efficiency, robustness, scalability and timeliness of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO guidelines, this methodological work is split into two parts. The present first paper provides a multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT analysis of the GEOBIA/GEOOIA approaches that augments similar analyses proposed in recent years. In line with constraints stemming from human vision, this SWOT analysis promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS image understanding system (RS-IUS, from sub-symbolic statistical model-based (inductive image segmentation to symbolic physical model-based (deductive image preliminary classification. Hence, a symbolic deductive pre-attentive vision first stage accomplishes image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the second part of this work a novel hybrid (combined deductive and inductive RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a computational theory (system design; (b information/knowledge representation; (c algorithm design; and (d implementation. As proof-of-concept of symbolic physical model-based pre-attentive vision first stage, the spectral knowledge-based, operational, near real-time Satellite Image Automatic Mapper™ (SIAM™ is selected from existing literature. To the best of these authors’ knowledge, this is the first time a

  4. Application of principal component analysis to multispectral imaging data for evaluation of pigmented skin lesions

    Science.gov (United States)

    Jakovels, Dainis; Lihacova, Ilze; Kuzmina, Ilona; Spigulis, Janis

    2013-11-01

    Non-invasive and fast primary diagnostics of pigmented skin lesions is required due to frequent incidence of skin cancer - melanoma. Diagnostic potential of principal component analysis (PCA) for distant skin melanoma recognition is discussed. Processing of the measured clinical multi-spectral images (31 melanomas and 94 nonmalignant pigmented lesions) in the wavelength range of 450-950 nm by means of PCA resulted in 87 % sensitivity and 78 % specificity for separation between malignant melanomas and pigmented nevi.

  5. [An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

    Science.gov (United States)

    Xu, Yonghong; Gao, Shangce; Hao, Xiaofei

    2016-04-01

    Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

  6. Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

    Directory of Open Access Journals (Sweden)

    Ming-Der Yang

    2017-06-01

    Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

  7. Global spectral graph wavelet signature for surface analysis of carpal bones

    Science.gov (United States)

    Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

    2018-02-01

    Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

  8. Clinical significance of power spectral analysis of heart rate variability and {sup 123}I-metaiodobenzylguanidine (MIBG) myocardial imaging for assessing the severity of heart failure

    Energy Technology Data Exchange (ETDEWEB)

    Ishida, Yoshio; Fukuoka, Shuji; Shimotsu, Yoriko; Sasaki, Tatsuya; Kamakura, Shiro; Yasumura, Yoshio; Miyatake, Kunio; Shimomura, Katsuro [National Cardiovascular Center, Suita, Osaka (Japan); Tani, Akihiro

    1997-04-01

    The significance of power spectral analysis of heart rate variability and of MIBG myocardial imaging to see the sympathetic nervous function was evaluated in patients with congestive heart failure due to dilated cardiomyopathy. Subjects were 10 normal volunteers and 8 patients with severity NYHA II; 10 normals and 25 patients with NYHA II and III; and 17 patients treated with a beta-blocker (metoprolol 5-40 mg). ECG was recorded with a portable ECG recorder for measuring RR intervals for 24 hr, which were applied for power spectral analysis. Early and delayed imagings with 111 MBq of {sup 123}I-MIBG were performed at 15 min and 4 hr, respectively, after its intravenous administration for acquisition of anterior planar and SPECT images. Myocardial blood flow SPECT was also done with 111 MBq of {sup 201}Tl given intravenously, and difference of total defect scores between MIBG and Tl images was computed. MIBG myocardial sympathetic nerve imaging in those patients was found useful to assess the severity of heart failure, to predict the risk patients for beta-blocker treatment and to assess the risk in complicated ventricular tachycardia. (K.H.)

  9. Spectral tuning via multi-phonon-assisted stokes and anti-stokes excitations in LaF{sub 3}: Tm{sup 3+} nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Dangli, E-mail: gaodangli@163.com [School of Materials & Mineral Resources, Xi' an University of Architecture and Technology, Xi' an, Shaanxi 710055 (China); College of Science, Xi' an University of Architecture and Technology, Xi' an, Shaanxi 710055 (China); Shaanxi Key Laboratory of Nano Materials and Technology, Xi' an, Shaanxi 710055 (China); Tian, Dongping, E-mail: dptian@xauat.edu.cn [School of Materials & Mineral Resources, Xi' an University of Architecture and Technology, Xi' an, Shaanxi 710055 (China); College of Science, Xi' an University of Architecture and Technology, Xi' an, Shaanxi 710055 (China); Chong, Bo; Li, Long [College of Science, Xi' an University of Architecture and Technology, Xi' an, Shaanxi 710055 (China); Zhang, Xiangyu [College of Science, Chang' an University, Xi' an, Shaanxi 710064 (China)

    2016-09-05

    We present a facile and highly effective method to tailor upconversion (UC) emission from LaF{sub 3}: Tm{sup 3+} nanoparticles (NPs) by adjusting ambient temperature from 20 K to 400 K accompanied with the pulse laser excitation. Spectral tuning mechanism controlled by ambient temperature at pulse laser excitation is revealed, and a mechanism based on the modification on multi-phonon relaxation rates for the rapid population of intermediate level {sup 3}H{sub 4} and multi-phonon-assisted excited state absorption is proposed. Based on multi-phonon relaxation theory and time-resolved photoluminescence studies, it is reasonable that UC luminescence under short-pulse laser excitation mainly originates from the ions at/near the surface of NPs. These exciting findings in ambient temperature accompanied with the short-pulse excitation dependent UC selectivity offer a general approach to tailoring lanthanide related UC emissions, which will benefit multicolor displays and imaging. - Graphical abstract: An effective method to tailor upconversion from LaF{sub 3}: Tm{sup 3+} nanoparticles by adjusting ambient temperature accompanied with the short-pulse laser excitation is presented and the spectral tuning mechanism based the modification on multi-phonon relaxation rate and multi-phonon-assisted excited state absorption is also revealed. - Highlights: • The luminescence switching is controlled by temperature and pulse duration. • The mechanism based on the multi-phonon-assisted excitations is proposed. • Blue luminescence under short-pulse excitation originates from the surface ions. • Temperature has a big effect on luminescence color output.

  10. A variational multi-scale method with spectral approximation of the sub-scales: Application to the 1D advection-diffusion equations

    KAUST Repository

    Chacó n Rebollo, Tomá s; Dia, Ben Mansour

    2015-01-01

    This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.

  11. A variational multi-scale method with spectral approximation of the sub-scales: Application to the 1D advection-diffusion equations

    KAUST Repository

    Chacón Rebollo, Tomás

    2015-03-01

    This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.

  12. Hyper-Spectral Imager in visible and near-infrared band for lunar ...

    Indian Academy of Sciences (India)

    India's first lunar mission, Chandrayaan-1, will have a Hyper-Spectral Imager in the visible and near-infrared spectral ... mapping of the Moon's crust in a large number of spectral channels. The planned .... In-flight verification may be done.

  13. Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

    Science.gov (United States)

    Earl, Nicholas; Peeples, Molly; JDADF Developers

    2018-01-01

    A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user

  14. Superpixel segmentation and pigment identification of colored relics based on visible spectral image

    Science.gov (United States)

    Li, Junfeng; Wan, Xiaoxia

    2018-01-01

    To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution.

  15. OBJECT-SPACE MULTI-IMAGE MATCHING OF MOBILE-MAPPING-SYSTEM IMAGE SEQUENCES

    Directory of Open Access Journals (Sweden)

    Y. C. Chen

    2012-07-01

    Full Text Available This paper proposes an object-space multi-image matching procedure of terrestrial MMS (Mobile Mapping System image sequences to determine the coordinates of an object point automatically and reliably. This image matching procedure can be applied to find conjugate points of MMS image sequences efficiently. Conventional area-based image matching methods are not reliable to deliver accurate matching results for this application due to image scale variations, viewing angle variations, and object occlusions. In order to deal with these three matching problems, an object space multi-image matching is proposed. A modified NCC (Normalized Cross Correlation coefficient is proposed to measure the similarity of image patches. A modified multi-window matching procedure will also be introduced to solve the problem of object occlusion. A coarse-to-fine procedure with a combination of object-space multi-image matching and multi-window matching is adopted. The proposed procedure has been implemented for the purpose of matching terrestrial MMS image sequences. The ratio of correct matches of this experiment was about 80 %. By providing an approximate conjugate point in an overlapping image manually, most of the incorrect matches could be fixed properly and the ratio of correct matches was improved up to 98 %.

  16. Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

    Science.gov (United States)

    Lee-Felker, Stephanie A; Tekchandani, Leena; Thomas, Mariam; Gupta, Esha; Andrews-Tang, Denise; Roth, Antoinette; Sayre, James; Rahbar, Guita

    2017-11-01

    Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed

  17. The Fresnel Zone Light Field Spectral Imager

    Science.gov (United States)

    2017-03-23

    detection efficiency for weak signals . Additionally, further study should be done on spectral calibration methods for a FZLFSI. When dealing with weak ... detection assembly. The different image formation planes for each wavelength are constructed synthetically through processing the collected light ...a single micro-lens image. This character- istic also holds for wavelengths other than the design wavelength. 36 modified light field PSF is detected

  18. MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION

    Directory of Open Access Journals (Sweden)

    X. Liu

    2012-08-01

    Full Text Available Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP and Local Weighted Amplitude (LWA, are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the

  19. Multi-spectral optical absorption in substrate-free nanowire arrays

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Junpeng; Chia, Andrew; Boulanger, Jonathan; LaPierre, Ray, E-mail: lapierr@mcmaster.ca [Department of Engineering Physics, McMaster University, 1280 Main St. West, Hamilton, Ontario L8S 4L7 (Canada); Dhindsa, Navneet; Khodadad, Iman; Saini, Simarjeet [Department of Electrical and Computer Engineering, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada); Waterloo Institute of Nanotechnology, University of Waterloo, 200 University Ave West, Waterloo, Ontario N2L 3G1 (Canada)

    2014-09-22

    A method is presented of fabricating gallium arsenide (GaAs) nanowire arrays of controlled diameter and period by reactive ion etching of a GaAs substrate containing an indium gallium arsenide (InGaP) etch stop layer, allowing the precise nanowire length to be controlled. The substrate is subsequently removed by selective etching, using the same InGaP etch stop layer, to create a substrate-free GaAs nanowire array. The optical absorptance of the nanowire array was then directly measured without absorption from a substrate. We directly observe absorptance spectra that can be tuned by the nanowire diameter, as explained with rigorous coupled wave analysis. These results illustrate strong optical absorption suitable for nanowire-based solar cells and multi-spectral absorption for wavelength discriminating photodetectors. The solar-weighted absorptance above the bandgap of GaAs was 94% for a nanowire surface coverage of only 15%.

  20. Spectral Properties of Homogeneous and Nonhomogeneous Radar Images

    DEFF Research Database (Denmark)

    Madsen, Søren Nørvang

    1987-01-01

    On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown that the sp......On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown...... that the spectrum of the intensityimage is in general related to the radar scene spectrum by a linearintegral equation, a Fredholm's integral equation of the third kind.Under simplifying assumptions, a closed-form equation giving theradar scene spectrum as a function of the SAR image spectrum canbe derived....

  1. Interpretation of archaeological small-scale features in spectral images

    DEFF Research Database (Denmark)

    Grøn, Ole; Palmer, Susanna; Stylegar, Frans-Arne

    2011-01-01

    The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern-recognition are......The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern...

  2. Multispectral analysis tools can increase utility of RGB color images in histology

    Science.gov (United States)

    Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

    2018-04-01

    Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

  3. Remote spectral measurements of the blood volume pulse with applications for imaging photoplethysmography

    Science.gov (United States)

    Blackford, Ethan B.; Estepp, Justin R.; McDuff, Daniel J.

    2018-02-01

    Imaging photoplethysmography uses camera image sensors to measure variations in light absorption related to the delivery of the blood volume pulse to peripheral tissues. The characteristics of the measured BVP waveform depends on the spectral absorption of various tissue components including melanin, hemoglobin, water, and yellow pigments. Signal quality and artifact rejection can be enhanced by taking into account the spectral properties of the BVP waveform and surrounding tissue. The current literature regarding the spectral relationships of remote PPG is limited. To supplement this fundamental data, we present an analysis of remotely-measured, visible and near-infrared spectroscopy to better understand the spectral signature of remotely measured BVP signals. To do so, spectra were measured from the right cheek of 25, stationary participants whose heads were stabilized by a chinrest. A collimating lens was used to collect reflected light from a region of 3 cm in diameter. The spectrometer provided 3 nm resolution measurements from 500-1000 nm. Measurements were acquired at a rate of 50 complete spectra per second for a period of five minutes. Reference physiology, including electrocardiography was simultaneously and synchronously acquired. The spectral data were analyzed to determine the relationship between light wavelength and the resulting remote-BVP signal-to-noise ratio and to identify those bands best suited for pulse rate measurement. To our knowledge this is the most comprehensive dataset of remotely-measured spectral iPPG data. In due course, we plan to release this dataset for research purposes.

  4. Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection -A First Study

    Science.gov (United States)

    Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Orthaus, Sandra; Achilefu, Samuel; Nussinov, Zohar

    2014-01-01

    Inspired by a multi-resolution community detection (MCD) based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Further, using the proposed method, the mean-square error (MSE) in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The MCD method appeared to perform better than a popular spectral clustering based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in MSE with increasing resolution. PMID:24251410

  5. Examination of Spectral Transformations on Spectral Mixture Analysis

    Science.gov (United States)

    Deng, Y.; Wu, C.

    2018-04-01

    While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

  6. Multi-angle compound imaging

    DEFF Research Database (Denmark)

    Jespersen, Søren Kragh; Wilhjelm, Jens Erik; Sillesen, Henrik

    1998-01-01

    This paper reports on a scanning technique, denoted multi-angle compound imaging (MACI), using spatial compounding. The MACI method also contains elements of frequency compounding, as the transmit frequency is lowered for the highest beam angles in order to reduce grating lobes. Compared to conve......This paper reports on a scanning technique, denoted multi-angle compound imaging (MACI), using spatial compounding. The MACI method also contains elements of frequency compounding, as the transmit frequency is lowered for the highest beam angles in order to reduce grating lobes. Compared...... to conventional B-mode imaging MACI offers better defined tissue boundaries and lower variance of the speckle pattern, resulting in an image with reduced random variations. Design and implementation of a compound imaging system is described, images of rubber tubes and porcine aorta are shown and effects...... on visualization are discussed. The speckle reduction is analyzed numerically and the results are found to be in excellent agreement with existing theory. An investigation of detectability of low-contrast lesions shows significant improvements compared to conventional imaging. Finally, possibilities for improving...

  7. NDVI and Panchromatic Image Correlation Using Texture Analysis

    Science.gov (United States)

    2010-03-01

    6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

  8. An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images

    Science.gov (United States)

    Bhardwaj, Kaushal; Patra, Swarnajyoti

    2018-04-01

    Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.

  9. A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture

    Directory of Open Access Journals (Sweden)

    Dimitris Stratoulias

    2017-10-01

    Full Text Available Earth Observation has become a progressively important source of information for land use and land cover services over the past decades. At the same time, an increasing number of reconnaissance satellites have been set in orbit with ever increasing spatial, temporal, spectral, and radiometric resolutions. The available bulk of data, fostered by open access policies adopted by several agencies, is setting a new landscape in remote sensing in which timeliness and efficiency are important aspects of data processing. This study presents a fully automated workflow able to process a large collection of very high spatial resolution satellite images to produce actionable information in the application framework of smallholder farming. The workflow applies sequential image processing, extracts meaningful statistical information from agricultural parcels, and stores them in a crop spectrotemporal signature library. An important objective is to follow crop development through the season by analyzing multi-temporal and multi-sensor images. The workflow is based on free and open-source software, namely R, Python, Linux shell scripts, the Geospatial Data Abstraction Library, custom FORTRAN, C++, and the GNU Make utilities. We tested and applied this workflow on a multi-sensor image archive of over 270 VHSR WorldView-2, -3, QuickBird, GeoEye, and RapidEye images acquired over five different study areas where smallholder agriculture prevails.

  10. Development of multi-dimensional body image scale for malaysian female adolescents.

    Science.gov (United States)

    Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

    2008-01-01

    The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

  11. A High-resolution Multi-wavelength Simultaneous Imaging System with Solar Adaptive Optics

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Changhui; Zhu, Lei; Gu, Naiting; Rao, Xuejun; Zhang, Lanqiang; Bao, Hua; Kong, Lin; Guo, Youming; Zhong, Libo; Ma, Xue’an; Li, Mei; Wang, Cheng; Zhang, Xiaojun; Fan, Xinlong; Chen, Donghong; Feng, Zhongyi; Wang, Xiaoyun; Wang, Zhiyong, E-mail: gunaiting@ioe.ac.cn [The Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, P.O. Box 350, Shuangliu, Chengdu 610209, Sichuan (China)

    2017-10-01

    A high-resolution multi-wavelength simultaneous imaging system from visible to near-infrared bands with a solar adaptive optics system, in which seven imaging channels, including the G band (430.5 nm), the Na i line (589 nm), the H α line (656.3 nm), the TiO band (705.7 nm), the Ca ii IR line (854.2 nm), the He i line (1083 nm), and the Fe i line (1565.3 nm), are chosen, is developed to image the solar atmosphere from the photosphere layer to the chromosphere layer. To our knowledge, this is the solar high-resolution imaging system with the widest spectral coverage. This system was demonstrated at the 1 m New Vaccum Solar Telescope and the on-sky high-resolution observational results were acquired. In this paper, we will illustrate the design and performance of the imaging system. The calibration and the data reduction of the system are also presented.

  12. Chemical imaging and solid state analysis at compact surfaces using UV imaging

    DEFF Research Database (Denmark)

    Wu, Jian X.; Rehder, Sönke; van den Berg, Frans

    2014-01-01

    and excipients in a non-invasive way, as well as mapping the glibenclamide solid state form. An exploratory data analysis supported the critical evaluation of the mapping results and the selection of model parameters for the chemical mapping. The present study demonstrated that the multi-wavelength UV imaging......Fast non-destructive multi-wavelength UV imaging together with multivariate image analysis was utilized to visualize distribution of chemical components and their solid state form at compact surfaces. Amorphous and crystalline solid forms of the antidiabetic compound glibenclamide...

