WorldWideScience

Sample records for information-efficient spectral imaging

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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)

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. [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.

  13. 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....

  14. 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.

  15. 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.

  16. 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.

  17. [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.

  18. Constellation modulation - an approach to increase spectral efficiency.

    Science.gov (United States)

    Dash, Soumya Sunder; Pythoud, Frederic; Hillerkuss, David; Baeuerle, Benedikt; Josten, Arne; Leuchtmann, Pascal; Leuthold, Juerg

    2017-07-10

    Constellation modulation (CM) is introduced as a new degree of freedom to increase the spectral efficiency and to further approach the Shannon limit. Constellation modulation is the art of encoding information not only in the symbols within a constellation but also by encoding information by selecting a constellation from a set of constellations that are switched from time to time. The set of constellations is not limited to sets of partitions from a given constellation but can e.g., be obtained from an existing constellation by applying geometrical transformations such as rotations, translations, scaling, or even more abstract transformations. The architecture of the transmitter and the receiver allows for constellation modulation to be used on top of existing modulations with little penalties on the bit-error ratio (BER) or on the required signal-to-noise ratio (SNR). The spectral bandwidth used by this modulation scheme is identical to the original modulation. Simulations demonstrate a particular advantage of the scheme for low SNR situations. So, for instance, it is demonstrated by simulation that a spectral efficiency increases by up to 33% and 20% can be obtained at a BER of 10 -3 and 2×10 -2 for a regular BPSK modulation format, respectively. Applying constellation modulation, we derive a most power efficient 4D-CM-BPSK modulation format that provides a spectral efficiency of 0.7 bit/s/Hz for an SNR of 0.2 dB at a BER of 2 × 10 -2 .

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. Evolving spectral transformations for multitemporal information extraction using evolutionary computation

    Science.gov (United States)

    Momm, Henrique; Easson, Greg

    2011-01-01

    Remote sensing plays an important role in assessing temporal changes in land features. The challenge often resides in the conversion of large quantities of raw data into actionable information in a timely and cost-effective fashion. To address this issue, research was undertaken to develop an innovative methodology integrating biologically-inspired algorithms with standard image classification algorithms to improve information extraction from multitemporal imagery. Genetic programming was used as the optimization engine to evolve feature-specific candidate solutions in the form of nonlinear mathematical expressions of the image spectral channels (spectral indices). The temporal generalization capability of the proposed system was evaluated by addressing the task of building rooftop identification from a set of images acquired at different dates in a cross-validation approach. The proposed system generates robust solutions (kappa values > 0.75 for stage 1 and > 0.4 for stage 2) despite the statistical differences between the scenes caused by land use and land cover changes coupled with variable environmental conditions, and the lack of radiometric calibration between images. Based on our results, the use of nonlinear spectral indices enhanced the spectral differences between features improving the clustering capability of standard classifiers and providing an alternative solution for multitemporal information extraction.

  7. Camouflage target detection via hyperspectral imaging plus information divergence measurement

    Science.gov (United States)

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

    2016-01-01

    Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

    Science.gov (United States)

    Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

    2018-01-01

    Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

  14. Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

    Science.gov (United States)

    Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.

    2015-10-01

    The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

  15. [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.

  16. 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.

  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. 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...

  19. 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.

  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. 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.

  2. 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.

  3. Classification of Hyperspectral Images by SVM Using a Composite Kernel by Employing Spectral, Spatial and Hierarchical Structure Information

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2018-03-01

    Full Text Available In this paper, we introduce a novel classification framework for hyperspectral images (HSIs by jointly employing spectral, spatial, and hierarchical structure information. In this framework, the three types of information are integrated into the SVM classifier in a way of multiple kernels. Specifically, the spectral kernel is constructed through each pixel’s vector value in the original HSI, and the spatial kernel is modeled by using the extended morphological profile method due to its simplicity and effectiveness. To accurately characterize hierarchical structure features, the techniques of Fish-Markov selector (FMS, marker-based hierarchical segmentation (MHSEG and algebraic multigrid (AMG are combined. First, the FMS algorithm is used on the original HSI for feature selection to produce its spectral subset. Then, the multigrid structure of this subset is constructed using the AMG method. Subsequently, the MHSEG algorithm is exploited to obtain a hierarchy consist of a series of segmentation maps. Finally, the hierarchical structure information is represented by using these segmentation maps. The main contributions of this work is to present an effective composite kernel for HSI classification by utilizing spatial structure information in multiple scales. Experiments were conducted on two hyperspectral remote sensing images to validate that the proposed framework can achieve better classification results than several popular kernel-based classification methods in terms of both qualitative and quantitative analysis. Specifically, the proposed classification framework can achieve 13.46–15.61% in average higher than the standard SVM classifier under different training sets in the terms of overall accuracy.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. 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.

  10. 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.)

  11. 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.

  12. Study on Efficiency of Fusion Techniques for IKONOS Images

    International Nuclear Information System (INIS)

    Liu, Yanmei; Yu, Haiyang; Guijun, Yang; Nie, Chenwei; Yang, Xiaodong; Ren, Dong

    2014-01-01

    Many image fusion techniques have been proposed to achieve optimal resolution in the spatial and spectral domains. Six different merging methods were listed in this paper and the efficiency of fusion techniques was assessed in qualitative and quantitative aspect. Both local and global evaluation parameters were used in the spectral quality and a Laplace filter method was used in spatial quality assessment. By simulation, the spectral quality of the images merged by Brovery was demonstrated to be the worst. In contrast, GS and PCA algorithms, especially the Pansharpening provided higher spectral quality than the standard Brovery, wavelet and CN methods. In spatial quality assessment, the CN method represented best compared with that of others, while the Brovery algorithm was worst. The wavelet parameters that performed best achieved acceptable spectral and spatial quality compared to the others

  13. Classification and Recognition of Tomb Information in Hyperspectral Image

    Science.gov (United States)

    Gu, M.; Lyu, S.; Hou, M.; Ma, S.; Gao, Z.; Bai, S.; Zhou, P.

    2018-04-01

    There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  14. 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.

  15. 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.

  16. Development of Fluorescence Spectral Imaging for Location of Uranium Deposited on Surfaces

    International Nuclear Information System (INIS)

    Monts, D.L.; Wang, G.; Su, Y.; Jang, P.R.; Waggoner, Ch.A.

    2009-01-01

    Since the 1980's, depleted uranium (DU) has been the primary material used by the US military in armor-piercing rounds. Domestic firing ranges that have been used for DU munitions training purposes are located around the country and have varying extents of contamination by other types of projectiles. A project is underway to develop a set of sensors to locate expended DU rounds and to process soil and debris to recover the material. In the environment, metallic DU readily oxidizes to form uranium compounds that contain the uranyl (UO 2 +2 ) moiety. For more than a hundred and fifty years, it has been known that when illuminated with ultraviolet (UV) light, uranyl compounds exhibit characteristic fluorescence in the visible region (450 - 650 nm). We report our efforts to develop a transportable, quantitative Fluorescence Spectral Imaging (FSI) system to locate and quantify uranyl compounds dispersed in soils and on other surfaces on domestic firing ranges; this system can also be utilized to monitor excavation of DU munitions and separation of uranyl compounds from soils. FSI images are acquired by illuminating a surface with a UV light and using a narrow band pass filter on a camera, recording an image of the resulting fluorescence. FSI images provide both spatial and spectral information. The FSI system is described and its performance characterized in the field and also by using field samples. The development and characterization of an improved transportable FSI system is presented. The applicability of this system for detection of uranium compounds deposited on surfaces for Decontaminating and Decommissioning (D and D) activities is discussed. We have successfully demonstrated in situ a first-generation, transportable Fluorescence Spectral Imaging (FSI) system for locating uranyl compounds dispersed in soils and on other surfaces of a domestic firing range. FSI images provide both spatial and spectral information. FSI images are acquired by illuminating a

  17. 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

  18. 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

  19. 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.

  20. 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,

  1. 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.

  2. CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE

    Directory of Open Access Journals (Sweden)

    M. Gu

    2018-04-01

    Full Text Available There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  3. 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).

  4. 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

  5. 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.

  6. Spectral Efficiency Analysis for Multicarrier Based 4G Systems

    DEFF Research Database (Denmark)

    Silva, Nuno; Rahman, Muhammad Imadur; Frederiksen, Flemming Bjerge

    2006-01-01

    In this paper, a spectral efficiency definition is proposed. Spectral efficiency for multicarrier based multiaccess techniques, such as OFDMA, MC-CDMA and OFDMA-CDM, is analyzed. Simulations for different indoor and outdoor scenarios are carried out. Based on the simulations, we have discussed ho...