  13. Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

    International Nuclear Information System (INIS)

    Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

    2011-01-01

    We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

  14. [A preliminary research on multi-source medical image fusion].

    Science.gov (United States)

    Kang, Yuanyuan; Li, Bin; Tian, Lianfang; Mao, Zongyuan

    2009-04-01

    Multi-modal medical image fusion has important value in clinical diagnosis and treatment. In this paper, the multi-resolution analysis of Daubechies 9/7 Biorthogonal Wavelet Transform is introduced for anatomical and functional image fusion, then a new fusion algorithm with the combination of local standard deviation and energy as texture measurement is presented. At last, a set of quantitative evaluation criteria is given. Experiments show that both anatomical and metabolism information can be obtained effectively, and both the edge and texture features can be reserved successfully. The presented algorithm is more effective than the traditional algorithms.

  15. Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager

    Science.gov (United States)

    Nagayama, T.; Mancini, R. C.; Mayes, D.; Tommasini, R.; Florido, R.

    2015-11-01

    Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ˜6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ˜10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.

  16. Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager

    International Nuclear Information System (INIS)

    Nagayama, T.; Mancini, R. C.; Mayes, D.; Tommasini, R.; Florido, R.

    2015-01-01

    Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application

  17. Understanding reliability and some limitations of the images and spectra reconstructed from a multi-monochromatic x-ray imager.

    Science.gov (United States)

    Nagayama, T; Mancini, R C; Mayes, D; Tommasini, R; Florido, R

    2015-11-01

    Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.

  18. Women's preferences of dynamic spectral imaging colposcopy

    NARCIS (Netherlands)

    Louwers, J.A.; Zaal, Afra; Kocken, M.; Papagiannakis, E.; Meijer, C.J.; Verheijen, RHM

    2015-01-01

    Background: The focus of testing the dynamic spectral imaging (DSI) colposcope has been on the technical characteristics and clinical performance. However, aspects from a patient’s perspective are just as important. Methods: This study was designed as a substudy of the DSI validation study, a

  19. Objective image characterization of a spectral CT scanner with dual-layer detector

    Science.gov (United States)

    Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

    2018-01-01

    This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

  20. Methods for Enhancing Geological Structures in Spectral Spatial Difference-Based on Remote-Sensing Image

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    @@In this paper, some image processing methods such as directional template (mask) matching enhancement, pseudocolor or false color enhancement, K-L transform enhancement are used to enhance a geological structure, one of important ore-controlling factors, shown in the remote-sensing images.This geological structure is regarded as image anomaly in the remote-sensing image, since considerable differences, based on the spatial spectral distribution pattern, in gray values (spectral), color tones and texture, are always present between the geological structure and background. Therefore,the enhancement of the geological structure in the remotesensing image is that of the spectral spatial difference.

  1. CHANGE DETECTION OF CROPPING PATTERN IN PADDY FIELD USING MULTI SPECTRAL SATELLITE DATA FOR ESTIMATING IRRIGATION WATER NEEDS

    Directory of Open Access Journals (Sweden)

    Rizatus Shofiyati1

    2012-10-01

    Full Text Available This paper investigates the use of multi spectral satellite data for cropping pattern monitoring in paddy field. The southern coastal of Citarum watershed, West Java Province was selected as study sites. The analysis used in this study is identifying crop pattern based on growth stages of wetland paddy and other crops by investi-gating the characteristic of Normalized Differen-ce Vegetation Indices (NDVI and Wetness of Tasseled Cap Transformation (TCT derived from 14 scenes of Landsat TM date 1988 to 2001. In general, the phenological of growth stages of wetland paddy can be used to distinguish with other seasonal crops. The research results indicate that multi spectral satellite data has a great potential for identi-fication and monitoring cropping pattern in paddy field. Specific character of NDVI and Wetness can also produce a map of cropping pattern in paddy field that is useful to monitor agricultural land condition. The cropping pattern can also be used to estimate irrigation water needed of paddy field in the area. Expected implication of the information obtained from this analysis is useful for guiding more appropriate planning and better agricultural management.

  2. Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    International Nuclear Information System (INIS)

    Mohamed, S S; Salama, M M A; Kamel, M; El-Saadany, E F; Rizkalla, K; Chin, J

    2005-01-01

    This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided into regions of interest (ROIs) by the Gabor multi-resolution analysis, a crucial stage, in which segmentation is achieved according to the frequency response of the image pixels. The pixels with a similar response to the same filter are grouped to form one ROI. Next, from each ROI two different statistical feature sets are constructed; the first set includes four grey level dependence matrix (GLDM) features and the second set consists of five grey level difference vector (GLDV) features. These constructed feature sets are then ranked by the mutual information feature selection (MIFS) algorithm. Here, the features that provide the maximum mutual information of each feature and class (cancerous and non-cancerous) and the minimum mutual information of the selected features are chosen, yeilding a reduced feature subset. The two constructed feature sets, GLDM and GLDV, as well as the reduced feature subset, are examined in terms of three different classifiers: the condensed k-nearest neighbour (CNN), the decision tree (DT) and the support vector machine (SVM). The accuracy classification results range from 87.5% to 93.75%, where the performance of the SVM and that of the DT are significantly better than the performance of the CNN. (note)

  3. Portable laser synthesizer for high-speed multi-dimensional spectroscopy

    Science.gov (United States)

    Demos, Stavros G [Livermore, CA; Shverdin, Miroslav Y [Sunnyvale, CA; Shirk, Michael D [Brentwood, CA

    2012-05-29

    Portable, field-deployable laser synthesizer devices designed for multi-dimensional spectrometry and time-resolved and/or hyperspectral imaging include a coherent light source which simultaneously produces a very broad, energetic, discrete spectrum spanning through or within the ultraviolet, visible, and near infrared wavelengths. The light output is spectrally resolved and each wavelength is delayed with respect to each other. A probe enables light delivery to a target. For multidimensional spectroscopy applications, the probe can collect the resulting emission and deliver this radiation to a time gated spectrometer for temporal and spectral analysis.

  4. Continuous non-invasive blood glucose monitoring by spectral image differencing method

    Science.gov (United States)

    Huang, Hao; Liao, Ningfang; Cheng, Haobo; Liang, Jing

    2018-01-01

    Currently, the use of implantable enzyme electrode sensor is the main method for continuous blood glucose monitoring. But the effect of electrochemical reactions and the significant drift caused by bioelectricity in body will reduce the accuracy of the glucose measurements. So the enzyme-based glucose sensors need to be calibrated several times each day by the finger-prick blood corrections. This increases the patient's pain. In this paper, we proposed a method for continuous Non-invasive blood glucose monitoring by spectral image differencing method in the near infrared band. The method uses a high-precision CCD detector to switch the filter in a very short period of time, obtains the spectral images. And then by using the morphological method to obtain the spectral image differences, the dynamic change of blood sugar is reflected in the image difference data. Through the experiment proved that this method can be used to monitor blood glucose dynamically to a certain extent.

  5. Multi-spectral lifetime imaging: methods and applications

    NARCIS (Netherlands)

    Fereidouni, F.

    2013-01-01

    The aim of this PhD project is to further develop multispectral life time imaging hardware and analyses methods. The hardware system, Lambda-Tau, generates a considerable amount of data at high speed. To fully exploit the power of this new hardware, fast and reliable data analyses methods are

  6. Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Blaschke, Thomas; Tiede, Dirk; Moghaddam, Mohammad Hossein Rezaei

    2017-09-01

    This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

  7. SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

    Energy Technology Data Exchange (ETDEWEB)

    Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Wang, Qinfen [Shandong Normal University, Jinan, Shandong (China); Li, H; Chen, J [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)

    2014-06-01

    Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity

  8. Color camera computed tomography imaging spectrometer for improved spatial-spectral image accuracy

    Science.gov (United States)

    Wilson, Daniel W. (Inventor); Bearman, Gregory H. (Inventor); Johnson, William R. (Inventor)

    2011-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.

  9. Eyjafjallajokull Volcano Plume Particle-Type Characterization from Space-Based Multi-angle Imaging

    Science.gov (United States)

    Kahn, Ralph A.; Limbacher, James

    2012-01-01

    The Multi-angle Imaging SpectroRadiometer (MISR) Research Aerosol algorithm makes it possible to study individual aerosol plumes in considerable detail. From the MISR data for two optically thick, near-source plumes from the spring 2010 eruption of the Eyjafjallaj kull volcano, we map aerosol optical depth (AOD) gradients and changing aerosol particle types with this algorithm; several days downwind, we identify the occurrence of volcanic ash particles and retrieve AOD, demonstrating the extent and the limits of ash detection and mapping capability with the multi-angle, multi-spectral imaging data. Retrieved volcanic plume AOD and particle microphysical properties are distinct from background values near-source, as well as for overwater cases several days downwind. The results also provide some indication that as they evolve, plume particles brighten, and average particle size decreases. Such detailed mapping offers context for suborbital plume observations having much more limited sampling. The MISR Standard aerosol product identified similar trends in plume properties as the Research algorithm, though with much smaller differences compared to background, and it does not resolve plume structure. Better optical analogs of non-spherical volcanic ash, and coincident suborbital data to validate the satellite retrieval results, are the factors most important for further advancing the remote sensing of volcanic ash plumes from space.

  10. Fluorescence hyper-spectral imaging to detecting faecal contamination on fresh tomatoes

    Directory of Open Access Journals (Sweden)

    Roberto Romaniello

    2016-03-01

    Full Text Available Faecal contamination of fresh fruits represents a severe danger for human health. Thus some techniques based on microbiological testing were developed to individuate faecal contaminants but those tests do not results efficient because their non-applicability on overall vegetable unity. In this work a methodology based on hyper-spectral fluorescence imaging was developed and tested to detecting faecal contamination on fresh tomatoes. Two image-processing methods were performed to maximise the contrast between the faecal contaminant and tomatoes skin: principal component analysis and band image ratio (BRI. The BRI method allows classifying correctly 70% of contaminated area, with no false-positives in all examined cases. Thus, the developed methodology can be employed for a fast and effective detection of faecal contamination on fresh tomatoes.

  11. From Pixels to Geographic Objects in Remote Sensing Image Analysis

    NARCIS (Netherlands)

    Addink, E.A.; Van Coillie, Frieke M.B.; Jong, Steven M. de

    Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received

  12. Fluorescence spectral studies of Gum Arabic: Multi-emission of Gum Arabic in aqueous solution

    Energy Technology Data Exchange (ETDEWEB)

    Dhenadhayalan, Namasivayam, E-mail: ndhena@gmail.com [Department of Chemistry, National Taiwan University, Taipei, Taiwan (China); Mythily, Rajan, E-mail: rajanmythily@gmail.com [Department of Chemistry, Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), 833, Gokul Bagh, E.V.R. Periyar Road, Arumbakkam, Chennai 600 106 (India); Kumaran, Rajendran, E-mail: kumaranwau@rediffmail.com [Department of Chemistry, Dwaraka Doss Goverdhan Doss Vaishnav College (Autonomous), 833, Gokul Bagh, E.V.R. Periyar Road, Arumbakkam, Chennai 600 106 (India)

    2014-11-15

    Gum Arabic (GA), a food hydrocolloid is a natural composite obtained from the stems and branches of Acacia Senegal and Acacia Seyal trees. GA structure is made up of highly branched arabinogalactan polysaccharides. Steady-state absorption, fluorescence, and time-resolved fluorescence spectral studies of acid hydrolyzed GA solutions were carried out at various pH conditions. The fluorescence in GA is predominantly attributed to the presence of tyrosine and phenylalanine amino acids. The presence of multi-emissive peaks at different pH condition is attributed to the exposure of the fluorescing amino acids to the aqueous phase, which contains several sugar units, hydrophilic and hydrophobic moieties. Time-resolved fluorescence studies of GA exhibits a multi-exponential decay with different fluorescence lifetime of varying amplitude which confirms that tyrosine is confined to a heterogeneous microenvironment. The existence of multi-emissive peaks with large variation in the fluorescence intensities were established by 3D emission contour spectral studies. The probable location of the fluorophore in a heterogeneous environment was further ascertained by constructing a time-resolved emission spectrum (TRES) and time-resolved area normalized emission spectrum (TRANES) plots. Fluorescence spectral technique is used as an analytical tool in understanding the photophysical properties of a water soluble complex food hydrocolloid containing an intrinsic fluorophore located in a multiple environment is illustrated. - Highlights: • The Manuscript deals with the steady state absorption, emission, fluorescence lifetime and time-resolved emission spectrum studies of Gum Arabic in aqueous medium at various pH conditions. • The fluorescence emanates from the tyrosine amino acid present in GA. • Change in pH results in marked variation in the fluorescence spectral properties of tyrosine. • Fluorescence spectral techniques are employed as a tool in establishing the

  13. Effects of spectral variation on the device performance of copper indium diselenide and multi-crystalline silicon photovoltaic modules

    Energy Technology Data Exchange (ETDEWEB)

    Okullo, W.; Munji, M.K.; Vorster, F.J.; van Dyk, E.E. [Department of Physics, Nelson Mandela Metropolitan University, Box 77000, Port Elizabeth (South Africa)

    2011-02-15

    We present results of an experimental investigation of the effects of the daily spectral variation on the device performance of copper indium diselenide and multi-crystalline silicon photovoltaic modules. Such investigations are of importance in characterization of photovoltaic devices. The investigation centres on the analysis of outdoor solar spectral measurements carried out at 10 min intervals on clear-sky days. We have shown that the shift in the solar spectrum towards infrared has a negative impact on the device performance of both modules. The spectral bands in the visible region contribute more to the short circuit current than the bands in the infrared region while the ultraviolet region contributes least. The quantitative effects of the spectral variation on the performance of the two photovoltaic modules are reflected on their respective device performance parameters. The decrease in the visible and the increase in infrared of the late afternoon spectra in each case account for the decreased current collection and hence power and efficiency of both modules. (author)

  14. A Concept of Multi-Mode High Spectral Resolution Lidar Using Mach-Zehnder Interferometer

    Directory of Open Access Journals (Sweden)

    Jin Yoshitaka

    2016-01-01

    Full Text Available In this paper, we present the design of a High Spectral Resolution Lidar (HSRL using a laser that oscillates in a multi-longitudinal mode. Rayleigh and Mie scattering components are separated using a Mach-Zehnder Interferometer (MZI with the same free spectral range (FSR as the transmitted laser. The transmitted laser light is measured as a reference signal with the same MZI. By scanning the MZI periodically with a scanning range equal to the mode spacing, we can identify the maximum Mie and the maximum Rayleigh signals using the reference signal. The cross talk due to the spectral width of each laser mode can also be estimated.

  15. Multichannel imager for littoral zone characterization

    Science.gov (United States)

    Podobna, Yuliya; Schoonmaker, Jon; Dirbas, Joe; Sofianos, James; Boucher, Cynthia; Gilbert, Gary

    2010-04-01

    This paper describes an approach to utilize a multi-channel, multi-spectral electro-optic (EO) system for littoral zone characterization. Advanced Coherent Technologies, LLC (ACT) presents their EO sensor systems for the surf zone environmental assessment and potential surf zone target detection. Specifically, an approach is presented to determine a Surf Zone Index (SZI) from the multi-spectral EO sensor system. SZI provides a single quantitative value of the surf zone conditions delivering an immediate understanding of the area and an assessment as to how well an airborne optical system might perform in a mine countermeasures (MCM) operation. Utilizing consecutive frames of SZI images, ACT is able to measure variability over time. A surf zone nomograph, which incorporates targets, sensor, and environmental data, including the SZI to determine the environmental impact on system performance, is reviewed in this work. ACT's electro-optical multi-channel, multi-spectral imaging system and test results are presented and discussed.

  16. Effective approach to spectroscopy and spectral analysis techniques using Matlab

    Science.gov (United States)

    Li, Xiang; Lv, Yong

    2017-08-01

    With the development of electronic information, computer and network, modern education technology has entered new era, which would give a great impact on teaching process. Spectroscopy and spectral analysis is an elective course for Optoelectronic Information Science and engineering. The teaching objective of this course is to master the basic concepts and principles of spectroscopy, spectral analysis and testing of basic technical means. Then, let the students learn the principle and technology of the spectrum to study the structure and state of the material and the developing process of the technology. MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, Based on the teaching practice, this paper summarizes the new situation of applying Matlab to the teaching of spectroscopy. This would be suitable for most of the current school multimedia assisted teaching

  17. Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

    DEFF Research Database (Denmark)

    Kazantsev, Daniil; Jørgensen, Jakob Sauer; Andersen, Martin S

    2018-01-01

    peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually...... to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction...