  7. Spectral Efficiency of OCDMA Systems With Coherent Pulsed Sources

    Science.gov (United States)

    Rochette, Martin; Rusch, Leslie A.

    2005-03-01

    We present a model to evaluate the upper limit of the spectral efficiency of optical code-division multiple-access (OCDMA) systems with coherent sources. Phase-encoded and direct-sequence OCDMA systems are evaluated using this model. The results show that a spectral efficiency of 2.24x10^-2 b/s.Hz can be achieved with a maximum bit error rate of 10^-10 in these systems of the number of users. This result demonstrates that the maximum spectral efficiency of OCDMA systems with coherent sources is at least a factor of 5 higher than OCDMA systems with incoherent sources.

  8. 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

  9. 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.

  10. 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.

  11. 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. 

  12. 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.

  13. 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

  14. Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

    Science.gov (United States)

    Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon

    2001-01-01

    A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

  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. 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

  18. 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.

  19. COFFEE - Coherent Optical System Field Trial for Spectral Efficiency Enhancement

    DEFF Research Database (Denmark)

    Imran, Muhammad; Fresi, Francesco; Rommel, Simon

    2016-01-01

    The scope, aims, and contributions of the COFFEE project for spectral efficiency enhancement and market exposure are presented.......The scope, aims, and contributions of the COFFEE project for spectral efficiency enhancement and market exposure are presented....

  20. 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

  1. 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.

  2. 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)

  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. 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.

  5. 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

  6. 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.

  7. Spectrally efficient switched transmit diversity for spectrum sharing systems

    KAUST Repository

    Bouida, Zied; Abdallah, Mohamed M.; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

    2011-01-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link. The proposed bandwidth efficient scheme (BES) uses the scan and wait (SWC) combining technique where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In our scheme, the modulation constellation size and the used transmit branch are determined to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. Selected numerical examples show that the BES scheme increases the capacity of the secondary link when compared to an existing switching efficient scheme (SES). This spectral efficiency comes at the expense of an increased average number of switched branches and thus an increased average delay. © 2011 IEEE.

  8. Spectrally efficient switched transmit diversity for spectrum sharing systems

    KAUST Repository

    Bouida, Zied

    2011-09-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link. The proposed bandwidth efficient scheme (BES) uses the scan and wait (SWC) combining technique where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In our scheme, the modulation constellation size and the used transmit branch are determined to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. Selected numerical examples show that the BES scheme increases the capacity of the secondary link when compared to an existing switching efficient scheme (SES). This spectral efficiency comes at the expense of an increased average number of switched branches and thus an increased average delay. © 2011 IEEE.

  9. Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems

    Directory of Open Access Journals (Sweden)

    Feilong Li

    2017-01-01

    Full Text Available The usable satellite spectrum is becoming scarce due to static spectrum allocation policies. Cognitive radio approaches have already demonstrated their potential towards spectral efficiency for providing more spectrum access opportunities to secondary user (SU with sufficient protection to licensed primary user (PU. Hence, recent scientific literature has been focused on the tradeoff between spectrum reuse and PU protection within narrowband spectrum sensing (SS in terrestrial wireless sensing networks. However, those narrowband SS techniques investigated in the context of terrestrial CR may not be applicable for detecting wideband satellite signals. In this paper, we mainly investigate the problem of joint designing sensing time and hard fusion scheme to maximize SU spectral efficiency in the scenario of low earth orbit (LEO mobile satellite services based on wideband spectrum sensing. Compressed detection model is established to prove that there indeed exists one optimal sensing time achieving maximal spectral efficiency. Moreover, we propose novel wideband cooperative spectrum sensing (CSS framework where each SU reporting duration can be utilized for its following SU sensing. The sensing performance benefits from the novel CSS framework because the equivalent sensing time is extended by making full use of reporting slot. Furthermore, in respect of time-varying channel, the spatiotemporal CSS (ST-CSS is presented to attain space and time diversity gain simultaneously under hard decision fusion rule. Computer simulations show that the optimal sensing settings algorithm of joint optimization of sensing time, hard fusion rule and scheduling strategy achieves significant improvement in spectral efficiency. Additionally, the novel ST-CSS scheme performs much higher spectral efficiency than that of general CSS framework.

  10. 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....

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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

  16. Payload Configurations for Efficient Image Acquisition - Indian Perspective

    Science.gov (United States)

    Samudraiah, D. R. M.; Saxena, M.; Paul, S.; Narayanababu, P.; Kuriakose, S.; Kiran Kumar, A. S.

    2014-11-01

    The world is increasingly depending on remotely sensed data. The data is regularly used for monitoring the earth resources and also for solving problems of the world like disasters, climate degradation, etc. Remotely sensed data has changed our perspective of understanding of other planets. With innovative approaches in data utilization, the demands of remote sensing data are ever increasing. More and more research and developments are taken up for data utilization. The satellite resources are scarce and each launch costs heavily. Each launch is also associated with large effort for developing the hardware prior to launch. It is also associated with large number of software elements and mathematical algorithms post-launch. The proliferation of low-earth and geostationary satellites has led to increased scarcity in the available orbital slots for the newer satellites. Indian Space Research Organization has always tried to maximize the utility of satellites. Multiple sensors are flown on each satellite. In each of the satellites, sensors are designed to cater to various spectral bands/frequencies, spatial and temporal resolutions. Bhaskara-1, the first experimental satellite started with 2 bands in electro-optical spectrum and 3 bands in microwave spectrum. The recent Resourcesat-2 incorporates very efficient image acquisition approach with multi-resolution (3 types of spatial resolution) multi-band (4 spectral bands) electro-optical sensors (LISS-4, LISS-3* and AWiFS). The system has been designed to provide data globally with various data reception stations and onboard data storage capabilities. Oceansat-2 satellite has unique sensor combination with 8 band electro-optical high sensitive ocean colour monitor (catering to ocean and land) along with Ku band scatterometer to acquire information on ocean winds. INSAT- 3D launched recently provides high resolution 6 band image data in visible, short-wave, mid-wave and long-wave infrared spectrum. It also has 19 band

  17. 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'...

  18. 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'...

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Analysis of the Spectral Efficiency of Frequency-Encoded OCDMA Systems With Incoherent Sources

    Science.gov (United States)

    Rochette, Martin; Ayotte, Simon; Rusch, Leslie A.

    2005-04-01

    This paper presents the spectral efficiency of frequency-encoded (FE) optical code-division multiple-access (OCDMA) systems with incoherent sources. The spectral efficiency of five code families compatible with FE-OCDMA is calculated as a function of the number of users. Analytical equations valid in the limiting case of Gaussian noise are also developed for the bit-error rate and the spectral efficiency. Among the code families considered, the modified quadratic congruence code leads to the maximum achievable spectral efficiency.

  5. 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.

  6. Advanced astigmatism-corrected tandem Wadsworth mounting for small-scale spectral broadband imaging spectrometer.

    Science.gov (United States)

    Lei, Yu; Lin, Guan-yu

    2013-01-01

    Tandem gratings of double-dispersion mount make it possible to design an imaging spectrometer for the weak light observation with high spatial resolution, high spectral resolution, and high optical transmission efficiency. The traditional tandem Wadsworth mounting is originally designed to match the coaxial telescope and large-scale imaging spectrometer. When it is used to connect the off-axis telescope such as off-axis parabolic mirror, it presents lower imaging quality than to connect the coaxial telescope. It may also introduce interference among the detector and the optical elements as it is applied to the short focal length and small-scale spectrometer in a close volume by satellite. An advanced tandem Wadsworth mounting has been investigated to deal with the situation. The Wadsworth astigmatism-corrected mounting condition for which is expressed as the distance between the second concave grating and the imaging plane is calculated. Then the optimum arrangement for the first plane grating and the second concave grating, which make the anterior Wadsworth condition fulfilling each wavelength, is analyzed by the geometric and first order differential calculation. These two arrangements comprise the advanced Wadsworth mounting condition. The spectral resolution has also been calculated by these conditions. An example designed by the optimum theory proves that the advanced tandem Wadsworth mounting performs excellently in spectral broadband.

  7. Maximizing the spectral and energy efficiency of ARQ with a fixed outage probability

    KAUST Repository

    Hadjtaieb, Amir

    2015-10-05

    This paper studies the spectral and energy efficiency of automatic repeat request (ARQ) in Nakagami-m block-fading channels. The source encodes each packet into L similar sequences and transmits them to the destination in the L subsequent time slots. The destination combines the L sequences using maximal ratio combining and tries to decode the information. In case of decoding failure, the destination feeds back a negative acknowledgment and then the source sends the same L sequences to the destination. This process continues until successful decoding occurs at the destination with no limit on the number of retransmissions. We consider two optimization problems. In the first problem, we maximize the spectral efficiency of the system with respect to the rate for a fixed power. In the second problem, we maximize the energy efficiency with respect to the transmitted power for a fixed rate. © 2015 IEEE.

  8. A Method of Particle Swarm Optimized SVM Hyper-spectral Remote Sensing Image Classification

    International Nuclear Information System (INIS)

    Liu, Q J; Jing, L H; Wang, L M; Lin, Q Z

    2014-01-01

    Support Vector Machine (SVM) has been proved to be suitable for classification of remote sensing image and proposed to overcome the Hughes phenomenon. Hyper-spectral sensors are intrinsically designed to discriminate among a broad range of land cover classes which may lead to high computational time in SVM mutil-class algorithms. Model selection for SVM involving kernel and the margin parameter values selection which is usually time-consuming, impacts training efficiency of SVM model and final classification accuracies of SVM hyper-spectral remote sensing image classifier greatly. Firstly, based on combinatorial optimization theory and cross-validation method, particle swarm algorithm is introduced to the optimal selection of SVM (PSSVM) kernel parameter σ and margin parameter C to improve the modelling efficiency of SVM model. Then an experiment of classifying AVIRIS in India Pine site of USA was performed for evaluating the novel PSSVM, as well as traditional SVM classifier with general Grid-Search cross-validation method (GSSVM). And then, evaluation indexes including SVM model training time, classification Overall Accuracy (OA) and Kappa index of both PSSVM and GSSVM are all analyzed quantitatively. It is demonstrated that OA of PSSVM on test samples and whole image are 85% and 82%, the differences with that of GSSVM are both within 0.08% respectively. And Kappa indexes reach 0.82 and 0.77, the differences with that of GSSVM are both within 0.001. While the modelling time of PSSVM can be only 1/10 of that of GSSVM, and the modelling. Therefore, PSSVM is an fast and accurate algorithm for hyper-spectral image classification and is superior to GSSVM

  9. 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)

  10. 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.

  11. Land Cover Classification Using Integrated Spectral, Temporal, and Spatial Features Derived from Remotely Sensed Images

    Directory of Open Access Journals (Sweden)

    Yongguang Zhai

    2018-03-01

    Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.

  12. Modified fuzzy c-means applied to a Bragg grating-based spectral imager for material clustering

    Science.gov (United States)

    Rodríguez, Aida; Nieves, Juan Luis; Valero, Eva; Garrote, Estíbaliz; Hernández-Andrés, Javier; Romero, Javier

    2012-01-01

    We have modified the Fuzzy C-Means algorithm for an application related to segmentation of hyperspectral images. Classical fuzzy c-means algorithm uses Euclidean distance for computing sample membership to each cluster. We have introduced a different distance metric, Spectral Similarity Value (SSV), in order to have a more convenient similarity measure for reflectance information. SSV distance metric considers both magnitude difference (by the use of Euclidean distance) and spectral shape (by the use of Pearson correlation). Experiments confirmed that the introduction of this metric improves the quality of hyperspectral image segmentation, creating spectrally more dense clusters and increasing the number of correctly classified pixels.

  13. Spectral efficiency in crosstalk-impaired multi-core fiber links

    Science.gov (United States)

    Luís, Ruben S.; Puttnam, Benjamin J.; Rademacher, Georg; Klaus, Werner; Agrell, Erik; Awaji, Yoshinari; Wada, Naoya

    2018-02-01

    We review the latest advances on ultra-high throughput transmission using crosstalk-limited single-mode multicore fibers and compare these with the theoretical spectral efficiency of such systems. We relate the crosstalkimposed spectral efficiency limits with fiber parameters, such as core diameter, core pitch, and trench design. Furthermore, we investigate the potential of techniques such as direction interleaving and high-order MIMO to improve the throughput or reach of these systems when using various modulation formats.

  14. 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.

  15. 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.

  16. 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.

  17. Spectral efficiency enhancement with interference cancellation for wireless relay network

    DEFF Research Database (Denmark)

    Yomo, Hiroyuki; De Carvalho, Elisabeth

    The introduction of relaying into wireless communication system for coverage enhancement can cause severe decrease of spectral efficiency due to the requirement on extra radio resource. In this paper, we propose a method to increase spectral efficiency in such a wireless relay network by employing...... an interference cancellation technique. We focus on a typical scenario of relaying in a cellular system, where a mobile station (MS) requires the help of a relay station (RS) to communicate with the base station (BS). In such a case, interference cancellation can be used to achieve a small reuse distance...... of identical radio resource. We analyze a simple scenario with BS, single RS, and 2 MSs, and show that the proposed method has significant potential to enhance spectral efficiency in wireless relay networks....

  18. 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.

  19. 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

  20. Radiometric Correction of Close-Range Spectral Image Blocks Captured Using an Unmanned Aerial Vehicle with a Radiometric Block Adjustment

    Directory of Open Access Journals (Sweden)

    Eija Honkavaara

    2018-02-01

    Full Text Available Unmanned airborne vehicles (UAV equipped with novel, miniaturized, 2D frame format hyper- and multispectral cameras make it possible to conduct remote sensing measurements cost-efficiently, with greater accuracy and detail. In the mapping process, the area of interest is covered by multiple, overlapping, small-format 2D images, which provide redundant information about the object. Radiometric correction of spectral image data is important for eliminating any external disturbance from the captured data. Corrections should include sensor, atmosphere and view/illumination geometry (bidirectional reflectance distribution function—BRDF related disturbances. An additional complication is that UAV remote sensing campaigns are often carried out under difficult conditions, with varying illumination conditions and cloudiness. We have developed a global optimization approach for the radiometric correction of UAV image blocks, a radiometric block adjustment. The objective of this study was to implement and assess a combined adjustment approach, including comprehensive consideration of weighting of various observations. An empirical study was carried out using imagery captured using a hyperspectral 2D frame format camera of winter wheat crops. The dataset included four separate flights captured during a 2.5 h time period under sunny weather conditions. As outputs, we calculated orthophoto mosaics using the most nadir images and sampled multiple-view hyperspectral spectra for vegetation sample points utilizing multiple images in the dataset. The method provided an automated tool for radiometric correction, compensating for efficiently radiometric disturbances in the images. The global homogeneity factor improved from 12–16% to 4–6% with the corrections, and a reduction in disturbances could be observed in the spectra of the object points sampled from multiple overlapping images. Residuals in the grey and white reflectance panels were less than 5% of the

  1. 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

  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. Validation of Spectral Unmixing Results from Informed Non-Negative Matrix Factorization (INMF) of Hyperspectral Imagery

    Science.gov (United States)

    Wright, L.; Coddington, O.; Pilewskie, P.

    2017-12-01

    Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. We describe the development of an Informed Non-Negative Matrix Factorization (INMF) spectral unmixing method to exploit this spectral information and separate atmospheric and surface signals based on their physical sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO), with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric and surface conditions. These include atmospheres with varying aerosol optical thicknesses and cloud cover. HICO images also provide a range of surface conditions including deep ocean regions, with only minor contributions from the ocean surfaces; and more complex shallow coastal regions with contributions from the seafloor or suspended sediments. We provide extensive comparison of INMF decomposition results against independent measurements of physical properties. These include comparison against traditional model-based retrievals of water-leaving, aerosol, and molecular scattering radiances and other satellite products, such as aerosol optical thickness from

  4. 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.

  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. 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...

  7. 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.

  8. 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

  9. 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.

  10. 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 ...

  11. Apparatus and method using a holographic optical element for converting a spectral distribution to image points

    Science.gov (United States)

    McGill, Matthew J. (Inventor); Scott, Vibart S. (Inventor); Marzouk, Marzouk (Inventor)

    2001-01-01

    A holographic optical element transforms a spectral distribution of light to image points. The element comprises areas, each of which acts as a separate lens to image the light incident in its area to an image point. Each area contains the recorded hologram of a point source object. The image points can be made to lie in a line in the same focal plane so as to align with a linear array detector. A version of the element has been developed that has concentric equal areas to match the circular fringe pattern of a Fabry-Perot interferometer. The element has high transmission efficiency, and when coupled with high quantum efficiency solid state detectors, provides an efficient photon-collecting detection system. The element may be used as part of the detection system in a direct detection Doppler lidar system or multiple field of view lidar system.

  12. 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 ...