  18. Selecting optimal monochromatic level with spectral CT imaging for improving imaging quality in hepatic venography

    International Nuclear Information System (INIS)

    Sun Jun; Luo Xianfu; Wang Shou'an; Wang Jun; Sun Jiquan; Wang Zhijun; Wu Jingtao

    2013-01-01

    Objective: To investigate the effect of spectral CT monochromatic images for improving imaging quality in hepatic venography. Methods: Thirty patients underwent spectral CT examination on a GE Discovery CT 750 HD scanner. During portal phase, 1.25 mm slice thickness polychromatic images and optimal monochromatic images were obtained, and volume rendering and maximum intensity projection were created to show the hepatic veins respectively. The overall imaging quality was evaluated on a five-point scale by two radiologists. Inter-observer agreement in subjective image quality grading was assessed by Kappa statistics. Paired-sample t test were used to compare hepatic vein attenuation, hepatic parenchyma attenuation, CT value difference between the hepatic vein and the liver parenchyma, image noise, vein-to-liver contrast-to-noise ratio (CNR), the image quality score of hepatic venography between the two image data sets. Results: The monochromatic images at 50 keV were found to demonstrate the best CNR for hepatic vein.The hepatic vein attenuation [(329 ± 47) HU], hepatic parenchyma attenuation [(178 ± 33) HU], CT value difference between the hepatic vein and the liver parenchyma [(151 ± 33) HU], image noise (17.33 ± 4.18), CNR (9.13 ± 2.65), the image quality score (4.2 ± 0.6) of optimal monochromatic images were significantly higher than those of polychromatic images [(149 ± 18) HU], [(107 ± 14) HU], [(43 ±11) HU], 12.55 ± 3.02, 3.53 ± 1.03, 3.1 ± 0.8 (t values were 24.79, 13.95, 18.85, 9.07, 13.25 and 12.04, respectively, P < 0.01). In the comparison of image quality, Kappa value was 0.81 with optimal monochromatic images and 0.69 with polychromatic images. Conclusion: Monochromatic images of spectral CT could improve CNR for displaying hepatic vein and improve the image quality compared to the conventional polychromatic images. (authors)

  19. Multi-modal image registration: matching MRI with histology

    Science.gov (United States)

    Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

    2010-03-01

    Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

  20. Multi-target molecular imaging and its progress in research and application

    International Nuclear Information System (INIS)

    Tang Ganghua

    2011-01-01

    Multi-target molecular imaging (MMI) is an important field of research in molecular imaging. It includes multi-tracer multi-target molecular imaging(MTMI), fusion-molecule multi-target imaging (FMMI), coupling-molecule multi-target imaging (CMMI), and multi-target multifunctional molecular imaging(MMMI). In this paper,imaging modes of MMI are reviewed, and potential applications of positron emission tomography MMI in near future are discussed. (author)

  1. THE RESEARCH OF SPECTRAL RECONSTRUCTION FOR LARGE APERTURE STATIC IMAGING SPECTROMETER

    Directory of Open Access Journals (Sweden)

    H. Lv

    2018-04-01

    Full Text Available Imaging spectrometer obtains or indirectly obtains the spectral information of the ground surface feature while obtaining the target image, which makes the imaging spectroscopy has a prominent advantage in fine characterization of terrain features, and is of great significance for the study of geoscience and other related disciplines. Since the interference data obtained by interferometric imaging spectrometer is intermediate data, which must be reconstructed to achieve the high quality spectral data and finally used by users. The difficulty to restrict the application of interferometric imaging spectroscopy is to reconstruct the spectrum accurately. Based on the original image acquired by Large Aperture Static Imaging Spectrometer as the input, this experiment selected the pixel that is identified as crop by artificial recognition, extract and preprocess the interferogram to recovery the corresponding spectrum of this pixel. The result shows that the restructured spectrum formed a small crest near the wavelength of 0.55 μm with obvious troughs on both sides. The relative reflection intensity of the restructured spectrum rises abruptly at the wavelength around 0.7 μm, forming a steep slope. All these characteristics are similar with the spectral reflection curve of healthy green plants. It can be concluded that the experimental result is consistent with the visual interpretation results, thus validating the effectiveness of the scheme for interferometric imaging spectrum reconstruction proposed in this paper.

  2. Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale

    Directory of Open Access Journals (Sweden)

    Anne Clasen

    2015-11-01

    Full Text Available Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA can contribute to overcoming this challenge. Reference fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA and simulated Environmental Mapping and Analysis Program (EnMAP and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%.

  3. Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

    Science.gov (United States)

    Driscoll, Brandon; Jaffray, David; Coolens, Catherine

    2014-03-01

    Purpose: To provide clinicians & researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

  4. Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

    International Nuclear Information System (INIS)

    Driscoll, Brandon; Jaffray, David; Coolens, Catherine

    2014-01-01

    Purpose: To provide clinicians and researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

  5. 3D high spectral and spatial resolution imaging of ex vivo mouse brain

    International Nuclear Information System (INIS)

    Foxley, Sean; Karczmar, Gregory S.; Domowicz, Miriam; Schwartz, Nancy

    2015-01-01

    Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T 2 * -weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T 2 * and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm 3 and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T 2 * -weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not

  6. MULTI-TEMPORAL ASSESSMENT OF LYCHEE TREE CROP STRUCTURE USING MULTI-SPECTRAL RPAS IMAGERY

    Directory of Open Access Journals (Sweden)

    K. Johansen

    2017-08-01

    Full Text Available The lychee tree is native to China and produce small fleshy fruit up to 5 cm in diameter. Lychee production in Australia is worth > $20 million annually. Pruning of trees encourages new growth, has a positive effect on fruiting of lychee, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. The objective of this research was to assess changes in tree structure, i.e. tree crown circumference, width, height and Plant Projective Cover (PPC using multi-spectral Remotely Piloted Aircraft System (RPAS imagery collected before and after pruning of a lychee plantation. A secondary objective was to assess any variations in the results as a function of various flying heights (30, 50 and 70 m. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in: tree crown circumference of 1.94 m; tree crown width of 0.57 m; tree crown height of 0.62 m; and PPC of 14.8 %. The different flying heights produced similar measurements of tree crown width and PPC, whereas tree crown circumference and height measurements decreased with increasing flying height. These results show that multi-spectral RPAS imagery can provide a suitable means of assessing pruning efforts undertaken by contractors based on changes in tree structure of lychee plantations and that it is important to collect imagery in a consistent manner, as varying flying heights may cause changes to tree structural measurements.

  7. Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

    Science.gov (United States)

    Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.

    2004-02-01

    We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

  8. Conjugate Etalon Spectral Imager (CESI) & Scanning Etalon Methane Mapper (SEMM), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The Conjugate Etalon Spectral Imaging (CESI) concept enables the development of miniature instruments with high spectral resolution, suitable for LEO missions aboard...

  9. Sub-pattern based multi-manifold discriminant analysis for face recognition

    Science.gov (United States)

    Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

    2018-04-01

    In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

  10. Dual-camera design for coded aperture snapshot spectral imaging.

    Science.gov (United States)

    Wang, Lizhi; Xiong, Zhiwei; Gao, Dahua; Shi, Guangming; Wu, Feng

    2015-02-01

    Coded aperture snapshot spectral imaging (CASSI) provides an efficient mechanism for recovering 3D spectral data from a single 2D measurement. However, since the reconstruction problem is severely underdetermined, the quality of recovered spectral data is usually limited. In this paper we propose a novel dual-camera design to improve the performance of CASSI while maintaining its snapshot advantage. Specifically, a beam splitter is placed in front of the objective lens of CASSI, which allows the same scene to be simultaneously captured by a grayscale camera. This uncoded grayscale measurement, in conjunction with the coded CASSI measurement, greatly eases the reconstruction problem and yields high-quality 3D spectral data. Both simulation and experimental results demonstrate the effectiveness of the proposed method.

  11. Evaluation of cardiac function using multi-shot echo planar imaging

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi, Tadashi; Tanitame, Nobuko; Hata, Ryoichiro; Hirai, Nobuhiko; Ikeda, Midori; Ono, Chiaki; Fukuoka, Haruhito; Ito, Katsuhide [Hiroshima Univ. (Japan). School of Medicine

    1998-01-01

    In this study, we performed multi-shot echo planar imaging (8 shot, TR/TE/FL=55 ms/18 ms/60 degrees) and k-space segmented fast gradient echo sequence (8 views per segment, TR/TE/FL=9.9 ms/1.8 ms/30 degrees) to assess cardiac function in healthy volunteers. Transaxial sections of the entire heart were obtained with both sequences in ECG triggered, breath hold, and with a 256 x 128 matrix. Resulting temporal resolution was 55 ms for echo planar imaging, and 71 ms for k-space segmented fast gradient echo sequence, respectively. Ventricular volume and ejection fraction of both ventricles and left ventricular mass obtained with multi-shot echo planar imaging were assessed in comparison with k-space segmented fast gradient echo sequence. Measurements of left ventricular volume, ejection fraction and mass obtained with multi-shot echo planar imaging demonstrated close correlation with those obtained with k-space segmented fast gradient echo sequence. Right ventricular volumes obtained with echo planar imaging were significantly higher than those obtained with k-space segmented fast gradient echo sequence. This tendency is considered to be due to differing contrast between right ventricular myocardium and fat tissue observed with echo planar imaging relative to that observed with fast gradient echo sequence, because fat suppression is always performed in echo planar images. Multi-shot echo planar imaging can be a reliable tool for measurement of cardiac functional parameters, although wall motion analysis of the left ventricle requires higher temporal resolution and a short axial section. (K.H.)

  12. Cellular organization and spectral diversity of GFP-like proteins in live coral cells studied by single and multiphoton imaging and microspectroscopy

    Science.gov (United States)

    Salih, Anya; Cox, Guy C.; Larkum, Anthony W.

    2003-07-01

    Tissues of many marine invertebrates of class Anthozoa contain intensely fluorescent or brightly coloured pigments. These pigments belong to a family of photoactive proteins closely related to Green Fluorescent Protein (GFP), and their emissions range from blue to red wavelengths. The great diversity of these pigments has only recently been realised. To investigate the role of these proteins in corals, we have performed an in vivo fluorescent pigment (FP) spectral and cellular distribution analyses in live coral cells using single and multi-photon laser scanning imaging and microspectroscopy. These analyses revealed that even single colour corals contain spectroscopically heterogeneous pigment mixtures, with 2-5 major colour types in the same area of tissue. They were typically arranged in step-wise light emission energy gradients (e.g. blue, green, yellow, red). The successive overlapping emission-excitation spectral profiles of differently coloured FPs suggested that they were suited for sequential energy coupling. Traces of red FPs (emission = 570-660 nm) were present, even in non-red corals. We confirmed that radiative energy transfer could occur between separate granules of blue and green FPs and that energy transfer was inversely proportional to the square of the distance between them. Multi-photon micro-spectrofluorometric analysis gave significantly improved spectral resolution by restricting FP excitation to a single point in the focal plane of the sample. Pigment heterogeneity at small scales within granules suggested that fluorescence resonance energy transfer (FRET) might be occurring, and we confirmed that this was the case. Thus, energy transfer can take place both radiatively and by FRET, probably functioning in photoprotection by dissipation of excessive solar radiation.

  13. A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

    Science.gov (United States)

    Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

    2017-11-01

    Parametric response map (PRM) analysis of functional imaging has been shown to be an effective tool for early prediction of cancer treatment outcomes and may also be well-suited toward guiding personalized adaptive radiotherapy (RT) strategies such as sub-volume boosting. However, the PRM method was primarily designed for analysis of longitudinally acquired pairs of single-parameter image data. The purpose of this study was to demonstrate the feasibility of a generalized parametric response map analysis framework, which enables analysis of multi-parametric data while maintaining the key advantages of the original PRM method. MRI-derived apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps acquired at 1 and 3-months post-RT for 19 patients with high-grade glioma were used to demonstrate the algorithm. Images were first co-registered and then standardized using normal tissue image intensity values. Tumor voxels were then plotted in a four-dimensional Cartesian space with coordinate values equal to a voxel's image intensity in each of the image volumes and an origin defined as the multi-parametric mean of normal tissue image intensity values. Voxel positions were orthogonally projected onto a line defined by the origin and a pre-determined response vector. The voxels are subsequently classified as positive, negative or nil, according to whether projected positions along the response vector exceeded a threshold distance from the origin. The response vector was selected by identifying the direction in which the standard deviation of tumor image intensity values was maximally different between responding and non-responding patients within a training dataset. Voxel classifications were visualized via familiar three-class response maps and then the fraction of tumor voxels associated with each of the classes was investigated for predictive utility analogous to the original PRM method. Independent PRM and MPRM analyses of the contrast

  14. Flame analysis using image processing techniques

    Science.gov (United States)

    Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

    2018-04-01

    This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

  15. a Spatio-Spectral Camera for High Resolution Hyperspectral Imaging

    Science.gov (United States)

    Livens, S.; Pauly, K.; Baeck, P.; Blommaert, J.; Nuyts, D.; Zender, J.; Delauré, B.

    2017-08-01

    Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS) is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600-900 nm) in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots), horticulture (crop status monitoring to evaluate irrigation management in strawberry fields) and geology (meteorite detection on a grassland field). Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475-925 nm), and we discuss future work.

  16. A SPATIO-SPECTRAL CAMERA FOR HIGH RESOLUTION HYPERSPECTRAL IMAGING

    Directory of Open Access Journals (Sweden)

    S. Livens

    2017-08-01

    Full Text Available Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600–900 nm in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots, horticulture (crop status monitoring to evaluate irrigation management in strawberry fields and geology (meteorite detection on a grassland field. Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475–925 nm, and we discuss future work.

  17. Integrating two spectral imaging systems in an automated mineralogy application

    CSIR Research Space (South Africa)

    Harris, D

    2009-11-01

    Full Text Available is treated in batches, with trays of mono-layered material presented to various imaging systems. The identification of target grains is achieved by means of spectral imaging in two wavelength bands (Visible, and Long Wave Infrared). Target grains...

  18. SPECTRAL ANALYSIS OF EXCHANGE RATES

    Directory of Open Access Journals (Sweden)

    ALEŠA LOTRIČ DOLINAR

    2013-06-01

    Full Text Available Using spectral analysis is very common in technical areas but rather unusual in economics and finance, where ARIMA and GARCH modeling are much more in use. To show that spectral analysis can be useful in determining hidden periodic components for high-frequency finance data as well, we use the example of foreign exchange rates

  19. HYPERSPECTRAL HYPERION IMAGERY ANALYSIS AND ITS APPLICATION USING SPECTRAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Pervez

    2015-03-01

    Full Text Available Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more useful for its further processing/ application. Principal component (PC analysis applied to the hyperspectral calibrated bands reduced the dimensionality of the data and it is found that 99% of the data is held in first 10 PCs. Feature extraction is one of the important application by using vegetation delineation and normalized difference vegetation index. The machine learning classifiers uses the technique to identify the pixels having significant difference in the spectral signature which is very useful for classification of an image. Supervised machine learning classifier technique has been used for classification of hyperspectral image which resulted in overall efficiency of 86.6703 and Kappa co-efficient of 0.7998.

  20. Analysis of Harmonic Injection to the Modulation of Multi-Level ...

    African Journals Online (AJOL)

    This paper explores the analysis of third and ninth harmonic injection to the modulation of a multilevel diode clamped converter (DCC) at a varying modulation index. The spectral distributions of the various multi-level waveforms obtained under normal modulation index of 0.8 and over modulation index of 1.15 were ...

  1. Parallel Implementation of the Multi-Dimensional Spectral Code SPECT3D on large 3D grids.

    Science.gov (United States)

    Golovkin, Igor E.; Macfarlane, Joseph J.; Woodruff, Pamela R.; Pereyra, Nicolas A.

    2006-10-01

    The multi-dimensional collisional-radiative, spectral analysis code SPECT3D can be used to study radiation from complex plasmas. SPECT3D can generate instantaneous and time-gated images and spectra, space-resolved and streaked spectra, which makes it a valuable tool for post-processing hydrodynamics calculations and direct comparison between simulations and experimental data. On large three dimensional grids, transporting radiation along lines of sight (LOS) requires substantial memory and CPU resources. Currently, the parallel option in SPECT3D is based on parallelization over photon frequencies and allows for a nearly linear speed-up for a variety of problems. In addition, we are introducing a new parallel mechanism that will greatly reduce memory requirements. In the new implementation, spatial domain decomposition will be utilized allowing transport along a LOS to be performed only on the mesh cells the LOS crosses. The ability to operate on a fraction of the grid is crucial for post-processing the results of large-scale three-dimensional hydrodynamics simulations. We will present a parallel implementation of the code and provide a scalability study performed on a Linux cluster.

  2. A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

    Science.gov (United States)

    Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

    2016-11-01

    The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

  3. 3D high spectral and spatial resolution imaging of ex vivo mouse brain

    Energy Technology Data Exchange (ETDEWEB)

    Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S. [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Domowicz, Miriam [Department of Pediatrics, University of Chicago, Chicago, Illinois 60637 (United States); Schwartz, Nancy [Department of Pediatrics, Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637 (United States)

    2015-03-15

    Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in

  4. Sparse spectral deconvolution algorithm for noncartesian MR spectroscopic imaging.

    Science.gov (United States)

    Bhave, Sampada; Eslami, Ramin; Jacob, Mathews

    2014-02-01

    To minimize line shape distortions and spectral leakage artifacts in MR spectroscopic imaging (MRSI). A spatially and spectrally regularized non-Cartesian MRSI algorithm that uses the line shape distortion priors, estimated from water reference data, to deconvolve the spectra is introduced. Sparse spectral regularization is used to minimize noise amplification associated with deconvolution. A spiral MRSI sequence that heavily oversamples the central k-space regions is used to acquire the MRSI data. The spatial regularization term uses the spatial supports of brain and extracranial fat regions to recover the metabolite spectra and nuisance signals at two different resolutions. Specifically, the nuisance signals are recovered at the maximum resolution to minimize spectral leakage, while the point spread functions of metabolites are controlled to obtain acceptable signal-to-noise ratio. The comparisons of the algorithm against Tikhonov regularized reconstructions demonstrates considerably reduced line-shape distortions and improved metabolite maps. The proposed sparsity constrained spectral deconvolution scheme is effective in minimizing the line-shape distortions. The dual resolution reconstruction scheme is capable of minimizing spectral leakage artifacts. Copyright © 2013 Wiley Periodicals, Inc.

  5. The image evaluation of iterative motion correction reconstruction algorithm PROPELLER T2-weighted imaging compared with MultiVane T2-weighted imaging

    Science.gov (United States)

    Lee, Suk-Jun; Yu, Seung-Man

    2017-08-01

    The purpose of this study was to evaluate the usefulness and clinical applications of MultiVaneXD which was applying iterative motion correction reconstruction algorithm T2-weighted images compared with MultiVane images taken with a 3T MRI. A total of 20 patients with suspected pathologies of the liver and pancreatic-biliary system based on clinical and laboratory findings underwent upper abdominal MRI, acquired using the MultiVane and MultiVaneXD techniques. Two reviewers analyzed the MultiVane and MultiVaneXD T2-weighted images qualitatively and quantitatively. Each reviewer evaluated vessel conspicuity by observing motion artifacts and the sharpness of the portal vein, hepatic vein, and upper organs. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated by one reviewer for quantitative analysis. The interclass correlation coefficient was evaluated to measure inter-observer reliability. There were significant differences between MultiVane and MultiVaneXD in motion artifact evaluation. Furthermore, MultiVane was given a better score than MultiVaneXD in abdominal organ sharpness and vessel conspicuity, but the difference was insignificant. The reliability coefficient values were over 0.8 in every evaluation. MultiVaneXD (2.12) showed a higher value than did MultiVane (1.98), but the difference was insignificant ( p = 0.135). MultiVaneXD is a motion correction method that is more advanced than MultiVane, and it produced an increased SNR, resulting in a greater ability to detect focal abdominal lesions.

  6. A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis.

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Li, Yung-Hui; Wang, Wei; Tien, Chung-Hao

    2018-03-06

    In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme.

  7. [Influence of human body target's spectral characteristics on visual range of low light level image intensifiers].

    Science.gov (United States)

    Zhang, Jun-Ju; Yang, Wen-Bin; Xu, Hui; Liu, Lei; Tao, Yuan-Yaun

    2013-11-01

    To study the effect of different human target's spectral reflective characteristic on low light level (LLL) image intensifier's distance, based on the spectral characteristics of the night-sky radiation and the spectral reflective coefficients of common clothes, we established a equation of human body target's spectral reflective distribution, and analyzed the spectral reflective characteristics of different human targets wearing the clothes of different color and different material, and from the actual detection equation of LLL image intensifier distance, discussed the detection capability of LLL image intensifier for different human target. The study shows that the effect of different human target's spectral reflective characteristic on LLL image intensifier distance is mainly reflected in the average reflectivity rho(-) and the initial contrast of the target and the background C0. Reflective coefficient and spectral reflection intensity of cotton clothes are higher than polyester clothes, and detection capability of LLL image intensifier is stronger for the human target wearing cotton clothes. Experimental results show that the LLL image intensifiers have longer visual ranges for targets who wear cotton clothes than targets who wear same color but polyester clothes, and have longer visual ranges for targets who wear light-colored clothes than targets who wear dark-colored clothes. And in the full moon illumination conditions, LLL image intensifiers are more sensitive to the clothes' material.

  8. Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

    Science.gov (United States)

    Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

    2015-03-01

    Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

  9. Liquid crystal-based Mueller matrix spectral imaging polarimetry for parameterizing mineral structural organization.

    Science.gov (United States)

    Gladish, James C; Duncan, Donald D

    2017-01-20

    Herein, we discuss the remote assessment of the subwavelength organizational structure of a medium. Specifically, we use spectral imaging polarimetry, as the vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. The ability to image these effects allows for inference of spatial structural organization parameters. This work describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from liquid crystal variable retarders and a liquid crystal tunable filter. We provide results to validate the system and then show results from measurements on a mineral sample.

  10. Blind source separation of ex-vivo aorta tissue multispectral images.

    Science.gov (United States)

    Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

    2015-05-01

    Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method's performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue.

  11. Coupled Retrieval of Aerosol Properties and Surface Reflection Using the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI)

    Science.gov (United States)

    Xu, F.; van Harten, G.; Kalashnikova, O. V.; Diner, D. J.; Seidel, F. C.; Garay, M. J.; Dubovik, O.

    2016-12-01

    The Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 10 km and is observed from 9 view angles between ±67° off of nadir. We have developed an efficient and flexible code that uses the information content of AirMSPI data for a coupled retrieval of aerosol properties and surface reflection. The retrieval was built based on the multi-pixel optimization concept [2], with the use of a hybrid radiative transfer model [3] that combines the Markov Chain [4] and adding/doubling methods [5]. The convergence and robustness of our algorithm is ensured by applying constraints on (a) the spectral variation of the Bidirectional Polarization Distribution Function (BPDF) and angular shape of the Bidirectional Reflectance Distribution Function (BRDF); (b) the spectral variation of aerosol optical properties; and (c) the spatial variation of aerosol parameters across neighboring image pixels. Our retrieval approach has been tested using over 20 AirMSPI datasets having low to moderately high aerosol loadings ( 0.02550-nmSpace Sci. Rev. 16, 527 (1974).

  12. Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

    Science.gov (United States)

    Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

    2018-04-01

    The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

  13. EIT Imaging Regularization Based on Spectral Graph Wavelets.

    Science.gov (United States)

    Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Vauhkonen, Marko; Wolf, Gerhard; Mueller-Lisse, Ullrich; Moeller, Knut

    2017-09-01

    The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

  14. INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    H. Shen

    2012-08-01

    Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.

  15. Detecting Multi-scale Structures in Chandra Images of Centaurus A

    Science.gov (United States)

    Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

    1999-12-01

    Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

  16. X-ray spectral decomposition imaging system

    Energy Technology Data Exchange (ETDEWEB)

    1977-07-27

    Projection measurements are made of the transmitted X-ray beam in low and high energy regions. These are combined in a non-linear processor to produce atomic-number-dependent and density-dependent projection information. This information is used to provide cross-sectional images which are free of spectral-shift artifacts and completely define the specific material properties. The invention described herein was made in the course of work under a grant from the Department of Health, Education, and Welfare.

  17. A spatial-spectral approach for deriving high signal quality eigenvectors for remote sensing image transformations

    DEFF Research Database (Denmark)

    Rogge, Derek; Bachmann, Martin; Rivard, Benoit

    2014-01-01

    Spectral decorrelation (transformations) methods have long been used in remote sensing. Transformation of the image data onto eigenvectors that comprise physically meaningful spectral properties (signal) can be used to reduce the dimensionality of hyperspectral images as the number of spectrally...... distinct signal sources composing a given hyperspectral scene is generally much less than the number of spectral bands. Determining eigenvectors dominated by signal variance as opposed to noise is a difficult task. Problems also arise in using these transformations on large images, multiple flight...... and spectral subsampling to the data, which is accomplished by deriving a limited set of eigenvectors for spatially contiguous subsets. These subset eigenvectors are compiled together to form a new noise reduced data set, which is subsequently used to derive a set of global orthogonal eigenvectors. Data from...

  18. Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research

    OpenAIRE

    Milchenko, Mikhail; Snyder, Abraham Z.; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L.; Fouke, Sarah Jost; Marcus, Daniel S.

    2016-01-01

    Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis.

  19. Spectral analysis and filter theory in applied geophysics

    CERN Document Server

    Buttkus, Burkhard

    2000-01-01

    This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli­ cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval­ uated, and instructions provided for their practical application. Be­ sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob­ served data, maximum-entropy spectral analysis and maximum-like­ lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation­ ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil­ ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...

  20. Exploiting the capabilities of the Sentinel-2 multi spectral instrument for predicting growing stock volume in forest ecosystems

    Science.gov (United States)

    Mura, Matteo; Bottalico, Francesca; Giannetti, Francesca; Bertani, Remo; Giannini, Raffaello; Mancini, Marco; Orlandini, Simone; Travaglini, Davide; Chirici, Gherardo

    2018-04-01

    The spatial prediction of growing stock volume is one of the most frequent application of remote sensing for supporting the sustainable management of forest ecosystems. For such a purpose data from active or passive sensors are used as predictor variables in combination with measures taken in the field in sampling plots. The Sentinel-2 (S2) satellites are equipped with a Multi Spectral Instrument (MSI) capable of acquiring 13 bands in the visible and infrared domains with a spatial resolution varying between 10 and 60 m. The present study aimed at evaluating the performance of the S2-MSI imagery for estimating the growing stock volume of forest ecosystems. To do so we used 240 plots measured in two study areas in Italy. The imputation was carried out with eight k-Nearest Neighbours (k-NN) methods available in the open source YaImpute R package. In order to evaluate the S2-MSI performance we repeated the experimental protocol also with two other sets of images acquired by two well-known satellites equipped with multi spectral instruments: Landsat 8 OLI and RapidEye scanner. We found that S2 worked better than Landsat in 37.5% of the cases and in 62.5% of the cases better than RapidEye. In one study area the best performance was obtained with Landsat OLI (RMSD = 6.84%) and in the other with S2 (RMSD = 22.94%), both with the k-NN system based on a distance matrix calculated with the Random Forest algorithm. The results confirmed that S2 images are suitable for predicting growing stock volume obtaining good performances (average RMSD for both the test areas of less than 19%).

  1. Progress on Ultra-Wideband (UWB Multi-Antenna radar imaging for MIGA

    Directory of Open Access Journals (Sweden)

    Yedlin Matthew

    2016-01-01

    Full Text Available Progress on the development of the multi-channel, ground penetrating radar imaging system is presented from hardware and software perspectives. A new exponentially tapered slot antenna, with an operating bandwidth from 100 MHz to 1.5 GHz was fabricated and tested using the eight-port vector network analyzer, designed by Rhode and Schwarz Incorporated for this imaging project. An eight element antenna array mounted on two carts with automatic motor drive, was designed for optimal common midpoint (CMP data acquisition. Data acquisition scenarios were tested using the acoustic version of the NORSAR2D seismic ray-tracing software. This package enables the synthesis and analysis of multi-channel, multi-offset data acquisitions comprising more than a hundred thousand traces. Preliminary processing is in good agreement with published bistatic ground-penetrating radar images obtained in the tunnels of the Low-noise Underground Laboratory (LSBB at Rustrel, France.

  2. Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

    Science.gov (United States)

    Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

    2018-02-01

    Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

  3. 5-ALA induced fluorescent image analysis of actinic keratosis

    Science.gov (United States)

    Cho, Yong-Jin; Bae, Youngwoo; Choi, Eung-Ho; Jung, Byungjo

    2010-02-01

    In this study, we quantitatively analyzed 5-ALA induced fluorescent images of actinic keratosis using digital fluorescent color and hyperspectral imaging modalities. UV-A was utilized to induce fluorescent images and actinic keratosis (AK) lesions were demarcated from surrounding the normal region with different methods. Eight subjects with AK lesion were participated in this study. In the hyperspectral imaging modality, spectral analysis method was utilized for hyperspectral cube image and AK lesions were demarcated from the normal region. Before image acquisition, we designated biopsy position for histopathology of AK lesion and surrounding normal region. Erythema index (E.I.) values on both regions were calculated from the spectral cube data. Image analysis of subjects resulted in two different groups: the first group with the higher fluorescence signal and E.I. on AK lesion than the normal region; the second group with lower fluorescence signal and without big difference in E.I. between two regions. In fluorescent color image analysis of facial AK, E.I. images were calculated on both normal and AK lesions and compared with the results of hyperspectral imaging modality. The results might indicate that the different intensity of fluorescence and E.I. among the subjects with AK might be interpreted as different phases of morphological and metabolic changes of AK lesions.

  4. Discriminative Multi-View Interactive Image Re-Ranking.

    Science.gov (United States)

    Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

    2017-07-01

    Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

  5. Spectral CT imaging in patients with Budd-Chiari syndrome: investigation of image quality.

    Science.gov (United States)

    Su, Lei; Dong, Junqiang; Sun, Qiang; Liu, Jie; Lv, Peijie; Hu, Lili; Yan, Liangliang; Gao, Jianbo

    2014-11-01

    To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers' subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40-70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.

  6. Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation

    Directory of Open Access Journals (Sweden)

    Eva Husson

    2017-03-01

    Full Text Available Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a Growth forms including the classes of water, nymphaeid, and helophyte; and (b dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities

  7. A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Wang, Wei; Tien, Chung-Hao

    2018-01-01

    In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme. PMID:29509692

  8. A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis

    Directory of Open Access Journals (Sweden)

    Sheng-Hsun Hsieh

    2018-03-01

    Full Text Available In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme.

  9. Computational analyses of spectral trees from electrospray multi-stage mass spectrometry to aid metabolite identification.

    Science.gov (United States)

    Cao, Mingshu; Fraser, Karl; Rasmussen, Susanne

    2013-10-31

    Mass spectrometry coupled with chromatography has become the major technical platform in metabolomics. Aided by peak detection algorithms, the detected signals are characterized by mass-over-charge ratio (m/z) and retention time. Chemical identities often remain elusive for the majority of the signals. Multi-stage mass spectrometry based on electrospray ionization (ESI) allows collision-induced dissociation (CID) fragmentation of selected precursor ions. These fragment ions can assist in structural inference for metabolites of low molecular weight. Computational investigations of fragmentation spectra have increasingly received attention in metabolomics and various public databases house such data. We have developed an R package "iontree" that can capture, store and analyze MS2 and MS3 mass spectral data from high throughput metabolomics experiments. The package includes functions for ion tree construction, an algorithm (distMS2) for MS2 spectral comparison, and tools for building platform-independent ion tree (MS2/MS3) libraries. We have demonstrated the utilization of the package for the systematic analysis and annotation of fragmentation spectra collected in various metabolomics platforms, including direct infusion mass spectrometry, and liquid chromatography coupled with either low resolution or high resolution mass spectrometry. Assisted by the developed computational tools, we have demonstrated that spectral trees can provide informative evidence complementary to retention time and accurate mass to aid with annotating unknown peaks. These experimental spectral trees once subjected to a quality control process, can be used for querying public MS2 databases or de novo interpretation. The putatively annotated spectral trees can be readily incorporated into reference libraries for routine identification of metabolites.

  10. Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

    Directory of Open Access Journals (Sweden)

    Myung-Ho Ju

    2013-10-01

    Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

  11. Evaluation of therapy for dilated cardiomyopathy with heart failure by iodine-123 metaiodobenzyl-guanidine imaging. Comparison with heart rate variability power spectral analysis

    Energy Technology Data Exchange (ETDEWEB)

    Li, Shou-lin; Ikeda, Jun; Takita, Tamotsu; Sekiguchi, Yohei; Demachi, Jun; Chikama, Hisao; Goto, Atsushi; Shirato, Kunio [Tohoku Univ., Sendai (Japan). School of Medicine

    1998-11-01

    The relationship between the myocardial uptake of iodine-123 metaiodobenzylguanidine ({sup 123}I-MIBG) and heart rate variability parameters has not been determined. This study determined the relationship between the change in myocardial uptake of {sup 123}I-MIBG and improvement in left ventricular function after treatment, to determine the usefulness of {sup 123}I-MIBG imaging to assess the effect of therapy on heart failure due to dilated cardiomyopathy (DCM). {sup 123}I-MIBG imaging and power spectral analysis of heart rate variability were performed before and after treatment in 17 patients with heart failure due to DCM. The following parameters were compared before and after treatment: New York Heart Association (NYHA) functional class, radiographic cardiothoracic ratio (CTR), blood pressure, echocardiographic data (left ventricular end-systolic (LVDs) and end-diastolic (LVDd) diameters, left ventricular ejection fraction (LVEF)), plasma concentrations of norepinephrine and epinephrine, heart rate variability power spectral analysis data (mean low frequency (MLF) and high frequency power (MHF)) and the myocardium to mediastinum activity ratio (MYO/M) obtained in early and late images, and washout rate calculated by anterior planar imaging of {sup 123}I-MIBG. The NYHA functional class, LVEF, LVDs, CTR, MLF and MHF improved after treatment. Early MYO/M and late MYO/M improved after treatment. The rate of increase in late MYO/M was positively correlated with the rate of improvement of LVEF after treatment. Furthermore, the late MYO/M was negatively correlated with MLF. Washout rate revealed no correlation with hemodynamic parameters. These findings suggest that late MYO/M is more useful than washout rate to assess the effect of treatment on heart failure due to DCM. Furthermore, the {sup 123}I-MIBG imaging and heart rate variability parameters are useful to assess the autonomic tone in DCM with heart failure. (author)

  12. Evaluation of therapy for dilated cardiomyopathy with heart failure by iodine-123 metaiodobenzyl-guanidine imaging. Comparison with heart rate variability power spectral analysis

    International Nuclear Information System (INIS)

    Li, Shou-lin; Ikeda, Jun; Takita, Tamotsu; Sekiguchi, Yohei; Demachi, Jun; Chikama, Hisao; Goto, Atsushi; Shirato, Kunio

    1998-01-01

    The relationship between the myocardial uptake of iodine-123 metaiodobenzylguanidine ( 123 I-MIBG) and heart rate variability parameters has not been determined. This study determined the relationship between the change in myocardial uptake of 123 I-MIBG and improvement in left ventricular function after treatment, to determine the usefulness of 123 I-MIBG imaging to assess the effect of therapy on heart failure due to dilated cardiomyopathy (DCM). 123 I-MIBG imaging and power spectral analysis of heart rate variability were performed before and after treatment in 17 patients with heart failure due to DCM. The following parameters were compared before and after treatment: New York Heart Association (NYHA) functional class, radiographic cardiothoracic ratio (CTR), blood pressure, echocardiographic data (left ventricular end-systolic (LVDs) and end-diastolic (LVDd) diameters, left ventricular ejection fraction (LVEF)), plasma concentrations of norepinephrine and epinephrine, heart rate variability power spectral analysis data (mean low frequency (MLF) and high frequency power (MHF)) and the myocardium to mediastinum activity ratio (MYO/M) obtained in early and late images, and washout rate calculated by anterior planar imaging of 123 I-MIBG. The NYHA functional class, LVEF, LVDs, CTR, MLF and MHF improved after treatment. Early MYO/M and late MYO/M improved after treatment. The rate of increase in late MYO/M was positively correlated with the rate of improvement of LVEF after treatment. Furthermore, the late MYO/M was negatively correlated with MLF. Washout rate revealed no correlation with hemodynamic parameters. These findings suggest that late MYO/M is more useful than washout rate to assess the effect of treatment on heart failure due to DCM. Furthermore, the 123 I-MIBG imaging and heart rate variability parameters are useful to assess the autonomic tone in DCM with heart failure. (author)

  13. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

  14. Element-specific spectral imaging of multiple contrast agents: a phantom study

    Science.gov (United States)

    Panta, R. K.; Bell, S. T.; Healy, J. L.; Aamir, R.; Bateman, C. J.; Moghiseh, M.; Butler, A. P. H.; Anderson, N. G.