  13. An efficient spectral crystal plasticity solver for GPU architectures

    Science.gov (United States)

    Malahe, Michael

    2018-03-01

    We present a spectral crystal plasticity (CP) solver for graphics processing unit (GPU) architectures that achieves a tenfold increase in efficiency over prior GPU solvers. The approach makes use of a database containing a spectral decomposition of CP simulations performed using a conventional iterative solver over a parameter space of crystal orientations and applied velocity gradients. The key improvements in efficiency come from reducing global memory transactions, exposing more instruction-level parallelism, reducing integer instructions and performing fast range reductions on trigonometric arguments. The scheme also makes more efficient use of memory than prior work, allowing for larger problems to be solved on a single GPU. We illustrate these improvements with a simulation of 390 million crystal grains on a consumer-grade GPU, which executes at a rate of 2.72 s per strain step.

  14. 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

  15. A spectrally efficient detect-and-forward scheme with two-tier adaptive cooperation

    KAUST Repository

    Benjillali, Mustapha

    2011-09-01

    We propose a simple relay-based adaptive cooperation scheme to improve the spectral efficiency of "Detect-and-Forward" (DetF) half-duplex relaying in fading channels. In a new common framework, we show that the proposed scheme offers considerable gainsin terms of the achievable information ratescompared to conventional DetF relaying schemes for both orthogonal and non-orthogonal source/relay transmissions. The analysis leads on to a general adaptive cooperation strategy based on the maximization of information rates at the destination which needs to observe only the average signal-to-noise ratios of the links. © 2006 IEEE.

  16. 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.

  17. A compact bio-inspired visible/NIR imager for image-guided surgery (Conference Presentation)

    Science.gov (United States)

    Gao, Shengkui; Garcia, Missael; Edmiston, Chris; York, Timothy; Marinov, Radoslav; Mondal, Suman B.; Zhu, Nan; Sudlow, Gail P.; Akers, Walter J.; Margenthaler, Julie A.; Liang, Rongguang; Pepino, Marta; Achilefu, Samuel; Gruev, Viktor

    2016-03-01

    Inspired by the visual system of the morpho butterfly, we have designed, fabricated, tested and clinically translated an ultra-sensitive, light weight and compact imaging sensor capable of simultaneously capturing near infrared (NIR) and visible spectrum information. The visual system of the morpho butterfly combines photosensitive cells with spectral filters at the receptor level. The spectral filters are realized by alternating layers of high and low dielectric constant, such as air and cytoplasm. We have successfully mimicked this concept by integrating pixelated spectral filters, realized by alternating silicon dioxide and silicon nitrate layers, with an array of CCD detectors. There are four different types of pixelated spectral filters in the imaging plane: red, green, blue and NIR. The high optical density (OD) of all spectral filters (OD>4) allow for efficient rejections of photons from unwanted bands. The single imaging chip weighs 20 grams with form factor of 5mm by 5mm. The imaging camera is integrated with a goggle display system. A tumor targeted agent, LS301, is used to identify all spontaneous tumors in a transgenic PyMT murine model of breast cancer. The imaging system achieved sensitivity of 98% and selectivity of 95%. We also used our imaging sensor to locate sentinel lymph nodes (SLNs) in patients with breast cancer using indocyanine green tracer. The surgeon was able to identify 100% of SLNs when using our bio-inspired imaging system, compared to 93% when using information from the lymphotropic dye and 96% when using information from the radioactive tracer.

  18. 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

  19. 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

  20. Simulative Investigation on Spectral Efficiency of Unipolar Codes based OCDMA System using Importance Sampling Technique

    Science.gov (United States)

    Farhat, A.; Menif, M.; Rezig, H.

    2013-09-01

    This paper analyses the spectral efficiency of Optical Code Division Multiple Access (OCDMA) system using Importance Sampling (IS) technique. We consider three configurations of OCDMA system namely Direct Sequence (DS), Spectral Amplitude Coding (SAC) and Fast Frequency Hopping (FFH) that exploits the Fiber Bragg Gratings (FBG) based encoder/decoder. We evaluate the spectral efficiency of the considered system by taking into consideration the effect of different families of unipolar codes for both coherent and incoherent sources. The results show that the spectral efficiency of OCDMA system with coherent source is higher than the incoherent case. We demonstrate also that DS-OCDMA outperforms both others in terms of spectral efficiency in all conditions.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Fluorescence spectral imaging as a tool for locating uranium deposited on surfaces - 16089

    International Nuclear Information System (INIS)

    Monts, David L.; Wang, Guangjun; Su, Yi; Jang, Ping-Rey; Waggoner, Charles A.

    2009-01-01

    In the environment, metallic uranium readily oxidizes to form uranium compounds that contain the uranyl (UO 2 +2 ) moiety. For more than a hundred and fifty years, it has been known that when illuminated with ultraviolet (UV) light, uranyl compounds exhibit characteristic fluorescence in the visible region (450-650 nm). We report our efforts to develop a transportable, quantitative Fluorescence Spectral Imaging (FSI) system as a tool for locating and quantifying uranyl compounds dispersed in soils and on other surfaces. A project is underway to develop a set of sensors to locate expended depleted uranium (DU) rounds and to process soil and debris to recover the material from domestic firing ranges. The FSI system can also be utilized to monitor excavation of DU munitions and separation of uranyl compounds from soils. FSI images are acquired by illuminating a surface with a UV light and using a narrow band pass filter on a camera, recording an image of the resulting fluorescence. The FSI image provides both spatial and spectral information. The FSI system is described and its performance characterized using field samples. (authors)

  6. 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

  7. 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

  8. A portable confocal hyperspectral microscope without any scan or tube lens and its application in fluorescence and Raman spectral imaging

    Science.gov (United States)

    Li, Jingwei; Cai, Fuhong; Dong, Yongjiang; Zhu, Zhenfeng; Sun, Xianhe; Zhang, Hequn; He, Sailing

    2017-06-01

    In this study, a portable confocal hyperspectral microscope is developed. In traditional confocal laser scanning microscopes, scan lens and tube lens are utilized to achieve a conjugate relationship between the galvanometer and the back focal plane of the objective, in order to achieve a better resolution. However, these lenses make it difficult to scale down the volume of the system. In our portable confocal hyperspectral microscope (PCHM), the objective is placed directly next to the galvomirror. Thus, scan lens and tube lens are not included in our system and the size of this system is greatly reduced. Furthermore, the resolution is also acceptable in many biomedical and food-safety applications. Through reducing the optical length of the system, the signal detection efficiency is enhanced. This is conducive to realizing both the fluorescence and Raman hyperspectral imaging. With a multimode fiber as a pinhole, an improved image contrast is also achieved. Fluorescent spectral images for HeLa cells/fingers and Raman spectral images of kumquat pericarp are present. The spectral resolution and spatial resolutions are about 0.4 nm and 2.19 μm, respectively. These results demonstrate that this portable hyperspectral microscope can be used in in-vivo fluorescence imaging and in situ Raman spectral imaging.

  9. 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.

  10. 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.

  11. 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

  12. [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.

  13. 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.

  14. Very High Spectral Resolution Imaging Spectroscopy: the Fluorescence Explorer (FLEX) Mission

    Science.gov (United States)

    Moreno, Jose F.; Goulas, Yves; Huth, Andreas; Middleton, Elizabeth; Miglietta, Franco; Mohammed, Gina; Nedbal, Ladislav; Rascher, Uwe; Verhoef, Wouter; Drusch, Matthias

    2016-01-01

    The Fluorescence Explorer (FLEX) mission has been recently selected as the 8th Earth Explorer by the European Space Agency (ESA). It will be the first mission specifically designed to measure from space vegetation fluorescence emission, by making use of very high spectral resolution imaging spectroscopy techniques. Vegetation fluorescence is the best proxy to actual vegetation photosynthesis which can be measurable from space, allowing an improved quantification of vegetation carbon assimilation and vegetation stress conditions, thus having key relevance for global mapping of ecosystems dynamics and aspects related with agricultural production and food security. The FLEX mission carries the FLORIS spectrometer, with a spectral resolution in the range of 0.3 nm, and is designed to fly in tandem with Copernicus Sentinel-3, in order to provide all the necessary spectral / angular information to disentangle emitted fluorescence from reflected radiance, and to allow proper interpretation of the observed fluorescence spatial and temporal dynamics.

  15. Spectrally efficient polymer optical fiber transmission

    Science.gov (United States)

    Randel, Sebastian; Bunge, Christian-Alexander

    2011-01-01

    The step-index polymer optical fiber (SI-POF) is an attractive transmission medium for high speed communication links in automotive infotainment networks, in industrial automation, and in home networks. Growing demands for quality of service, e.g., for IPTV distribution in homes and for Ethernet based industrial control networks will necessitate Gigabit speeds in the near future. We present an overview on recent advances in the design of spectrally efficient and robust Gigabit-over-SI-POF transmission systems.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

    Directory of Open Access Journals (Sweden)

    Nelson Eduardo Diaz

    2015-09-01

    Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed.  In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

  1. 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.