    2018-02-01

    This work demonstrates the feasibility of simultaneous discrimination of multiple contrast agents based on their element-specific and energy-dependent X-ray attenuation properties using a pre-clinical photon-counting spectral CT. We used a photon-counting based pre-clinical spectral CT scanner with four energy thresholds to measure the X-ray attenuation properties of various concentrations of iodine (9, 18 and 36 mg/ml), gadolinium (2, 4 and 8 mg/ml) and gold (2, 4 and 8 mg/ml) based contrast agents, calcium chloride (140 and 280 mg/ml) and water. We evaluated the spectral imaging performances of different energy threshold schemes between 25 to 82 keV at 118 kVp, based on K-factor and signal-to-noise ratio and ranked them. K-factor was defined as the X-ray attenuation in the K-edge containing energy range divided by the X-ray attenuation in the preceding energy range, expressed as a percentage. We evaluated the effectiveness of the optimised energy selection to discriminate all three contrast agents in a phantom of 33 mm diameter. A photon-counting spectral CT using four energy thresholds of 27, 33, 49 and 81 keV at 118 kVp simultaneously discriminated three contrast agents based on iodine, gadolinium and gold at various concentrations using their K-edge and energy-dependent X-ray attenuation features in a single scan. A ranking method to evaluate spectral imaging performance enabled energy thresholds to be optimised to discriminate iodine, gadolinium and gold contrast agents in a single spectral CT scan. Simultaneous discrimination of multiple contrast agents in a single scan is likely to open up new possibilities of improving the accuracy of disease diagnosis by simultaneously imaging multiple bio-markers each labelled with a nano-contrast agent.

  15. A Practical Guide to Multi-image Alignment

    OpenAIRE

    Aguerrebere, Cecilia; Delbracio, Mauricio; Bartesaghi, Alberto; Sapiro, Guillermo

    2018-01-01

    Multi-image alignment, bringing a group of images into common register, is an ubiquitous problem and the first step of many applications in a wide variety of domains. As a result, a great amount of effort is being invested in developing efficient multi-image alignment algorithms. Little has been done, however, to answer fundamental practical questions such as: what is the comparative performance of existing methods? is there still room for improvement? under which conditions should one techni...

  16. Automated thermal mapping techniques using chromatic image analysis

    Science.gov (United States)

    Buck, Gregory M.

    1989-01-01

    Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

  17. Development of low-dose photon-counting contrast-enhanced tomosynthesis with spectral imaging.

    Science.gov (United States)

    Schmitzberger, Florian F; Fallenberg, Eva Maria; Lawaczeck, Rüdiger; Hemmendorff, Magnus; Moa, Elin; Danielsson, Mats; Bick, Ulrich; Diekmann, Susanne; Pöllinger, Alexander; Engelken, Florian J; Diekmann, Felix

    2011-05-01

    To demonstrate the feasibility of low-dose photon-counting tomosynthesis in combination with a contrast agent (contrast material-enhanced tomographic mammography) for the differentiation of breast cancer. All studies were approved by the institutional review board, and all patients provided written informed consent. A phantom model with wells of iodinated contrast material (3 mg of iodine per milliliter) 1, 2, 5, 10, and 15 mm in diameter was assessed. Nine patients with malignant lesions and one with a high-risk lesion (atypical papilloma) were included (all women; mean age, 60.7 years). A multislit photon-counting tomosynthesis system was utilized (spectral imaging) to produce both low- and high-energy tomographic data (below and above the k edge of iodine, respectively) in a single scan, which allowed for dual-energy visualization of iodine. Images were obtained prior to contrast material administration and 120 and 480 seconds after contrast material administration. Four readers independently assessed the images along with conventional mammograms, ultrasonographic images, and magnetic resonance images. Glandular dose was estimated. Contrast agent was visible in the phantom model with simulated spherical tumor diameters as small as 5 mm. The average glandular dose was measured as 0.42 mGy per complete spectral imaging tomosynthesis scan of one breast. Because there were three time points (prior to contrast medium administration and 120 and 480 seconds after contrast medium administration), this resulted in a total dose of 1.26 mGy for the whole procedure in the breast with the abnormality. Seven of 10 cases were categorized as Breast Imaging Reporting and Data System score of 4 or higher by all four readers when reviewing spectral images in combination with mammograms. One lesion near the chest wall was not captured on the spectral image because of a positioning problem. The use of contrast-enhanced tomographic mammography has been demonstrated successfully in

  18. A spectral approach for the quantitative description of cardiac collagen network from nonlinear optical imaging.

    Science.gov (United States)

    Masè, Michela; Cristoforetti, Alessandro; Avogaro, Laura; Tessarolo, Francesco; Piccoli, Federico; Caola, Iole; Pederzolli, Carlo; Graffigna, Angelo; Ravelli, Flavia

    2015-01-01

    The assessment of collagen structure in cardiac pathology, such as atrial fibrillation (AF), is essential for a complete understanding of the disease. This paper introduces a novel methodology for the quantitative description of collagen network properties, based on the combination of nonlinear optical microscopy with a spectral approach of image processing and analysis. Second-harmonic generation (SHG) microscopy was applied to atrial tissue samples from cardiac surgery patients, providing label-free, selective visualization of the collagen structure. The spectral analysis framework, based on 2D-FFT, was applied to the SHG images, yielding a multiparametric description of collagen fiber orientation (angle and anisotropy indexes) and texture scale (dominant wavelength and peak dispersion indexes). The proof-of-concept application of the methodology showed the capability of our approach to detect and quantify differences in the structural properties of the collagen network in AF versus sinus rhythm patients. These results suggest the potential of our approach in the assessment of collagen properties in cardiac pathologies related to a fibrotic structural component.

  19. SpectralNET – an application for spectral graph analysis and visualization

    Directory of Open Access Journals (Sweden)

    Schreiber Stuart L

    2005-10-01

    Full Text Available Abstract Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices and interactions (edges that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors. Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is

  20. Metabolic Mapping of Breast Cancer with Multiphoton Spectral and Lifetime Imaging

    Science.gov (United States)

    2007-03-01

    2002. Spectrally resolved fluorescence lifetime imaging microscopy. Appl. Spec- trosc. 56 :155-166. 38. Becker, W., A. Bergmann, E. Haustein , Z...photon fluores- cence lifetime imaging microscopy of macrophage-mediated antigen processing. J. Microsc. 185 :339-353. 45. Lin, H.J., P. Herman , and

  1. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

    2011-01-01

    This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

  2. Analysis of PET hypoxia imaging in the quantitative imaging for personalized cancer medicine program

    International Nuclear Information System (INIS)

    Yeung, Ivan; Driscoll, Brandon; Keller, Harald; Shek, Tina; Jaffray, David; Hedley, David

    2014-01-01

    Quantitative imaging is an important tool in clinical trials of testing novel agents and strategies for cancer treatment. The Quantitative Imaging Personalized Cancer Medicine Program (QIPCM) provides clinicians and researchers participating in multi-center clinical trials with a central repository for their imaging data. In addition, a set of tools provide standards of practice (SOP) in end-to-end quality assurance of scanners and image analysis. The four components for data archiving and analysis are the Clinical Trials Patient Database, the Clinical Trials PACS, the data analysis engine(s) and the high-speed networks that connect them. The program provides a suite of software which is able to perform RECIST, dynamic MRI, CT and PET analysis. The imaging data can be assessed securely from remote and analyzed by researchers with these software tools, or with tools provided by the users and installed at the server. Alternatively, QIPCM provides a service for data analysis on the imaging data according developed SOP. An example of a clinical study in which patients with unresectable pancreatic adenocarcinoma were studied with dynamic PET-FAZA for hypoxia measurement will be discussed. We successfully quantified the degree of hypoxia as well as tumor perfusion in a group of 20 patients in terms of SUV and hypoxic fraction. It was found that there is no correlation between bulk tumor perfusion and hypoxia status in this cohort. QIPCM also provides end-to-end QA testing of scanners used in multi-center clinical trials. Based on quality assurance data from multiple CT-PET scanners, we concluded that quality control of imaging was vital in the success in multi-center trials as different imaging and reconstruction parameters in PET imaging could lead to very different results in hypoxia imaging. (author)

  3. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  4. A multi-domain spectral method for time-fractional differential equations

    Science.gov (United States)

    Chen, Feng; Xu, Qinwu; Hesthaven, Jan S.

    2015-07-01

    This paper proposes an approach for high-order time integration within a multi-domain setting for time-fractional differential equations. Since the kernel is singular or nearly singular, two main difficulties arise after the domain decomposition: how to properly account for the history/memory part and how to perform the integration accurately. To address these issues, we propose a novel hybrid approach for the numerical integration based on the combination of three-term-recurrence relations of Jacobi polynomials and high-order Gauss quadrature. The different approximations used in the hybrid approach are justified theoretically and through numerical examples. Based on this, we propose a new multi-domain spectral method for high-order accurate time integrations and study its stability properties by identifying the method as a generalized linear method. Numerical experiments confirm hp-convergence for both time-fractional differential equations and time-fractional partial differential equations.

  5. Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

    Science.gov (United States)

    Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

    2010-11-19

    Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without

  6. Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

    Science.gov (United States)

    Matsuoka, M.

    2012-07-01

    A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

  7. Spectral analysis by correlation

    International Nuclear Information System (INIS)

    Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G.

    1969-01-01

    The spectral density of a signal, which represents its power distribution along the frequency axis, is a function which is of great importance, finding many uses in all fields concerned with the processing of the signal (process identification, vibrational analysis, etc...). Amongst all the possible methods for calculating this function, the correlation method (correlation function calculation + Fourier transformation) is the most promising, mainly because of its simplicity and of the results it yields. The study carried out here will lead to the construction of an apparatus which, coupled with a correlator, will constitute a set of equipment for spectral analysis in real time covering the frequency range 0 to 5 MHz. (author) [fr

  8. Multi-scale image segmentation method with visual saliency constraints and its application

    Science.gov (United States)

    Chen, Yan; Yu, Jie; Sun, Kaimin

    2018-03-01

    Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works

  9. A novel scatter separation method for multi-energy x-ray imaging

    Science.gov (United States)

    Sossin, A.; Rebuffel, V.; Tabary, J.; Létang, J. M.; Freud, N.; Verger, L.

    2016-06-01

    X-ray imaging coupled with recently emerged energy-resolved photon counting detectors provides the ability to differentiate material components and to estimate their respective thicknesses. However, such techniques require highly accurate images. The presence of scattered radiation leads to a loss of spatial contrast and, more importantly, a bias in radiographic material imaging and artefacts in computed tomography (CT). The aim of the present study was to introduce and evaluate a partial attenuation spectral scatter separation approach (PASSSA) adapted for multi-energy imaging. This evaluation was carried out with the aid of numerical simulations provided by an internal simulation tool, Sindbad-SFFD. A simplified numerical thorax phantom placed in a CT geometry was used. The attenuation images and CT slices obtained from corrected data showed a remarkable increase in local contrast and internal structure detectability when compared to uncorrected images. Scatter induced bias was also substantially decreased. In terms of quantitative performance, the developed approach proved to be quite accurate as well. The average normalized root-mean-square error between the uncorrected projections and the reference primary projections was around 23%. The application of PASSSA reduced this error to around 5%. Finally, in terms of voxel value accuracy, an increase by a factor  >10 was observed for most inspected volumes-of-interest, when comparing the corrected and uncorrected total volumes.

  10. The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

    Science.gov (United States)

    Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

    2011-08-01

    Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Intensity correction method customized for multi-animal abdominal MR imaging with 3 T clinical scanner and multi-array coil

    International Nuclear Information System (INIS)

    Mitsuda, Minoru; Yamaguchi, Masayuki; Nakagami, Ryutaro; Furuta, Toshihiro; Fujii, Hirofumi; Sekine, Norio; Niitsu, Mamoru; Moriyama, Noriyuki

    2013-01-01

    Simultaneous magnetic resonance (MR) imaging of multiple small animals in a single session increases throughput of preclinical imaging experiments. Such imaging using a 3-tesla clinical scanner with multi-array coil requires correction of intensity variation caused by the inhomogeneous sensitivity profile of the coil. We explored a method for correcting intensity that we customized for multi-animal MR imaging, especially abdominal imaging. Our institutional committee for animal experimentation approved the protocol. We acquired high resolution T 1 -, T 2 -, and T 2 * -weighted images and low resolution proton density-weighted images (PDWIs) of 4 rat abdomens simultaneously using a 3T clinical scanner and custom-made multi-array coil. For comparison, we also acquired T 1 -, T 2 -, and T 2 * -weighted volume coil images in the same rats in 4 separate sessions. We used software created in-house to correct intensity variation. We applied thresholding to the PDWIs to produce binary images that displayed only a signal-producing area, calculated multi-array coil sensitivity maps by dividing low-pass filtered PDWIs by low-pass filtered binary images pixel by pixel, and divided uncorrected T 1 -, T 2 -, or T 2 * -weighted images by those maps to obtain intensity-corrected images. We compared tissue contrast among the liver, spinal canal, and muscle between intensity-corrected multi-array coil images and volume coil images. Our intensity correction method performed well for all pulse sequences studied and corrected variation in original multi-array coil images without deteriorating the throughput of animal experiments. Tissue contrasts were comparable between intensity-corrected multi-array coil images and volume coil images. Our intensity correction method customized for multi-animal abdominal MR imaging using a 3T clinical scanner and dedicated multi-array coil could facilitate image interpretation. (author)

  12. Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2012-05-01

    Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.

  13. Extended depth of field integral imaging using multi-focus fusion

    Science.gov (United States)

    Piao, Yongri; Zhang, Miao; Wang, Xiaohui; Li, Peihua

    2018-03-01

    In this paper, we propose a new method for depth of field extension in integral imaging by realizing the image fusion method on the multi-focus elemental images. In the proposed method, a camera is translated on a 2D grid to take multi-focus elemental images by sweeping the focus plane across the scene. Simply applying an image fusion method on the elemental images holding rich parallax information does not work effectively because registration accuracy of images is the prerequisite for image fusion. To solve this problem an elemental image generalization method is proposed. The aim of this generalization process is to geometrically align the objects in all elemental images so that the correct regions of multi-focus elemental images can be exacted. The all-in focus elemental images are then generated by fusing the generalized elemental images using the block based fusion method. The experimental results demonstrate that the depth of field of synthetic aperture integral imaging system has been extended by realizing the generation method combined with the image fusion on multi-focus elemental images in synthetic aperture integral imaging system.

  14. Three-dimensional fabric analysis for anisotropic material using multi-directional scanning line. Application to x-ray CI image

    International Nuclear Information System (INIS)

    Takemura, Takato; Takahashi, Manabu; Oda, Masanobu; Hirai, Hidekazu; Murakoshi, Atsushi; Miura, Makoto

    2007-01-01

    In microscopic analysis, materials are characterized by a three-dimensional (3D) microstructure which is composed of constituent elements such as pores, voids and cracks. A material's mechanical and hydrological properties are strongly dependent on its microstructure. In order to discuss the mechanics of geomaterials on a microstructural level, detailed information on their 3D macrostructure is required. X-ray computed tomography is a powerful non-destructive method for determining the microstructure, however it can be difficult to determine a material's microstructure from the reconstructed 3D image. We successfully evaluated the 3D microstructural anisotropy of porous and fibrous materials using a multi-directional scanning line method that employs straightforward image analysis, and its results were visualized using stereonet projection. (author)

  15. Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Naveed ur Rehman

    2015-05-01

    Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

  16. A Gimbal-Stabilized Compact Hyperspectral Imaging System, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The Gimbal-stabilized Compact Hyperspectral Imaging System (GCHIS) fully integrates multi-sensor spectral imaging, stereovision, GPS and inertial measurement,...

  17. Image quality of conventional images of dual-layer SPECTRAL CT: a phantom study.

    Science.gov (United States)

    van Ommen, F; Bennink, E; Vlassenbroek, A; Dankbaar, J W; Schilham, A M R; Viergever, M A; de Jong, H W A M

    2018-05-10

    Spectral CT using a dual layer detector offers the possibility of retrospectively introducing spectral information to conventional CT images. In theory, the dual-layer technology should not come with a dose or image quality penalty for conventional images. In this study, we evaluate the influence of a dual-layer detector (IQon Spectral CT, Philips) on the image quality of conventional CT images, by comparing these images with those of a conventional but otherwise technically comparable single-layer CT scanner (Brilliance iCT, Philips), by means of phantom experiments. For both CT scanners conventional CT images were acquired using four adult scanning protocols: i) body helical, ii) body axial, iii) head helical and iv) head axial. A CATPHAN 600 phantom was scanned to conduct an assessment of image quality metrics at equivalent (CTDI) dose levels. Noise was characterized by means of noise power spectra (NPS) and standard deviation (SD) of a uniform region, and spatial resolution was evaluated with modulation transfer functions (MTF) of a tungsten wire. In addition, contrast-to-noise ratio (CNR), image uniformity, CT number linearity, slice thickness, slice spacing, and spatial linearity were measured and evaluated. Additional measurements of CNR, resolution and noise were performed in two larger phantoms. The resolution levels at 50%, 10% and 5% MTF of the iCT and IQon showed small but significant differences up to 0.25 lp/cm for body scans, and up to 0.2 lp/cm for head scans in favor of the IQon. The iCT and IQon showed perfect CT linearity for body scans, but for head scans both scanners showed an underestimation of the CT numbers of materials with a high opacity. Slice thickness was slightly overestimated for both scanners. Slice spacing was comparable and reconstructed correctly. In addition, spatial linearity was excellent for both scanners, with a maximum error of 0.11 mm. CNR was higher on the IQon compared to the iCT for both normal and larger phantoms with

  18. Sensitivity and Uncertainty Analysis of Coupled Reactor Physics Problems : Method Development for Multi-Physics in Reactors

    NARCIS (Netherlands)

    Perkó, Z.