  2. 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.

  3. 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....

  4. 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...

  5. 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.

  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. 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)

  8. Rare-earth doped transparent ceramics for spectral filtering and quantum information processing

    Science.gov (United States)

    Kunkel, Nathalie; Ferrier, Alban; Thiel, Charles W.; Ramírez, Mariola O.; Bausá, Luisa E.; Cone, Rufus L.; Ikesue, Akio; Goldner, Philippe

    2015-09-01

    Homogeneous linewidths below 10 kHz are reported for the first time in high-quality Eu3+ doped Y 2O3 transparent ceramics. This result is obtained on the 7F0→5D0 transition in Eu3+ doped Y 2O3 ceramics and corresponds to an improvement of nearly one order of magnitude compared to previously reported values in transparent ceramics. Furthermore, we observed spectral hole lifetimes of ˜15 min that are long enough to enable efficient optical pumping of the nuclear hyperfine levels. Additionally, different Eu3+ concentrations (up to 1.0%) were studied, resulting in an increase of up to a factor of three in the peak absorption coefficient. These results suggest that transparent ceramics can be useful in applications where narrow and deep spectral holes can be burned into highly absorbing lines, such as quantum information processing and spectral filtering.

  9. Computational information geometry for image and signal processing

    CERN Document Server

    Critchley, Frank; Dodson, Christopher

    2017-01-01

    This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals. It provides introductory chapters to help those new to information geometry and applies the theory to several applications. This area has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition and the desire to process and interpret large databases of digital information. The book addresses both the transfer of methodology to practitioners involved in database analysis and in its efficient computational implementation.

  10. Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

    Directory of Open Access Journals (Sweden)

    Veronika Kopačková

    2017-09-01

    Full Text Available Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS, near-infrared (NIR, shortwave infrared (SWIR and longwave infrared (LWIR spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data and Airborne Hyperspectral Scanner (AHS, LWIR image data. Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved.

  11. 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.

  12. Cross Correlation versus Normalized Mutual Information on Image Registration

    Science.gov (United States)

    Tan, Bin; Tilton, James C.; Lin, Guoqing

    2016-01-01

    This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

  13. 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.

  14. Efficient Hybrid-Spectral Model for Fully Nonlinear Numerical Wave Tank

    DEFF Research Database (Denmark)

    Christiansen, Torben; Bingham, Harry B.; Engsig-Karup, Allan Peter

    2013-01-01

    A new hybrid-spectral solution strategy is proposed for the simulation of the fully nonlinear free surface equations based on potential flow theory. A Fourier collocation method is adopted horisontally for the discretization of the free surface equations. This is combined with a modal Chebyshev Tau...... method in the vertical for the discretization of the Laplace equation in the fluid domain, which yields a sparse and spectrally accurate Dirichletto-Neumann operator. The Laplace problem is solved with an efficient Defect Correction method preconditioned with a spectral discretization of the linearised...... wave problem, ensuring fast convergence and optimal scaling with the problem size. Preliminary results for very nonlinear waves show expected convergence rates and a clear advantage of using spectral schemes....

  15. 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.

  16. 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.

  17. 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.

  18. 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

  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. Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization

    Energy Technology Data Exchange (ETDEWEB)

    Shiga, Motoki, E-mail: shiga_m@gifu-u.ac.jp [Department of Electrical, Electronic and Computer Engineering, Gifu University, 1-1, Yanagido, Gifu 501-1193 (Japan); Tatsumi, Kazuyoshi; Muto, Shunsuke [Advanced Measurement Technology Center, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan); Tsuda, Koji [Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa 277-8561 (Japan); Center for Materials Research by Information Integration, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba 305-0047 (Japan); Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology, 2-4-7 Aomi Koto-ku, Tokyo 135-0064 (Japan); Yamamoto, Yuta [High-Voltage Electron Microscope Laboratory, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan); Mori, Toshiyuki [Environment and Energy Materials Division, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044 (Japan); Tanji, Takayoshi [Division of Materials Research, Institute of Materials and Systems for Sustainability, Nagoya University, Chikusa-ku, Nagoya 464-8603 (Japan)

    2016-11-15

    Advances in scanning transmission electron microscopy (STEM) techniques have enabled us to automatically obtain electron energy-loss (EELS)/energy-dispersive X-ray (EDX) spectral datasets from a specified region of interest (ROI) at an arbitrary step width, called spectral imaging (SI). Instead of manually identifying the potential constituent chemical components from the ROI and determining the chemical state of each spectral component from the SI data stored in a huge three-dimensional matrix, it is more effective and efficient to use a statistical approach for the automatic resolution and extraction of the underlying chemical components. Among many different statistical approaches, we adopt a non-negative matrix factorization (NMF) technique, mainly because of the natural assumption of non-negative values in the spectra and cardinalities of chemical components, which are always positive in actual data. This paper proposes a new NMF model with two penalty terms: (i) an automatic relevance determination (ARD) prior, which optimizes the number of components, and (ii) a soft orthogonal constraint, which clearly resolves each spectrum component. For the factorization, we further propose a fast optimization algorithm based on hierarchical alternating least-squares. Numerical experiments using both phantom and real STEM-EDX/EELS SI datasets demonstrate that the ARD prior successfully identifies the correct number of physically meaningful components. The soft orthogonal constraint is also shown to be effective, particularly for STEM-EELS SI data, where neither the spatial nor spectral entries in the matrices are sparse. - Highlights: • Automatic resolution of chemical components from spectral imaging is considered. • We propose a new non-negative matrix factorization with two new penalties. • The first penalty is sparseness to choose the number of components from data. • Experimental results with real data demonstrate effectiveness of our method.

  1. Rare-earth doped transparent ceramics for spectral filtering and quantum information processing

    Energy Technology Data Exchange (ETDEWEB)

    Kunkel, Nathalie, E-mail: nathalie.kunkel@chimie-paristech.fr; Goldner, Philippe, E-mail: philippe.goldner@chimie-paristech.fr [PSL Research University, Chimie ParisTech–CNRS, Institut de Recherche de Chimie Paris, 11 rue Pierre et Marie Curie, 75005 Paris (France); Ferrier, Alban [PSL Research University, Chimie ParisTech–CNRS, Institut de Recherche de Chimie Paris, 11 rue Pierre et Marie Curie, 75005 Paris (France); Sorbonnes Universités, UPMC Univ Paris 06, 75005 Paris (France); Thiel, Charles W.; Cone, Rufus L. [Department of Physics, Montana State University, Bozeman, Montana 59717 (United States); Ramírez, Mariola O.; Bausá, Luisa E. [Departamento Física de Materiales and Instituto Nicolás Cabrera, Universidad Autónoma de Madrid, 28049 Madrid (Spain); Ikesue, Akio [World Laboratory, Mutsuno, Atsuta-ku, Nagoya 456-0023 (Japan)

    2015-09-01

    Homogeneous linewidths below 10 kHz are reported for the first time in high-quality Eu{sup 3+} doped Y {sub 2}O{sub 3} transparent ceramics. This result is obtained on the {sup 7}F{sub 0}→{sup 5}D{sub 0} transition in Eu{sup 3+} doped Y {sub 2}O{sub 3} ceramics and corresponds to an improvement of nearly one order of magnitude compared to previously reported values in transparent ceramics. Furthermore, we observed spectral hole lifetimes of ∼15 min that are long enough to enable efficient optical pumping of the nuclear hyperfine levels. Additionally, different Eu{sup 3+} concentrations (up to 1.0%) were studied, resulting in an increase of up to a factor of three in the peak absorption coefficient. These results suggest that transparent ceramics can be useful in applications where narrow and deep spectral holes can be burned into highly absorbing lines, such as quantum information processing and spectral filtering.

  2. An efficient quantum algorithm for spectral estimation

    Science.gov (United States)

    Steffens, Adrian; Rebentrost, Patrick; Marvian, Iman; Eisert, Jens; Lloyd, Seth

    2017-03-01

    We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially damped sinusoids. Our algorithm provides a quantum speedup in a natural regime where the sampling rate is much higher than the number of sinusoid components. Along the way, we develop techniques that are expected to be useful for other quantum algorithms as well—consecutive phase estimations to efficiently make products of asymmetric low rank matrices classically accessible and an alternative method to efficiently exponentiate non-Hermitian matrices. Our algorithm features an efficient quantum-classical division of labor: the time-critical steps are implemented in quantum superposition, while an interjacent step, requiring much fewer parameters, can operate classically. We show that frequencies and damping factors can be obtained in time logarithmic in the number of sampling points, exponentially faster than known classical algorithms.