    2015-01-01

    This thesis presents novel adjoint and spectral methods for the sensitivity and uncertainty (S&U) analysis of multi-physics problems encountered in the field of reactor physics. The first part focuses on the steady state of reactors and extends the adjoint sensitivity analysis methods well

  19. Using Image Texture and Spectral Reflectance Analysis to Detect Yellowness and Esca in Grapevines at Leaf-Level

    Directory of Open Access Journals (Sweden)

    Hania Al-Saddik

    2018-04-01

    Full Text Available Plant diseases are one of the main reasons behind major economic and production losses in the agricultural field. Current research activities enable large fields monitoring and plant disease detection using innovative and robust technologies. French grapevines have a reputation for producing premium quality wines, however, these major fruit crops are susceptible to many diseases, including Esca, Downy mildew, Powdery mildew, Yellowing, and many others. In this study, we focused on two main infections (Esca and Yellowing, and data were gathered from fields that were located in Aquitaine and Burgundy regions, France. Since plant diseases can be diagnosed from the properties of the leaf, we acquired both Red-Green-Blue (RGB digital image and hyperspectral reflectance data from infected and healthy leaves. Biophysical parameters that were produced by the PROSPECT model inversion together with texture parameters compiled from the literature were deduced. Then we investigated their relationship to damage caused by Yellowing and Esca. This study examined whether spectral and textural data can identify the two diseases through the use of Neural Networks. We obtained an overall accuracy of 99% for both of the diseases when textural and spectral data are combined. These results suggest that, first, biophysical parameters present a valid dimension reduction tool that could replace the use of complete hyperspectral data. Second, remote sensing using spectral reflectance and digital images can make an overall nondestructive, rapid, cost-effective, and reproducible technique to determine diseases in grapevines with a good level of accuracy.

  20. Computer generated multi-color graphics in whole body gamma spectral analysis

    International Nuclear Information System (INIS)

    Phillips, W.G.; Curtis, S.P.; Environmental Protection Agency, Las Vegas, NV)

    1984-01-01

    A medium resolution color graphics terminal (512 x 512 pixels) was appended to a computerized gamma spectrometer for the display of whole body counting data. The color display enhances the ability of a spectroscopist to identify at a glance multicolored spectral regions of interest immediate qualitative interpretation. Spectral data from subjects containing low concentrations of gamma emitters obtained by both NaI(T1) and phoswich detectors are viewed by the method. In addition, software generates a multispectral display by which the gross, background, and net spectra are displayed in color simultaneously on a single screen

  1. Evaluation of non-invasive multispectral imaging as a tool for measuring the effect of systemic therapy in Kaposi sarcoma.

    Directory of Open Access Journals (Sweden)

    Jana M Kainerstorfer

    Full Text Available Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect.

  2. Analysis of X-ray Spectra of High-Z Elements obtained on Nike with high spectral and spatial resolution

    Science.gov (United States)

    Aglitskiy, Yefim; Weaver, J. L.; Karasik, M.; Serlin, V.; Obenschain, S. P.; Ralchenko, Yu.

    2014-10-01

    The spectra of multi-charged ions of Hf, Ta, W, Pt, Au and Bi have been studied on Nike krypton-fluoride laser facility with the help of two kinds of X-ray spectrometers. First, survey instrument covering a spectral range from 0.5 to 19.5 angstroms which allows simultaneous observation of both M- and N- spectra of above mentioned elements with high spectral resolution. Second, an imaging spectrometer with interchangeable spherically bent Quartz crystals that added higher efficiency, higher spectral resolution and high spatial resolution to the qualities of the former one. Multiple spectral lines with X-ray energies as high as 4 keV that belong to the isoelectronic sequences of Fe, Co, Ni, Cu and Zn were identified with the help of NOMAD package developed by Dr. Yu. Ralchenko and colleagues. In our continuous effort to support DOE-NNSA's inertial fusion program, this campaign covered a wide range of plasma conditions that result in production of relatively energetic X-rays. Work supported by the US DOE/NNSA.

  3. TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kapadia, A; Morris, R; Albanese, K; Spencer, J; McCall, S; Greenberg, J [Duke University, Durham, NC (United States)

    2016-06-15

    Purpose: We have previously described the development and testing of a coherent-scatter spectral imaging system for identification of cancer. Our prior evaluations were performed using either tissue surrogate phantoms or formalin-fixed tissue obtained from pathology. Here we present the first results from a scatter imaging study using fresh breast tumor tissues obtained through surgical excision. Methods: A coherent-scatter imaging system was built using a clinical X-ray tube, photon counting detectors, and custom-designed coded-apertures. System performance was characterized using calibration phantoms of biological materials. Fresh breast tumors were obtained from patients undergoing mastectomy and lumpectomy surgeries for breast cancer. Each specimen was vacuum-sealed, scanned using the scatter imaging system, and then sent to pathology for histological workup. Scatter images were generated separately for each tissue specimen and analyzed to identify voxels containing malignant tissue. The images were compared against histological analysis (H&E + pathologist identification of tumors) to assess the match between scatter-based and histological diagnosis. Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2–3 mm, and the total scan time for each specimen was under 15 minutes. Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It

  4. Chest CT using spectral filtration: radiation dose, image quality, and spectrum of clinical utility

    Energy Technology Data Exchange (ETDEWEB)

    Braun, Franziska M.; Johnson, Thorsten R.C.; Sommer, Wieland H.; Thierfelder, Kolja M.; Meinel, Felix G. [University Hospital Munich, Institute for Clinical Radiology, Munich (Germany)

    2015-06-01

    To determine the radiation dose, image quality, and clinical utility of non-enhanced chest CT with spectral filtration. We retrospectively analysed 25 non-contrast chest CT examinations acquired with spectral filtration (tin-filtered Sn100 kVp spectrum) compared to 25 examinations acquired without spectral filtration (120 kV). Radiation metrics were compared. Image noise was measured. Contrast-to-noise-ratio (CNR) and figure-of-merit (FOM) were calculated. Diagnostic confidence for the assessment of various thoracic pathologies was rated by two independent readers. Effective chest diameters were comparable between groups (P = 0.613). In spectral filtration CT, median CTDI{sub vol}, DLP, and size-specific dose estimate (SSDE) were reduced (0.46 vs. 4.3 mGy, 16 vs. 141 mGy*cm, and 0.65 vs. 5.9 mGy, all P < 0.001). Spectral filtration CT had higher image noise (21.3 vs. 13.2 HU, P < 0.001) and lower CNR (47.2 vs. 75.3, P < 0.001), but was more dose-efficient (FOM 10,659 vs. 2,231/mSv, P < 0.001). Diagnostic confidence for parenchymal lung disease and osseous pathologies was lower with spectral filtration CT, but no significant difference was found for pleural pathologies, pulmonary nodules, or pneumonia. Non-contrast chest CT using spectral filtration appears to be sufficient for the assessment of a considerable spectrum of thoracic pathologies, while providing superior dose efficiency, allowing for substantial radiation dose reduction. (orig.)

  5. Imaging the spectral reflectance properties of bipolar radiofrequency-fused bowel tissue

    Science.gov (United States)

    Clancy, Neil T.; Arya, Shobhit; Stoyanov, Danail; Du, Xiaofei; Hanna, George B.; Elson, Daniel S.

    2015-07-01

    Delivery of radiofrequency (RF) electrical energy is used during surgery to heat and seal tissue, such as vessels, allowing resection without blood loss. Recent work has suggested that this approach may be extended to allow surgical attachment of larger tissue segments for applications such as bowel anastomosis. In a large series of porcine surgical procedures bipolar RF energy was used to resect and re-seal the small bowel in vivo with a commercial tissue fusion device (Ligasure; Covidien PLC, USA). The tissue was then imaged with a multispectral imaging laparoscope to obtain a spectral datacube comprising both fused and healthy tissue. Maps of blood volume, oxygen saturation and scattering power were derived from the measured reflectance spectra using an optimised light-tissue interaction model. A 60% increase in reflectance of visible light (460-700 nm) was observed after fusion, with the tissue taking on a white appearance. Despite this the distinctive shape of the haemoglobin absorption spectrum was still noticeable in the 460-600 nm wavelength range. Scattering power increased in the fused region in comparison to normal serosa, while blood volume and oxygen saturation decreased. Observed fusion-induced changes in the reflectance spectrum are consistent with the biophysical changes induced through tissue denaturation and increased collagen cross-linking. The multispectral imager allows mapping of the spatial extent of these changes and classification of the zone of damaged tissue. Further analysis of the spectral data in parallel with histopathological examination of excised specimens will allow correlation of the optical property changes with microscopic alterations in tissue structure.

  6. Reconstruction of MODIS Spectral Reflectance under Cloudy-Sky Condition

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2016-09-01

    Full Text Available Clouds usually cause invalid observations for sensors aboard satellites, which corrupts the spatio-temporal continuity of land surface parameters retrieved from remote sensing data (e.g., MODerate Resolution Imaging Spectroradiometer (MODIS data and prevents the fusing of multi-source remote sensing data in the field of quantitative remote sensing. Based on the requirements of spatio-temporal continuity and the necessity of methods to restore bad pixels, primarily resulting from image processing, this study developed a novel method to derive the spectral reflectance for MODIS band of cloudy pixels in the visual–near infrared (VIS–NIR spectral channel based on the Bidirectional Reflectance Distribution Function (BRDF and multi-spatio-temporal observations. The proposed method first constructs the spatial distribution of land surface reflectance based on the corresponding BRDF and the solar-viewing geometry; then, a geographically weighted regression (GWR is introduced to individually derive the spectral surface reflectance for MODIS band of cloudy pixels. A validation of the proposed method shows that a total root-mean-square error (RMSE of less than 6% and a total R2 of more than 90% are detected, which indicates considerably better precision than those exhibited by other existing methods. Further validation of the retrieved white-sky albedo based on the spectral reflectance for MODIS band of cloudy pixels confirms an RMSE of 3.6% and a bias of 2.2%, demonstrating very high accuracy of the proposed method.

  7. Using Raman spectroscopic imaging for non-destructive analysis of filler distribution in chalk filled polypropylene

    DEFF Research Database (Denmark)

    Boros, Evelin; Porse, Peter Bak; Nielsen, Inga

    2016-01-01

    A feasibility study on using Raman spectral imaging for visualization and analysis of filler distribution in chalk filled poly-propylene samples has been carried out. The spectral images were acquired using a Raman spectrometer with 785 nm light source.Eight injection-molded samples with concentr...

  8. SUPPORT VECTOR MACHINE CLASSIFICATION OF OBJECT-BASED DATA FOR CROP MAPPING, USING MULTI-TEMPORAL LANDSAT IMAGERY

    Directory of Open Access Journals (Sweden)

    R. Devadas

    2012-07-01

    Full Text Available Crop mapping and time series analysis of agronomic cycles are critical for monitoring land use and land management practices, and analysing the issues of agro-environmental impacts and climate change. Multi-temporal Landsat data can be used to analyse decadal changes in cropping patterns at field level, owing to its medium spatial resolution and historical availability. This study attempts to develop robust remote sensing techniques, applicable across a large geographic extent, for state-wide mapping of cropping history in Queensland, Australia. In this context, traditional pixel-based classification was analysed in comparison with image object-based classification using advanced supervised machine-learning algorithms such as Support Vector Machine (SVM. For the Darling Downs region of southern Queensland we gathered a set of Landsat TM images from the 2010–2011 cropping season. Landsat data, along with the vegetation index images, were subjected to multiresolution segmentation to obtain polygon objects. Object-based methods enabled the analysis of aggregated sets of pixels, and exploited shape-related and textural variation, as well as spectral characteristics. SVM models were chosen after examining three shape-based parameters, twenty-three textural parameters and ten spectral parameters of the objects. We found that the object-based methods were superior to the pixel-based methods for classifying 4 major landuse/land cover classes, considering the complexities of within field spectral heterogeneity and spectral mixing. Comparative analysis clearly revealed that higher overall classification accuracy (95% was observed in the object-based SVM compared with that of traditional pixel-based classification (89% using maximum likelihood classifier (MLC. Object-based classification also resulted speckle-free images. Further, object-based SVM models were used to classify different broadacre crop types for summer and winter seasons. The influence of

  9. Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming

    Science.gov (United States)

    Lang, H. R.; Conel, J. E.; Paylor, E. D.

    1984-01-01

    A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.

  10. Digital spectral analysis parametric, non-parametric and advanced methods

    CERN Document Server

    Castanié, Francis

    2013-01-01

    Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

  11. SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y [University of Kansas Hospital, Kansas City, KS (United States); Fullerton, G; Goins, B [University of Texas Health Science Center at San Antonio, San Antonio, TX (United States)

    2015-06-15

    Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement

  12. On multi-spectral quantitative photoacoustic tomography in diffusive regime

    International Nuclear Information System (INIS)

    Bal, Guillaume; Ren, Kui

    2012-01-01

    The objective of quantitative photoacoustic tomography (qPAT) is to reconstruct the diffusion, absorption and Grüneisen thermodynamic coefficients of heterogeneous media from knowledge of the interior absorbed radiation. It has been shown in Bal and Ren (2011 Inverse Problems 27 075003), based on diffusion theory, that with data acquired at one given wavelength, all three coefficients cannot be reconstructed uniquely. In this work, we study the multi-spectral qPAT problem and show that when multiple wavelength data are available, all coefficients can be reconstructed simultaneously under minor prior assumptions. Moreover, the reconstructions are shown to be very stable. We present some numerical simulations that support the theoretical results. (paper)

  13. Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

    Science.gov (United States)

    Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

    2013-08-01

    During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.

  14. Analysis of multi-wall carbon nanotube based porous Li battery electrodes’ using TOF-SIMS ion imaging

    International Nuclear Information System (INIS)

    Karar, N.; Singh, B.P.; Elizabeth, Indu

    2015-01-01

    Highlights: • Usage of MWCNT material for Li battery electrode. • LiPF 6 as electrolyte material. • Charging and discharging cycles of the battery and their effect on the electrode and electrolyte material. • TOF-SIMS ion imaging based analysis of the effects of the charging discharging cycles on the materials. • Effects of multi-atomic molecules. - Abstract: Li ion batteries and its accessories are now under increased focus of research due to enhanced energy storage and recycling requirements and the need for clean environments. In this context, observations on Li battery electrodes prepared using multi-wall carbon nanotubes (MWCNT) coated on stainless steel as observed by time of flight secondary ion mass spectrometry (TOF-SIMS) analysis and their relevance in understanding and improving the electrochemical properties of such battery systems are discussed. Porosity issues due to MWCNT, and accumulation of chemical residues with operational cycles were observed, their possible causes were also analyzed and discussed. Issues on change in electrode performance due to usage of tin oxide coatings on the MWCNT were also compared and analyzed

  15. Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, N.G. [University of Otago, Department of Radiology, Christchurch (New Zealand); Butler, A.P. [University of Otago, Department of Radiology, Christchurch (New Zealand); University of Canterbury, Physics and Astronomy, Christchurch (New Zealand); Scott, N.J.A. [University of Otago, Department of Medicine, Christchurch (New Zealand); Cook, N.J. [Christchurch Hospital, Medical Physics and Bioengineering, Christchurch (New Zealand); Butzer, J.S. [Karlsruhe Institute of Technology, Physics Department, Karlsruhe (Germany); Schleich, N. [University of Canterbury, Physics and Astronomy, Christchurch (New Zealand); Christchurch Hospital, Medical Physics and Bioengineering, Christchurch (New Zealand); Firsching, M. [Friedrich Alexander University, Physics Department, Erlangen (Germany); Grasset, R.; Ruiter, N. de [University of Canterbury, Hitlab NZ, Christchurch (New Zealand); Campbell, M. [European Organisation for Nuclear Research, Physics Section, Geneva (Switzerland); Butler, P.H. [University of Canterbury, Physics and Astronomy, Christchurch (New Zealand)

    2010-09-15

    Spectral CT differs from dual-energy CT by using a conventional X-ray tube and a photon-counting detector. We wished to produce 3D spectroscopic images of mice that distinguished calcium, iodine and barium. We developed a desktop spectral CT, dubbed MARS, based around the Medipix2 photon-counting energy-discriminating detector. The single conventional X-ray tube operated at constant voltage (75 kVp) and constant current (150 {mu}A). We anaesthetised with ketamine six black mice (C57BL/6). We introduced iodinated contrast material and barium sulphate into the vascular system, alimentary tract and respiratory tract as we euthanised them. The mice were preserved in resin and imaged at four detector energy levels from 12 keV to 42 keV to include the K-edges of iodine (33.0 keV) and barium (37.4 keV). Principal component analysis was applied to reconstructed images to identify components with independent energy response, then displayed in 2D and 3D. Iodinated and barium contrast material was spectrally distinct from soft tissue and bone in all six mice. Calcium, iodine and barium were displayed as separate channels on 3D colour images at <55 {mu}m isotropic voxels. Spectral CT distinguishes contrast agents with K-edges only 4 keV apart. Multi-contrast imaging and molecular CT are potential future applications. (orig.)

  16. Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard

    Directory of Open Access Journals (Sweden)

    Clara Rey-Caramés

    2015-10-01

    Full Text Available Implementation of precision viticulture techniques requires the use of emerging sensing technologies to assess the vineyard spatial variability. This work shows the capability of multispectral imagery acquired from a remotely piloted aerial system (RPAS, and the derived spectral indices to assess the vegetative, productive, and berry composition spatial variability within a vineyard (Vitis vinifera L.. Multi-spectral imagery of 17 cm spatial resolution was acquired using a RPAS. Classical vegetation spectral indices and two newly defined normalised indices, NVI1 = (R802 − R531/(R802 + R531 and NVI2 = (R802 − R570/(R802 + R570, were computed. Their spatial distribution and relationships with grapevine vegetative, yield, and berry composition parameters were studied. Most of the spectral indices and field data varied spatially within the vineyard, as showed through the variogram parameters. While the correlations were significant but moderate among the spectral indices and the field variables, the kappa index showed that the spatial pattern of the spectral indices agreed with that of the vegetative variables (0.38–0.70 and mean cluster weight (0.40. These results proved the utility of the multi-spectral imagery acquired from a RPAS to delineate homogeneous zones within the vineyard, allowing the grapegrower to carry out a specific management of each subarea.

  17. Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

    Science.gov (United States)

    Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

    2018-01-15

    In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: Comparison with conventional tube-voltage images.