  3. Spatial compression algorithm for the analysis of very large multivariate images

    Science.gov (United States)

    Keenan, Michael R [Albuquerque, NM

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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)

  10. Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Qingshan Liu

    2017-12-01

    Full Text Available This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM network to automatically learn the spectral-spatial features from hyperspectral images (HSIs. In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to address it. Meanwhile, inspired from the widely used convolutional neural network (CNN, a convolution operator across the spatial domain is incorporated into the network to extract the spatial feature. In addition, to sufficiently capture the spectral information, a bidirectional recurrent connection is proposed. In the classification phase, the learned features are concatenated into a vector and fed to a Softmax classifier via a fully-connected operator. To validate the effectiveness of the proposed Bi-CLSTM framework, we compare it with six state-of-the-art methods, including the popular 3D-CNN model, on three widely used HSIs (i.e., Indian Pines, Pavia University, and Kennedy Space Center. The obtained results show that Bi-CLSTM can improve the classification performance by almost 1.5 % as compared to 3D-CNN.

  11. 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

    covering a wider area. This, although with very tight limitations, can be seen as an approach to t est the ability of 'up-scaling' the information contained in the classified images. 3. A third step consists of correlating the classified values with relevant petrophysical properties for each of these phases. This may help to relate petrophysical properties based on the mineralogy obtained from the classified hyper-spectral images. 4. The final step is the analysis of the connectivity of the different phases in two dimensions. The work flow briefly described above can of course be extended to the third dimension if scans and/or additional data at suitable positions exist. We present here an attempt to characterize different clay facies utilizing their reflection features in an underground setting. The first characterization is solely based on the 'visual' information obtained from classified hyper-spectral images and their comparison with lab measurements and geological maps. The second part extends this characterization to a more rigorous geostatistical analysis

  12. Spectrally and Energy Efficient OFDM (SEE-OFDM) for Intensity Modulated Optical Wireless Systems

    OpenAIRE

    Lam, Emily; Wilson, Sarah Kate; Elgala, Hany; Little, Thomas D. C.

    2015-01-01

    Spectrally and energy efficient orthogonal frequency division multiplexing (SEE-OFDM) is an optical OFDM technique based on combining multiple asymmetrically clipped optical OFDM (ACO-OFDM) signals into one OFDM signal. By summing different components together, SEE-OFDM can achieve the same spectral efficiency as DC-biased optical OFDM (DCO-OFDM) without an energy-inefficient DC-bias. This paper introduces multiple methods for decoding a SEE-OFDM symbol and shows that an iterative decoder wit...

  13. 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%.

  14. Combining total internal reflection sum frequency spectroscopy spectral imaging and confocal fluorescence microscopy.

    Science.gov (United States)

    Allgeyer, Edward S; Sterling, Sarah M; Gunewardene, Mudalige S; Hess, Samuel T; Neivandt, David J; Mason, Michael D

    2015-01-27

    Understanding surface and interfacial lateral organization in material and biological systems is critical in nearly every field of science. The continued development of tools and techniques viable for elucidation of interfacial and surface information is therefore necessary to address new questions and further current investigations. Sum frequency spectroscopy (SFS) is a label-free, nonlinear optical technique with inherent surface specificity that can yield critical organizational information on interfacial species. Unfortunately, SFS provides no spatial information on a surface; small scale heterogeneities that may exist are averaged over the large areas typically probed. Over the past decade, this has begun to be addressed with the advent of SFS microscopy. Here we detail the construction and function of a total internal reflection (TIR) SFS spectral and confocal fluorescence imaging microscope directly amenable to surface investigations. This instrument combines, for the first time, sample scanning TIR-SFS imaging with confocal fluorescence microscopy.

  15. Spectral and energy efficiency analysis of uplink heterogeneous networks with small-cells on edge

    KAUST Repository

    Shakir, Muhammad Zeeshan

    2014-12-01

    This paper presents a tractable mathematical framework to analyze the spectral and energy efficiency of an operator initiated deployment of the small-cells (e.g., femtocells) where the small-cell base stations are deliberately positioned around the edge of the macrocell. The considered deployment facilitates the cell-edge mobile users in terms of their coverage, spectral, and energy efficiency and is referred to as cell-on-edge (COE) configuration. The reduction in energy consumption is achieved by considering fast power control where the mobile users transmit with adaptive power to compensate the path loss, shadowing and fading. In particular, we develop a moment generating function (MGF) based approach to derive analytical bounds on the area spectral efficiency and exact expressions for the energy efficiency of the mobile users in the considered COE configuration over generalized-K fading channels. Besides the COE configuration, the derived bounds are also shown to be useful in evaluating the performance of random small-cell deployments, e.g., uniformly distributed small-cells. Simulation results are presented to demonstrate the improvements in spectral and energy efficiency of the COE configuration with respect to macro-only networks and other unplanned deployment strategies. © 2014 Elsevier B.V. All rights reserved.

  16. 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...

  17. 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.

  18. 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...

  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. 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)

  1. Fine-tuning of the spectral collection efficiency in multilayer junctions

    International Nuclear Information System (INIS)

    Fernandes, M.; Fantoni, A.; Louro, P.; Lavareda, G.; Carvalho, N.; Schwarz, R.; Vieira, M.

    2006-01-01

    a-SiC:H/a-Si:H p-i-n/p-i-n tandem cells with different i-layer thickness have been produced by PECVD and tested for a proper fine-tuning of the spectral collection efficiency. The tandem structure takes advantage on the radiation wavelength selectivity due to the different light penetration depth inside the a-Si:H and a-SiC:H absorbers. The thickness and the absorption coefficient of the front p-i-n cell were optimized for blue collection and red transmittance and the thickness of the back one adjusted to achieve full absorption in the green and high collection in the red spectral ranges. Preliminary results show that device optimization for red detection can be obtained by reducing the thickness of the internal recombination junction while by increasing the intrinsic layer of the bottom a-Si:H cell, a better detection of the green color under appropriated applied voltages is foreseen. The physics behind the device functioning is explained through a numerical simulation of the internal electrical configuration of the device in dark and under different wavelength irradiations. Considerations about conduction band offsets, electrical field profiles and inversion layers will be taken into account to explain the optical and voltage bias dependence of the spectral response. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications

  2. Adaptive Rates of High-Spectral-Efficiency WDM/SDM Channels Using PDM-1024-QAM Probabilistic Shaping

    DEFF Research Database (Denmark)

    Hu, Hao; Yankov, Metodi Plamenov; Da Ros, Francesco

    2017-01-01

    We demonstrate adaptive rates and spectral efficiencies in WDM/SDM transmission using probabilistically shaped PDM-1024-QAM signals, achieving up to 7-Tbit/s data rates per spatial-superchannel and up to 297.8-bit/s/Hz aggregate spectral efficiency using a 30-core fiber on 12.5 and 25GHz WDM grids...

  3. Highly Efficient Spectrally Stable Red Perovskite Light-Emitting Diodes.

    Science.gov (United States)

    Tian, Yu; Zhou, Chenkun; Worku, Michael; Wang, Xi; Ling, Yichuan; Gao, Hanwei; Zhou, Yan; Miao, Yu; Guan, Jingjiao; Ma, Biwu

    2018-05-01

    Perovskite light-emitting diodes (LEDs) have recently attracted great research interest for their narrow emissions and solution processability. Remarkable progress has been achieved in green perovskite LEDs in recent years, but not blue or red ones. Here, highly efficient and spectrally stable red perovskite LEDs with quasi-2D perovskite/poly(ethylene oxide) (PEO) composite thin films as the light-emitting layer are reported. By controlling the molar ratios of organic salt (benzylammonium iodide) to inorganic salts (cesium iodide and lead iodide), luminescent quasi-2D perovskite thin films are obtained with tunable emission colors from red to deep red. The perovskite/polymer composite approach enables quasi-2D perovskite/PEO composite thin films to possess much higher photoluminescence quantum efficiencies and smoothness than their neat quasi-2D perovskite counterparts. Electrically driven LEDs with emissions peaked at 638, 664, 680, and 690 nm have been fabricated to exhibit high brightness and external quantum efficiencies (EQEs). For instance, the perovskite LED with an emission peaked at 680 nm exhibits a brightness of 1392 cd m -2 and an EQE of 6.23%. Moreover, exceptional electroluminescence spectral stability under continuous device operation has been achieved for these red perovskite LEDs. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  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. [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.

  6. 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...

  7. 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.

  8. Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

    Directory of Open Access Journals (Sweden)

    Genyun Sun

    2017-08-01

    Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

  9. Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

    Science.gov (United States)

    Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

    2017-08-18

    Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

  10. Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

    Science.gov (United States)

    Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

    2017-01-01

    Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

  11. Systems and methods for selective detection and imaging in coherent Raman microscopy by spectral excitation shaping

    Science.gov (United States)

    Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei

    2016-03-15

    A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.

  12. 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...

  13. 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.

  14. 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.

  15. 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)

  16. An efficient adaptive arithmetic coding image compression technology

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Yun Jiao-Jiao; Zhang Yong-Lei

    2011-01-01

    This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  17. SHARPENDING OF THE VNIR AND SWIR BANDS OF THE WIDE BAND SPECTRAL IMAGER ONBOARD TIANGONG-II IMAGERY USING THE SELECTED BANDS

    Directory of Open Access Journals (Sweden)

    Q. Liu

    2018-04-01

    Full Text Available The Tiangong-II space lab was launched at the Jiuquan Satellite Launch Center of China on September 15, 2016. The Wide Band Spectral Imager (WBSI onboard the Tiangong-II has 14 visible and near-infrared (VNIR spectral bands covering the range from 403–990 nm and two shortwave infrared (SWIR bands covering the range from 1230–1250 nm and 1628–1652 nm respectively. In this paper the selected bands are proposed which aims at considering the closest spectral similarities between the VNIR with 100 m spatial resolution and SWIR bands with 200 m spatial resolution. The evaluation of Gram-Schmidt transform (GS sharpening techniques embedded in ENVI software is presented based on four types of the different low resolution pan band. The experimental results indicated that the VNIR band with higher CC value with the raw SWIR Band was selected, more texture information was injected the corresponding sharpened SWIR band image, and at that time another sharpened SWIR band image preserve the similar spectral and texture characteristics to the raw SWIR band image.

  18. 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.

  19. 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...

  20. 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%.

  1. 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.

  2. Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover

    Science.gov (United States)

    Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.

    2017-07-01

    Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.

  3. 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.

  4. Optically trapped atomic resonant devices for narrow linewidth spectral imaging

    Science.gov (United States)

    Qian, Lipeng

    This thesis focuses on the development of atomic resonant devices for spectroscopic applications. The primary emphasis is on the imaging properties of optically thick atomic resonant fluorescent filters and their applications. In addition, this thesis presents a new concept for producing very narrow linewidth light as from an atomic vapor lamp pumped by a nanosecond pulse system. This research was motivated by application for missile warning system, and presents an innovative approach to a wide angle, ultra narrow linewidth imaging filter using a potassium vapor cell. The approach is to image onto and collect the fluorescent photons emitted from the surface of an optically thick potassium vapor cell, generating a 2 GHz pass-band imaging filter. This linewidth is narrow enough to fall within a Fraunhefer dark zone in the solar spectrum, thus make the detection solar blind. Experiments are conducted to measure the absorption line shape of the potassium resonant filter, the quantum efficiency of the fluorescent behavior, and the resolution of the fluorescent image. Fluorescent images with different spatial frequency components are analyzed by using a discrete Fourier transform, and the imaging capability of the fluorescent filter is described by its Modulation Transfer Function. For the detection of radiation that is spectrally broader than the linewidth of the potassium imaging filter, the fluorescent image is seen to be blurred by diffuse fluorescence from the slightly off resonant photons. To correct this, an ultra-thin potassium imaging filter is developed and characterized. The imaging property of the ultra-thin potassium imaging cell is tested with a potassium seeded flame, yielding a resolution image of ˜ 20 lines per mm. The physics behind the atomic resonant fluorescent filter is radiation trapping. The diffusion process of the resonant photons trapped in the atomic vapor is theoretically described in this thesis. A Monte Carlo method is used to simulate the

  5. Spectral-Efficiency - Illumination Pareto Front for Energy Harvesting Enabled VLC System

    KAUST Repository

    Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Chaaban, Anas; Alouini, Mohamed-Slim

    2017-01-01

    . The adopted optical system provides users with illumination and data communication services. The outdoor optical design objective is to maximize the illumination, while the communication design objective is to maximize the spectral efficiency (SE). The design

  6. 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.

  7. 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.

  8. 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.

  9. Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach

    KAUST Repository

    Amin, Osama

    2015-04-23

    In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.

  10. Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach

    KAUST Repository

    Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed; Dobre, Octavia

    2015-01-01

    In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.

  11. 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.

  12. Imaging breast adipose and fibroglandular tissue molecular signatures by using hybrid MRI-guided near-infrared spectral tomography

    Science.gov (United States)

    Brooksby, Ben; Pogue, Brian W.; Jiang, Shudong; Dehghani, Hamid; Srinivasan, Subhadra; Kogel, Christine; Tosteson, Tor D.; Weaver, John; Poplack, Steven P.; Paulsen, Keith D.

    2006-06-01

    Magnetic resonance (MR)-guided near-infrared spectral tomography was developed and used to image adipose and fibroglandular breast tissue of 11 normal female subjects, recruited under an institutional review board-approved protocol. Images of hemoglobin, oxygen saturation, water fraction, and subcellular scattering were reconstructed and show that fibroglandular fractions of both blood and water are higher than in adipose tissue. Variation in adipose and fibroglandular tissue composition between individuals was not significantly different across the scattered and dense breast categories. Combined MR and near-infrared tomography provides fundamental molecular information about these tissue types with resolution governed by MR T1 images. hemoglobin | magnetic resonance imaging | water | fat | oxygen saturation

  13. From spectral information to animal colour vision: experiments and concepts.

    Science.gov (United States)

    Kelber, Almut; Osorio, Daniel

    2010-06-07

    Many animals use the spectral distribution of light to guide behaviour, but whether they have colour vision has been debated for over a century. Our strong subjective experience of colour and the fact that human vision is the paradigm for colour science inevitably raises the question of how we compare with other species. This article outlines four grades of 'colour vision' that can be related to the behavioural uses of spectral information, and perhaps to the underlying mechanisms. In the first, even without an (image-forming) eye, simple organisms can compare photoreceptor signals to locate a desired light environment. At the next grade, chromatic mechanisms along with spatial vision guide innate preferences for objects such as food or mates; this is sometimes described as wavelength-specific behaviour. Here, we compare the capabilities of di- and trichromatic vision, and ask why some animals have more than three spectral types of receptors. Behaviours guided by innate preferences are then distinguished from a grade that allows learning, in part because the ability to learn an arbitrary colour is evidence for a neural representation of colour. The fourth grade concerns colour appearance rather than colour difference: for instance, the distinction between hue and saturation, and colour categorization. These higher-level phenomena are essential to human colour perception but poorly known in animals, and we suggest how they can be studied. Finally, we observe that awareness of colour and colour qualia cannot be easily tested in animals.

  14. Spectrally selective glazings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-08-01

    Spectrally selective glazing is window glass that permits some portions of the solar spectrum to enter a building while blocking others. This high-performance glazing admits as much daylight as possible while preventing transmission of as much solar heat as possible. By controlling solar heat gains in summer, preventing loss of interior heat in winter, and allowing occupants to reduce electric lighting use by making maximum use of daylight, spectrally selective glazing significantly reduces building energy consumption and peak demand. Because new spectrally selective glazings can have a virtually clear appearance, they admit more daylight and permit much brighter, more open views to the outside while still providing the solar control of the dark, reflective energy-efficient glass of the past. This Federal Technology Alert provides detailed information and procedures for Federal energy managers to consider spectrally selective glazings. The principle of spectrally selective glazings is explained. Benefits related to energy efficiency and other architectural criteria are delineated. Guidelines are provided for appropriate application of spectrally selective glazing, and step-by-step instructions are given for estimating energy savings. Case studies are also presented to illustrate actual costs and energy savings. Current manufacturers, technology users, and references for further reading are included for users who have questions not fully addressed here.

  15. Spectral and Power-Efficiency Trade-off in Fixed-Grid Optical Networks

    Directory of Open Access Journals (Sweden)

    Sridhar Iyer

    2017-09-01

    Full Text Available The improvement of spectral efficiency in the MLR networks can be obtained by the reduction of sub-band spacing, or by minimizing the spacing of the sub-bands that operate at varied data rates. However, due to the presence of physical layer impairments, minimization in sub-band spacing leads to adverse effects on the channel(s transmission reach. As a result there occurs an increase in the consumed power due to the requirement of increase in regeneration of the signal. In the current work we propose an improved DWDM grating in view of obtaining higher spectral efficiency. For a system, with and without Forward Error Correction capabilities (i for various SLR solutions, we find and compare power consumption values of the components with respect to the total traffic, and (ii for different MLR and SLR solutions, for a fixed QoT, we evaluate the minimum values of the sub-band and the channel spacing, and also evaluate and compare the power-efficiency with the distance of transmission.

  16. 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

  17. 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

  18. Diagnostic medical imaging systems. X-ray radiography and angiography, computerized tomography, nuclear medicine, NMR imaging, sonography, integrated image information systems. 3. rev. and enl. ed.

    International Nuclear Information System (INIS)

    Morneburg, H.

    1995-01-01

    This third edition is based on major review and updating work. Many recent developments have been included, as for instance novel systems for fluoroscopy and mammography, spiral CT and electron beam CT, nuclear medical tomography ( SPECT and PET), novel techniques for fast NMR imaging, spectral and colour coded duplex sonography, as well as a new chapter on integrated image information systems, including network installations. (orig.) [de

  19. Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

    KAUST Repository

    Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Alouini, Mohamed-Slim

    2016-01-01

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

  20. Resource allocation for phantom cellular networks: Energy efficiency vs spectral efficiency

    KAUST Repository

    Abdelhady, Amr M.

    2016-07-26

    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Mean-while, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that finds the SE and EE resource allocation strategies for phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and phantom cells share of the total number of available resource blocks. We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It was found that increasing phantom cells share of resource blocks decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. © 2016 IEEE.

  1. Spectrally based mapping of riverbed composition

    Science.gov (United States)

    Legleiter, Carl; Stegman, Tobin K.; Overstreet, Brandon T.

    2016-01-01

    Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader

  2. 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.

  3. 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.

  4. 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.

  5. Efficient Lossy Compression for Compressive Sensing Acquisition of Images in Compressive Sensing Imaging Systems

    Directory of Open Access Journals (Sweden)

    Xiangwei Li

    2014-12-01

    Full Text Available Compressive Sensing Imaging (CSI is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS acquisition are very different from traditional image acquisition, the general image compression solution may not work well. In this paper, we propose an efficient lossy compression solution for CS acquisition of images by considering the distinctive features of the CSI. First, we design an adaptive compressive sensing acquisition method for images according to the sampling rate, which could achieve better CS reconstruction quality for the acquired image. Second, we develop a universal quantization for the obtained CS measurements from CS acquisition without knowing any a priori information about the captured image. Finally, we apply these two methods in the CSI system for efficient lossy compression of CS acquisition. Simulation results demonstrate that the proposed solution improves the rate-distortion performance by 0.4~2 dB comparing with current state-of-the-art, while maintaining a low computational complexity.

  6. 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

  7. Probabilistic hypergraph based hash codes for social image search

    Institute of Scientific and Technical Information of China (English)

    Yi XIE; Hui-min YU; Roland HU

    2014-01-01

    With the rapid development of the Internet, recent years have seen the explosive growth of social media. This brings great challenges in performing efficient and accurate image retrieval on a large scale. Recent work shows that using hashing methods to embed high-dimensional image features and tag information into Hamming space provides a powerful way to index large collections of social images. By learning hash codes through a spectral graph partitioning algorithm, spectral hashing (SH) has shown promising performance among various hashing approaches. However, it is incomplete to model the relations among images only by pairwise simple graphs which ignore the relationship in a higher order. In this paper, we utilize a probabilistic hypergraph model to learn hash codes for social image retrieval. A probabilistic hypergraph model offers a higher order repre-sentation among social images by connecting more than two images in one hyperedge. Unlike a normal hypergraph model, a probabilistic hypergraph model considers not only the grouping information, but also the similarities between vertices in hy-peredges. Experiments on Flickr image datasets verify the performance of our proposed approach.

  8. 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.

  9. 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...

  10. 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.)

  11. Spectral imaging and archival data in analyzing the Madonna of the Rabbit painting by Manet and Titian

    Czech Academy of Sciences Publication Activity Database

    Striová, J.; Ruberto, C.; Barucci, M.; Blažek, Jan; Kunzelman, D.; Dal Fovo, A.; Pampaloni, E.; Fontana, R.

    (2018) ISSN 1433-7851 Institutional support: RVO:67985556 Keywords : spectral mapping * image processing * visible near-infrared multispectral scanner Subject RIV: JC - Computer Hardware ; Software OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 11.994, year: 2016 http://library.utia.cas.cz/separaty/2018/ZOI/blazek-0489046.pdf

  12. 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

  13. Augmenting the spectral efficiency of enhanced PAM-DMT-based optical wireless communications.

    Science.gov (United States)

    Islim, Mohamed Sufyan; Haas, Harald

    2016-05-30

    The energy efficiency of pulse-amplitude-modulated discrete multitone modulation (PAM-DMT) decreases as the modulation order of M-PAM modulation increases. Enhanced PAM-DMT (ePAM-DMT) was proposed as a solution to the reduced energy efficiency of PAM-DMT. This was achieved by allowing multiple streams of PAM-DMT to be superimposed and successively demodulated at the receiver side. In order to maintain a distortion-free unipolar ePAM-DMT system, the multiple time-domain PAM-DMT streams are required to be aligned. However, aligning the antisymmetry in ePAM-DMT is complex and results in efficiency losses. In this paper, a novel simplified method to apply the superposition modulation on M-PAM modulated discrete multitone (DMT) is introduced. Contrary to ePAM-DMT, the signal generation of the proposed system, termed augmented spectral efficiency discrete multitone (ASE-DMT), occurs in the frequency domain. This results in an improved spectral and energy efficiency. The analytical bit error rate (BER) performance bound of the proposed system is derived and compared with Monte-Carlo simulations. The system performance is shown to offer significant electrical and optical energy savings compared with ePAM-DMT and DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM).

  14. 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

  15. [Fast Detection of Camellia Sinensis Growth Process and Tea Quality Informations with Spectral Technology: A Review].

    Science.gov (United States)

    Peng, Ji-yu; Song, Xing-lin; Liu, Fei; Bao, Yi-dan; He, Yong

    2016-03-01

    The research achievements and trends of spectral technology in fast detection of Camellia sinensis growth process information and tea quality information were being reviewed. Spectral technology is a kind of fast, nondestructive, efficient detection technology, which mainly contains infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy and mass spectroscopy. The rapid detection of Camellia sinensis growth process information and tea quality is helpful to realize the informatization and automation of tea production and ensure the tea quality and safety. This paper provides a review on its applications containing the detection of tea (Camellia sinensis) growing status(nitrogen, chlorophyll, diseases and insect pest), the discrimination of tea varieties, the grade discrimination of tea, the detection of tea internal quality (catechins, total polyphenols, caffeine, amino acid, pesticide residual and so on), the quality evaluation of tea beverage and tea by-product, the machinery of tea quality determination and discrimination. This paper briefly introduces the trends of the technology of the determination of tea growth process information, sensor and industrial application. In conclusion, spectral technology showed high potential to detect Camellia sinensis growth process information, to predict tea internal quality and to classify tea varieties and grades. Suitable chemometrics and preprocessing methods is helpful to improve the performance of the model and get rid of redundancy, which provides the possibility to develop the portable machinery. Future work is to develop the portable machinery and on-line detection system is recommended to improve the further application. The application and research achievement of spectral technology concerning about tea were outlined in this paper for the first time, which contained Camellia sinensis growth, tea production, the quality and safety of tea and by-produce and so on, as well as some problems to be solved

  16. Imaging Food Quality

    DEFF Research Database (Denmark)

    Møller, Flemming

    Imaging and spectroscopy have long been established methods for food quality control both in the laboratories and online. An ever increasing number of analytical techniques are being developed into imaging methods and existing imaging methods to contain spectral information. Images and especially...... spectral images contain large amounts of data which should be analysed appropriately by techniques combining structure and spectral information. This dissertation deals with how different types of food quality can be measured by imaging techniques, analysed with appropriate image analysis techniques...... and finally use the image data to predict or visualise food quality. A range of different food quality parameters was addressed, i.e. water distribution in bread throughout storage, time series analysis of chocolate milk stability, yoghurt glossiness, graininess and dullness and finally structure and meat...

  17. Spectrally efficient polarization multiplexed direct-detection OFDM system without frequency gap.

    Science.gov (United States)

    Wei, Chia-Chien; Zeng, Wei-Siang; Lin, Chun-Ting

    2016-01-25

    We experimentally demonstrate a spectrally efficient direct-detection orthogonal frequency-division multiplexing (DD-OFDM) system. In addition to polarization-division multiplexing, removing the frequency gap further improves the spectral efficiency of the OFDM system. The frequency gap between a reference carrier and OFDM subcarriers avoids subcarrier-to-subcarrier beating interference (SSBI) in traditional DD-OFDM systems. Without dynamic polarization control, the resulting interference after square-law direct detection in the proposed gap-less system is polarization-dependent and composed of linear inter-carrier interference (ICI) and nonlinear SSBI. Thus, this work proposes an iterative multiple-input