    Science.gov (United States)

    Sakabe, Daisuke; Funama, Yoshinori; Taguchi, Katsuyuki; Nakaura, Takeshi; Utsunomiya, Daisuke; Oda, Seitaro; Kidoh, Masafumi; Nagayama, Yasunori; Yamashita, Yasuyuki

    2018-05-01

    To investigate the image quality characteristics for virtual monoenergetic images compared with conventional tube-voltage image with dual-layer spectral CT (DLCT). Helical scans were performed using a first-generation DLCT scanner, two different sizes of acrylic cylindrical phantoms, and a Catphan phantom. Three different iodine concentrations were inserted into the phantom center. The single-tube voltage for obtaining virtual monoenergetic images was set to 120 or 140 kVp. Conventional 120- and 140-kVp images and virtual monoenergetic images (40-200-keV images) were reconstructed from slice thicknesses of 1.0 mm. The CT number and image noise were measured for each iodine concentration and water on the 120-kVp images and virtual monoenergetic images. The noise power spectrum (NPS) was also calculated. The iodine CT numbers for the iodinated enhancing materials were similar regardless of phantom size and acquisition method. Compared with the iodine CT numbers of the conventional 120-kVp images, those for the monoenergetic 40-, 50-, and 60-keV images increased by approximately 3.0-, 1.9-, and 1.3-fold, respectively. The image noise values for each virtual monoenergetic image were similar (for example, 24.6 HU at 40 keV and 23.3 HU at 200 keV obtained at 120 kVp and 30-cm phantom size). The NPS curves of the 70-keV and 120-kVp images for a 1.0-mm slice thickness over the entire frequency range were similar. Virtual monoenergetic images represent stable image noise over the entire energy spectrum and improved the contrast-to-noise ratio than conventional tube voltage using the dual-layer spectral detector CT. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  19. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    Directory of Open Access Journals (Sweden)

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  20. Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

    Science.gov (United States)

    Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

    2018-02-01

    The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

  1. Digital image analysis of X-ray television with an image digitizer

    International Nuclear Information System (INIS)

    Mochizuki, Yasuo; Akaike, Hisahiko; Ogawa, Hitoshi; Kyuma, Yukishige

    1995-01-01

    When video signals of X-ray fluoroscopy were transformed from analog-to-digital ones with an image digitizer, their digital characteristic curves, pre-sampling MTF's and digital Wiener spectral could be measured. This method was advant ageous in that it was able to carry out data sampling because the pixel values inputted could be verified on a CRT. The system of image analysis by this method is inexpensive and effective in evaluating the image quality of digital system. Also, it is expected that this method can be used as a tool for learning the measurement techniques and physical characteristics of digital image quality effectively. (author)

  2. Analysis of optical proprieties of the water reservoir Rodolfo Costa e Silva – Itaara, RS, Brazil, with field spectral data and orbital multispectral images

    Directory of Open Access Journals (Sweden)

    Waterloo Pereira Filho

    2007-08-01

    Full Text Available An evaluation of the discrimination of water classes using continuum removal technique applied over spectral data obtained in field and multispectral images classification is presented. The study area was the Rodolfo Costa e Silva water reservoir, located in central region of Rio Grande do Sul (RS State, in Southern region of Brazil. The methodology was based on in situ data collection of: total suspended solids, chlorophyll (a, b and c, water transparency, and bidirectional spectral reflectance. These data were collected in 21 point (samples in May 16, 2006. The continuum removal technique was applied on the spectral data over 4 absorption bands: 400-550nm, 610-640nm, 650-680nm e 580-700nm. The continuum removal parameters analyzed for each absorption band were: depth, area and width. The multispectral images used were CBERS-2/CCD and Landsat 5/TM. The images were acquired in a date nearest to field work and with appropriate weather conditions. These images were corrected by removing atmospheric effects and then classified. According to the results obtained from the continuum removal technique, it was verified that band depth, area and width did not present a good potential to separate different water classes. Digital classification results did not show significant correlations with the limnological parameters collected in field and, therefore, could not be used to characterize spectrally different water classes or compartments. The main problem of establishing relationships between spectral reflectance and water quality parameters was due to the low variability of optical components in the water of Rodolfo Costa e Silva Reservoir. In this case the spectral analyses (considering both techniques were not sensitive to the relative small variations observed in field data.

  3. WE-E-18C-01: Multi-Energy CT: Current Status and Recent Innovations

    International Nuclear Information System (INIS)

    Pelc, N; McCollough, C; Yu, L; Schmidt, T

    2014-01-01

    Conventional computed tomography (CT) uses a single polychromatic x-ray spectrum and energy integrating detectors, and produces images whose contrast depends on the effective attenuation coefficient of the broad spectrum beam. This can introduce errors from beam hardening and does not produce the optimal contrast-to-noise ratio. In addition, multiple materials can have the same effective attenuation coefficient, causing different materials to be indistinguishable in conventional CT images. If transmission measurements at two or more energies are obtained, even with polychromatic beams, more specific information about the object can be obtained. If the object does not contain materials with k-edges in the spectrum, the x-ray attenuation can be well-approximated by a linear combination of two processes (photoelectric absorption and Compton scattering) or, equivalently, two basis materials. For such cases, two spectral measurements suffice, although additional measurements can provide higher precision. If K-edge materials are present, additional spectral measurements can allow these materials to be isolated. Current commercial implementations use varied approaches, including two sources operating a different kVp, one source whose kVp is rapidly switched in a single scan, and a dual layer detector that can provide spectral information in every reading. Processing of the spectral information can be performed in the raw data domain or in the image domain. The process of calculating the amount of the two basis functions implicitly corrects for beam hardening and therefore can lead to improvements in quantitative accuracy. Information can be extracted to provide material specific information beyond that of conventional CT. This additional information has been shown to be important in several clinical applications, and can also lead to more efficient clinical protocols. Recent innovations in x-ray sources, detectors, and systems have made multi-energy CT much more practical

  4. Dual energy spectral CT imaging for the evaluation of small hepatocellular carcinoma microvascular invasion.

    Science.gov (United States)

    Yang, Chuang-Bo; Zhang, Shuang; Jia, Yong-Jun; Yu, Yong; Duan, Hai-Feng; Zhang, Xi-Rong; Ma, Guang-Ming; Ren, Chenglong; Yu, Nan

    2017-10-01

    To study the clinical value of dual-energy spectral CT in the quantitative assessment of microvascular invasion of small hepatocellular carcinoma. This study was approved by our ethics committee. 50 patients with small hepatocellular carcinoma who underwent contrast enhanced spectral CT in arterial phase (AP) and portal venous phase (VP) were enrolled. Tumour CT value and iodine concentration (IC) were measured from spectral CT images. The slope of spectral curve, normalized iodine concentration (NIC, to abdominal aorta) and ratio of IC difference between AP and VP (RIC AP-VP : [RIC AP-VP =(IC AP -IC VP )/IC AP ]) were calculated. Tumours were identified as either with or without microvascular invasion based on pathological results. Measurements were statistically compared using independent samples t test. The receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of tumours microvascular invasion assessment. The 70keV images were used to simulate the results of conventional CT scans for comparison. 56 small hepatocellular carcinomas were detected with 37 lesions (Group A) with microvascular invasion and 19 (Group B) without. There were significant differences in IC, NIC and slope in AP and RIC AP-VP between Group A (2.48±0.70mg/ml, 0.23±0.05, 3.39±1.01 and 0.28±0.16) and Group B (1.65±0.47mg/ml, 0.15±0.05, 2.22±0.64 and 0.03±0.24) (all phepatocellular carcinoma with and without microvascular invasion. Quantitative iodine concentration measurement in spectral CT may be used to provide a new method to improve the evaluation for small hepatocellular carcinoma microvascular invasion. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

    Directory of Open Access Journals (Sweden)

    Xingwei Wang

    2012-01-01

    Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

  6. Multi-Spectral Remote Sensing of Phytoplankton Pigment Absorption Properties in Cyanobacteria Bloom Waters: A Regional Example in the Western Basin of Lake Erie

    Directory of Open Access Journals (Sweden)

    Guoqing Wang

    2017-12-01

    Full Text Available Phytoplankton pigments absorb sunlight for photosynthesis, protect the chloroplast from damage caused by excess light energy, and influence the color of the water. Some pigments act as bio-markers and are important for separation of phytoplankton functional types. Among many efforts that have been made to obtain information on phytoplankton pigments from bio-optical properties, Gaussian curves decomposed from phytoplankton absorption spectrum have been used to represent the light absorption of different pigments. We incorporated the Gaussian scheme into a semi-analytical model and obtained the Gaussian curves from remote sensing reflectance. In this study, a series of sensitivity tests were conducted to explore the potential of obtaining the Gaussian curves from multi-spectral satellite remote sensing. Results showed that the Gaussian curves can be retrieved with 35% or less mean unbiased absolute percentage differences from MEdium Resolution Imaging Spectrometer (MERIS and Moderate Resolution Imaging Spectroradiometer (MODIS-like sensors. Further, using Lake Erie as an example, the spatial distribution of chlorophyll a and phycocyanin concentrations were obtained from the Gaussian curves and used as metrics for the spatial extent of an intense cyanobacterial bloom occurred in Lake Erie in 2014. The seasonal variations of Gaussian absorption properties in 2011 were further obtained from MERIS imagery. This study shows that it is feasible to obtain Gaussian curves from multi-spectral satellite remote sensing data, and the obtained chlorophyll a and phycocyanin concentrations from these Gaussian peak heights demonstrated potential application to monitor harmful algal blooms (HABs and identification of phytoplankton groups from satellite ocean color remote sensing semi-analytically.

  7. [A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

    Science.gov (United States)

    Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

    2015-07-01

    Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

  8. Multi-spectrometer calibration transfer based on independent component analysis.

    Science.gov (United States)

    Liu, Yan; Xu, Hao; Xia, Zhenzhen; Gong, Zhiyong

    2018-02-26

    Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.

  9. WE-FG-207B-03: Multi-Energy CT Reconstruction with Spatial Spectral Nonlocal Means Regularization

    Energy Technology Data Exchange (ETDEWEB)

    Li, B [University of Texas Southwestern Medical Center, Dallas, TX (United States); Southern Medical University, Guangzhou, Guangdong (China); Shen, C; Ouyang, L; Yang, M; Jiang, S; Jia, X [University of Texas Southwestern Medical Center, Dallas, TX (United States); Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

    2016-06-15

    Purpose: Multi-energy computed tomography (MECT) is an emerging application in medical imaging due to its ability of material differentiation and potential for molecular imaging. In MECT, image correlations at different spatial and channels exist. It is desirable to incorporate these correlations in reconstruction to improve image quality. For this purpose, this study proposes a MECT reconstruction technique that employes spatial spectral non-local means (ssNLM) regularization. Methods: We consider a kVp-switching scanning method in which source energy is rapidly switched during data acquisition. For each energy channel, this yields projection data acquired at a number of angles, whereas projection angles among channels are different. We formulate the reconstruction task as an optimziation problem. A least square term enfores data fidelity. A ssNLM term is used as regularization to encourage similarities among image patches at different spatial locations and channels. When comparing image patches at different channels, intensity difference were corrected by a transformation estimated via histogram equalization during the reconstruction process. Results: We tested our method in a simulation study with a NCAT phantom and an experimental study with a Gammex phantom. For comparison purpose, we also performed reconstructions using conjugate-gradient least square (CGLS) method and conventional NLM method that only considers spatial correlation in an image. ssNLM is able to better suppress streak artifacts. The streaks are along different projection directions in images at different channels. ssNLM discourages this dissimilarity and hence removes them. True image structures are preserved in this process. Measurements in regions of interests yield 1.1 to 3.2 and 1.5 to 1.8 times higher contrast to noise ratio than the NLM approach. Improvements over CGLS is even more profound due to lack of regularization in the CGLS method and hence amplified noise. Conclusion: The

  10. Multi-Label Classification Based on Low Rank Representation for Image Annotation

    Directory of Open Access Journals (Sweden)

    Qiaoyu Tan

    2017-01-01

    Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

  11. An Improved Algorithm Based on Minimum Spanning Tree for Multi-scale Segmentation of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LI Hui

    2015-07-01

    Full Text Available As the basis of object-oriented information extraction from remote sensing imagery,image segmentation using multiple image features,exploiting spatial context information, and by a multi-scale approach are currently the research focuses. Using an optimization approach of the graph theory, an improved multi-scale image segmentation method is proposed. In this method, the image is applied with a coherent enhancement anisotropic diffusion filter followed by a minimum spanning tree segmentation approach, and the resulting segments are merged with reference to a minimum heterogeneity criterion.The heterogeneity criterion is defined as a function of the spectral characteristics and shape parameters of segments. The purpose of the merging step is to realize the multi-scale image segmentation. Tested on two images, the proposed method was visually and quantitatively compared with the segmentation method employed in the eCognition software. The results show that the proposed method is effective and outperforms the latter on areas with subtle spectral differences.

  12. Theme section: Multi-dimensional modelling, analysis and visualization

    DEFF Research Database (Denmark)

    Guilbert, Éric; Coltekin, Arzu; Antón Castro, Francesc/François

    2016-01-01

    (Biljecki et al., 2015) as well as the temporal, but also the scale dimension (Van Oosterom and Stoter, 2010) or, as mentioned by(Lu et al., 2016), multi-spectral and multi-sensor data. Such a view provides an organisation of multidimensional data around these different axes and it is time to explore each...

  13. Near-infrared spectral imaging Michelson interferometer for astronomical applications

    Science.gov (United States)

    Wells, C. W.; Potter, A. E.; Morgan, T. H.

    1980-01-01

    The design and operation of an imaging Michelson interferometer-spectrometer used for near-infrared (0.8 micron to 2.5 microns) spectral imaging are reported. The system employs a rapid scan interferometer modified for stable low resolution (250/cm) performance and a 42 element PbS linear detector array. A microcomputer system is described which provides data acquisition, coadding, and Fourier transformation for near real-time presentation of the spectra of all 42 scene elements. The electronic and mechanical designs are discussed and telescope performance data presented.

  14. Preliminary PCA/TT Results on MRO CRISM Multispectral Images

    Science.gov (United States)

    Klassen, David R.; Smith, M. D.

    2010-10-01

    Mars Reconnaissance Orbiter arrived at Mars in March 2006 and by September had achieved its science-phase orbit with the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) beginning its visible to near-infrared (VIS/NIR) spectral imaging shortly thereafter. One goal of CRISM is to fill in the spatial gaps between the various targeted observations, eventually mapping the entire surface. Due to the large volume of data this would create, the instrument works in a reduced spectral sampling mode creating "multispectral” images. From these data we can create image cubes using 64 wavelengths from 0.410 to 3.923 µm. We present here our analysis of these multispectral mode data products using Principal Components Analysis (PCA) and Target Transformation (TT) [1]. Previous work with ground-based images [2-5] has shown that over an entire visible hemisphere, there are only three to four meaningful components using 32-105 wavelengths over 1.5-4.1 µm the first two are consistent over all temporal scales. The TT retrieved spectral endmembers show nearly the same level of consistency [5]. The preliminary work on the CRISM images cubes implies similar results; three to four significant principal components that are fairly consistent over time. These components are then used in TT to find spectral endmembers which can be used to characterize the surface reflectance for future use in radiative transfer cloud optical depth retrievals. We present here the PCA/TT results comparing the principal components and recovered endmembers from six reconstructed CRISM multi-spectral image cubes. References: [1] Bandfield, J. L., et al. (2000) JGR, 105, 9573. [2] Klassen, D. R. and Bell III, J. F. (2001) BAAS 33, 1069. [3] Klassen, D. R. and Bell III, J. F. (2003) BAAS, 35, 936. [4] Klassen, D. R., Wark, T. J., Cugliotta, C. G. (2005) BAAS, 37, 693. [5] Klassen, D. R. (2009) Icarus, 204, 32.

  15. Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

    Science.gov (United States)

    Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

    2015-04-01

    Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty

  16. The multi-spectral line-polarization MSE system on Alcator C-Mod

    Energy Technology Data Exchange (ETDEWEB)

    Mumgaard, R. T., E-mail: mumgaard@psfc.mit.edu; Khoury, M. [Plasma Science and Fusion Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Scott, S. D. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08540 (United States)

    2016-11-15

    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  17. The multi-spectral line-polarization MSE system on Alcator C-Mod

    International Nuclear Information System (INIS)

    Mumgaard, R. T.; Khoury, M.; Scott, S. D.

    2016-01-01

    A multi-spectral line-polarization motional Stark effect (MSE-MSLP) diagnostic has been developed for the Alcator C-Mod tokamak wherein the Stokes vector is measured in multiple wavelength bands simultaneously on the same sightline to enable better polarized background subtraction. A ten-sightline, four wavelength MSE-MSLP detector system was designed, constructed, and qualified. This system consists of a high-throughput polychromator for each sightline designed to provide large étendue and precise spectral filtering in a cost-effective manner. Each polychromator utilizes four narrow bandpass interference filters and four custom large diameter avalanche photodiode detectors. Two filters collect light to the red and blue of the MSE emission spectrum while the remaining two filters collect the beam pi and sigma emission generated at the same viewing volume. The filter wavelengths are temperature tuned using custom ovens in an automated manner. All system functions are remote controllable and the system can be easily retrofitted to existing single-wavelength line-polarization MSE systems.

  18. Biological Response to the Dynamic Spectral-Polarized Underwater Light Field

    Science.gov (United States)

    2010-01-01

    Texas coastal fish skin preparations with the HyperSpectral Imager mounted on a stereomicroscope in Norway in April (Dierssen). g) Camouflage...on fish skin preparations. B) Matlab image of skin preparation showing the boxed area used in the spectral analysis. C) Median reflectance

  19. Radiometric and spectral calibrations of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) using principle component analysis

    Science.gov (United States)

    Tian, Jialin; Smith, William L.; Gazarik, Michael J.

    2008-10-01

    The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw GIFTS interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. The radiometric calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. The absolute radiometric performance of the instrument is affected by several factors including the FPA off-axis effect, detector/readout electronics induced nonlinearity distortions, and fore-optics offsets. The GIFTS-EDU, being the very first imaging spectrometer to use ultra-high speed electronics to readout its large area format focal plane array detectors, operating at wavelengths as large as 15 microns, possessed non-linearity's not easily removable in the initial calibration process. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts remaining after the initial radiometric calibration process, thus, further enhance the absolute calibration accuracy. This method is

  20. Passive microrheology of soft materials with atomic force microscopy: A wavelet-based spectral analysis

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-Torres, C.; Streppa, L. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); Arneodo, A.; Argoul, F. [CNRS, UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d' Italie, Université de Lyon, 69007 Lyon (France); CNRS, UMR5798, Laboratoire Ondes et Matière d' Aquitaine, Université de Bordeaux, 351 Cours de la Libération, 33405 Talence (France); Argoul, P. [Université Paris-Est, Ecole des Ponts ParisTech, SDOA, MAST, IFSTTAR, 14-20 Bd Newton, Cité Descartes, 77420 Champs sur Marne (France)

    2016-01-18

    Compared to active microrheology where a known force or modulation is periodically imposed to a soft material, passive microrheology relies on the spectral analysis of the spontaneous motion of tracers inherent or external to the material. Passive microrheology studies of soft or living materials with atomic force microscopy (AFM) cantilever tips are rather rare because, in the spectral densities, the rheological response of the materials is hardly distinguishable from other sources of random or periodic perturbations. To circumvent this difficulty, we propose here a wavelet-based decomposition of AFM cantilever tip fluctuations and we show that when applying this multi-scale method to soft polymer layers and to living myoblasts, the structural damping exponents of these soft materials can be retrieved.

  1. Spatial and spectral analysis of corneal epithelium injury using hyperspectral images

    Science.gov (United States)

    Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

    2017-12-01

    Eye assessment is essential in preventing blindness. Currently, the existing methods to assess corneal epithelium injury are complex and require expert knowledge. Hence, we have introduced a non-invasive technique using hyperspectral imaging (HSI) and an image analysis algorithm of corneal epithelium injury. Three groups of images were compared and analyzed, namely healthy eyes, injured eyes, and injured eyes with stain. Dimensionality reduction using principal component analysis (PCA) was applied to reduce massive data and redundancies. The first 10 principal components (PCs) were selected for further processing. The mean vector of 10 PCs with 45 pairs of all combinations was computed and sent to two classifiers. A quadratic Bayes normal classifier (QDC) and a support vector classifier (SVC) were used in this study to discriminate the eleven eyes into three groups. As a result, the combined classifier of QDC and SVC showed optimal performance with 2D PCA features (2DPCA-QDSVC) and was utilized to classify normal and abnormal tissues, using color image segmentation. The result was compared with human segmentation. The outcome showed that the proposed algorithm produced extremely promising results to assist the clinician in quantifying a cornea injury.

  2. Evaluation of the robustness of estimating five components from a skin spectral image

    Science.gov (United States)

    Akaho, Rina; Hirose, Misa; Tsumura, Norimichi

    2018-04-01

    We evaluated the robustness of a method used to estimate five components (i.e., melanin, oxy-hemoglobin, deoxy-hemoglobin, shading, and surface reflectance) from the spectral reflectance of skin at five wavelengths against noise and a change in epidermis thickness. We also estimated the five components from recorded images of age spots and circles under the eyes using the method. We found that noise in the image must be no more 0.1% to accurately estimate the five components and that the thickness of the epidermis affects the estimation. We acquired the distribution of major causes for age spots and circles under the eyes by applying the method to recorded spectral images.

  3. Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

    Science.gov (United States)

    Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

    2011-01-01

    The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

  4. Multi-layer composite structure covered polytetrafluoroethylene for visible-infrared-radar spectral Compatibility

    Science.gov (United States)

    Qi, Dong; Cheng, Yongzhi; Wang, Xian; Wang, Fang; Li, Bowen; Gong, Rongzhou

    2017-12-01

    In this paper, a polytetrafluoroethylene (PTFE) top-covered multi-layer composite structure PTFE/H s/(Ge/ZnS)3 (H s represents the surface layer ZnS with various thicknesses) for spectral compatibility is proposed and investigated theoretically and experimentally. A substantial decline of glossiness from over 200 Gs to 74.2 Gs could be realized, due to high roughness and interface reflection of the 800 nm PTFE protection layer. In addition, similar to the structure of H s/(Ge/ZnS)3, the designed structure with a certain color exhibits ultra-low emissivity of average 0.196 at 8-14 µm and highly transparent performance of 96.45% in the radar frequency range of 2-18 GHz. Our design will provide an important reference for the practical applications of the spectral compatible multilayer films.

  5. The added value of contrast enhanced spectral mammography in identification of multiplicity of suspicious lesions in dense breast

    Directory of Open Access Journals (Sweden)

    Amr Farouk Ibrahim Moustafa

    2018-03-01

    Full Text Available Objective: To evaluate the additive value of Contrast Enhanced Spectral Mammography (CESM in the preoperative assessment of malignant lesions in dense breast parenchyma regarding multiplicity. Material and methods: The study included 160 women having heterogeneous dense breast parenchyma (ACR c and d with suspicious lesions identified on sono mammography examination. All patients performed contrast enhanced spectral mammography to confirm or exclude lesion multiplicity. The number of lesions was calculated in the contrast high energy subtraction images with the reference standard being histopathological analysis. Results: Adding CESM to sono-mammography the accuracy in identifying multiple malignant lesion increased from 81.8% accuracy of sono-mammography up to 100% accuracy after adding CESM. Conclusion: Contrast enhanced spectral mammogram showed an added value in the preoperative assessment of breast masses increasing the accuracy of detection of lesions and multiplicity (multifocality and multi-centricity. Keywords: Breast cancer, Contrast enhanced spectral mammogram

  6. A MULTI-CORE PARALLEL MOSAIC ALORITHM FOR MULTI-VIEW UAV IMAGES

    Directory of Open Access Journals (Sweden)

    X. Pan

    2017-09-01

    Full Text Available As the spread of the error and accumulation often lead to distortion or failure of image mosaic during the multi-view UAV (Unmanned Aerial Vehicle images stitching. In this paper, to solve the problem we propose a mosaic strategy to construct a mosaic ring and multi-level grouping parallel acceleration as an auxiliary. First, the input images will be divided into several groups, each group in the ring way to stitch. Then, use SIFT for matching, RANSAC to remove the wrong matching points. And then, calculate the perspective transformation matrix. Finally weaken the error by using the adjustment equation. All these steps run between different groups at the same time. By using real UAV images, the experiment results show that this method can effectively reduce the influence of accumulative error, improve the precision of mosaic and reduce the mosaic time by 60 %. The proposed method can be used as one of the effective ways to minimize the accumulative error.

  7. Spectral characterization in deep UV of an improved imaging KDP acousto-optic tunable filter

    International Nuclear Information System (INIS)

    Gupta, Neelam; Voloshinov, Vitaly

    2014-01-01

    Recently, we developed a number of high quality noncollinear acousto-optic tunable filter (AOTF) cells in different birefringent materials with UV imaging capability. Cells based on a single crystal of KDP (potassium dihydrophosphate) had the best transmission efficiency and the optical throughput needed to acquire high quality spectral images at wavelengths above 220 nm. One of the main limitations of these imaging filters was their small angular aperture in air, limited to about 1.0°. In this paper, we describe an improved imaging KDP AOTF operating from the deep UV to the visible region of the spectrum. The linear and angular apertures of the new filter are 10 × 10 mm 2 and 1.8°, respectively. The spectral tuning range is 205–430 nm with a 60 cm −1 spectral resolution. We describe the filter and present experimental results on imaging using both a broadband source and a number of light emitting diodes (LEDs) in the UV, and include the measured spectra of these LEDs obtained with a collinear SiO 2 filter-based spectrometer operating above 255 nm. (paper)

  8. Multi-modality molecular imaging: pre-clinical laboratory configuration

    Science.gov (United States)

    Wu, Yanjun; Wellen, Jeremy W.; Sarkar, Susanta K.

    2006-02-01

    In recent years, the prevalence of in vivo molecular imaging applications has rapidly increased. Here we report on the construction of a multi-modality imaging facility in a pharmaceutical setting that is expected to further advance existing capabilities for in vivo imaging of drug distribution and the interaction with their target. The imaging instrumentation in our facility includes a microPET scanner, a four wavelength time-domain optical imaging scanner, a 9.4T/30cm MRI scanner and a SPECT/X-ray CT scanner. An electronics shop and a computer room dedicated to image analysis are additional features of the facility. The layout of the facility was designed with a central animal preparation room surrounded by separate laboratory rooms for each of the major imaging modalities to accommodate the work-flow of simultaneous in vivo imaging experiments. This report will focus on the design of and anticipated applications for our microPET and optical imaging laboratory spaces. Additionally, we will discuss efforts to maximize the daily throughput of animal scans through development of efficient experimental work-flows and the use of multiple animals in a single scanning session.

  9. Texture analysis applied to second harmonic generation image data for disease classification and development of a multi-view second harmonic generation imaging platform

    Science.gov (United States)

    Wen, Lianggong

    Many diseases, e.g. ovarian cancer, breast cancer and pulmonary fibrosis, are commonly associated with drastic alterations in surrounding connective tissue, and changes in the extracellular matrix (ECM) are associated with the vast majority of cellular processes in disease progression and carcinogenesis: cell differentiation, proliferation, biosynthetic ability, polarity, and motility. We use second harmonic generation (SHG) microscopy for imaging the ECM because it is a non-invasive, non-linear laser scanning technique with high sensitivity and specificity for visualizing fibrillar collagen. In this thesis, we are interested in developing imaging techniques to understand how the ECM, especially the collagen architecture, is remodeled in diseases. To quantitate remodeling, we implement a 3D texture analysis to delineate the collagen fibrillar morphology observed in SHG microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"---frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations---is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective mages, we then perform classification between normal and high grade malignant ovarian tissues classification based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features. Further, we describe the development of a multi-view 3D SHG imaging platform. Unlike fluorescence microscopy, SHG excites

  10. EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

    Science.gov (United States)

    Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

    2015-01-01

    Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

  11. REMOTELY SENSEDC IMAGE COMPRESSION BASED ON WAVELET TRANSFORM

    Directory of Open Access Journals (Sweden)

    Heung K. Lee

    1996-06-01

    Full Text Available In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR and classification capability.

  12. A System for Compressive Spectral and Polarization Imaging at Short Wave Infrared (SWIR) Wavelengths

    Science.gov (United States)

    2017-10-18

    UV -­‐ VIS -­‐IR   60mm   Apo   Macro  lens   Jenoptik-­‐Inc   $5,817.36   IR... VIS /NIR Compressive Spectral Imager”, Proceedings of IEEE International Conference on Image Processing (ICIP ’15), Quebec City, Canada, (September...imaging   system   will   lead   to   a   wide-­‐band   VIS -­‐NIR-­‐SWIR   compressive  spectral  and  polarimetric

  13. Improving Spectral Image Classification through Band-Ratio Optimization and Pixel Clustering

    Science.gov (United States)

    O'Neill, M.; Burt, C.; McKenna, I.; Kimblin, C.

    2017-12-01

    The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of DigitalGlobe's WorldView-3 (WV3) to detect and map UNE signatures. WV3 is the current state-of-the-art, commercial, multispectral imaging satellite; however, it has relatively limited spectral and spatial resolutions. These limitations impede image classifiers from detecting targets that are spatially small and lack distinct spectral features. In order to improve classification results, we developed custom algorithms to reduce false positive rates while increasing true positive rates via a band-ratio optimization and pixel clustering front-end. The clusters resulting from these algorithms were processed with standard spectral image classifiers such as Mixture-Tuned Matched Filter (MTMF) and Adaptive Coherence Estimator (ACE). WV3 and AVIRIS data of Cuprite, Nevada, were used as a validation data set. These data were processed with a standard classification approach using MTMF and ACE algorithms. They were also processed using the custom front-end prior to the standard approach. A comparison of the results shows that the custom front-end significantly increases the true positive rate and decreases the false positive rate.This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy. DOE/NV/25946-3283.

  14. Extraction of urban vegetation with Pleiades multiangular images

    Science.gov (United States)

    Lefebvre, Antoine; Nabucet, Jean; Corpetti, Thomas; Courty, Nicolas; Hubert-Moy, Laurence

    2016-10-01

    Vegetation is essential in urban environments since it provides significant services in terms of health, heat, property value, ecology ... As part of the European Union Biodiversity Strategy Plan for 2020, the protection and development of green-infrastructures is strengthened in urban areas. In order to evaluate and monitor the quality of the green infra-structures, this article investigates contributions of Pléiades multi-angular images to extract and characterize low and high urban vegetation. From such images one can extract both spectral and elevation information from optical images. Our method is composed of 3 main steps : (1) the computation of a normalized Digital Surface Model from the multi-angular images ; (2) Extraction of spectral and contextual features ; (3) a classification of vegetation classes (tree and grass) performed with a random forest classifier. Results performed in the city of Rennes in France show the ability of multi-angular images to extract DEM in urban area despite building height. It also highlights its importance and its complementarity with contextual information to extract urban vegetation.

  15. Hurricane coastal flood analysis using multispectral spectral images

    Science.gov (United States)

    Ogashawara, I.; Ferreira, C.; Curtarelli, M. P.

    2013-12-01

    Flooding is one of the main hazards caused by extreme events such as hurricanes and tropical storms. Therefore, flood maps are a crucial tool to support policy makers, environmental managers and other government agencies for emergency management, disaster recovery and risk reduction planning. However traditional flood mapping methods rely heavily on the interpolation of hydrodynamic models results, and most recently, the extensive collection of field data. These methods are time-consuming, labor intensive, and costly. Efficient and fast response alternative methods should be developed in order to improve flood mapping, and remote sensing has been proved as a valuable tool for this application. Our goal in this paper is to introduce a novel technique based on spectral analysis in order to aggregate knowledge and information to map coastal flood areas. For this purpose we used the Normalized Diference Water Index (NDWI) which was derived from two the medium resolution LANDSAT/TM 5 surface reflectance product from the LANDSAT climate data record (CDR). This product is generated from specialized software called Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). We used the surface reflectance products acquired before and after the passage of Hurricane Ike for East Texas in September of 2008. We used as end member a classification of estimated flooded area based on the United States Geological Survey (USGS) mobile storm surge network that was deployed for Hurricane Ike. We used a dataset which consisted of 59 water levels recording stations. The estimated flooded area was delineated interpolating the maximum surge in each location using a spline with barriers method with high tension and a 30 meter Digital Elevation Model (DEM) from the National Elevation Dataset (NED). Our results showed that, in the flooded area, the NDWI values decreased after the hurricane landfall on average from 0.38 to 0.18 and the median value decreased from 0.36 to 0.2. However

  16. Polarimetric analysis of a CdZnTe spectro-imager under multi-pixel irradiation conditions

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, M. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Curado da Silva, R.M., E-mail: rui.silva@coimbra.lip.pt [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Maia, J.M. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Beira-Interior, Covilhã (Portugal); Simões, N. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Marques, J. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Centro de Astrofísica, Universidade do Porto, Porto (Portugal); Pereira, L.; Trindade, A.M.F. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); and others

    2016-12-21

    So far, polarimetry in high-energy astrophysics has been insufficiently explored due to the complexity of the required detection, electronic and signal processing systems. However, its importance is today largely recognized by the astrophysical community, therefore the next generation of high-energy space instruments will certainly provide polarimetric observations, contemporaneously with spectroscopy and imaging. We have been participating in high-energy observatory proposals submitted to ESA Cosmic Vision calls, such as GRI (Gamma-Ray Imager), DUAL and ASTROGAM, where the main instrument was a spectro-imager with polarimetric capabilities. More recently, the H2020 AHEAD project was launched with the objective to promote more coherent and mature future high-energy space mission proposals. In this context of high-energy proposal development, we have tested a CdZnTe detection plane prototype polarimeter under a partially polarized gamma-ray beam generated from an aluminum target irradiated by a {sup 22}Na (511 keV) radioactive source. The polarized beam cross section was 1 cm{sup 2}, allowing the irradiation of a wide multi-pixelated area where all the pixels operate simultaneously as a scatterer and as an absorber. The methods implemented to analyze such multi-pixel irradiation are similar to those required to analyze a spectro-imager polarimeter operating in space, since celestial source photons should irradiate its full pixilated area. Correction methods to mitigate systematic errors inherent to CdZnTe and to the experimental conditions were also implemented. The polarization level (~40%) and the polarization angle (precision of ±5° up to ±9°) obtained under multi-pixel irradiation conditions are presented and compared with simulated data.

  17. Multi-Source Image Analysis.

    Science.gov (United States)

    1979-12-01

    These collections were taken to show the advantages made available to the inter- preter. In a military operation, however, often little or no in- situ ...The large body of water labeled "W" on each image represents the Agua Hedionda lagoon. East of the lagoon the area is primarily agricultural with a...power plant located in the southeast corner of the image. West of the Agua Hedionda lagoon is Carlsbad, California. Damp ground is labelled "Dg" on the

  18. 3D Convolutional Neural Networks for Crop Classification with Multi-Temporal Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Shunping Ji

    2018-01-01

    Full Text Available This study describes a novel three-dimensional (3D convolutional neural networks (CNN based method that automatically classifies crops from spatio-temporal remote sensing images. First, 3D kernel is designed according to the structure of multi-spectral multi-temporal remote sensing data. Secondly, the 3D CNN framework with fine-tuned parameters is designed for training 3D crop samples and learning spatio-temporal discriminative representations, with the full crop growth cycles being preserved. In addition, we introduce an active learning strategy to the CNN model to improve labelling accuracy up to a required threshold with the most efficiency. Finally, experiments are carried out to test the advantage of the 3D CNN, in comparison to the two-dimensional (2D CNN and other conventional methods. Our experiments show that the 3D CNN is especially suitable in characterizing the dynamics of crop growth and outperformed the other mainstream methods.

  19. Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging

    Science.gov (United States)

    Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.

    2015-01-01

    Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288

  20. Basic Functional Analysis Puzzles of Spectral Flow

    DEFF Research Database (Denmark)

    Booss-Bavnbek, Bernhelm

    2011-01-01

    We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles.......We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles....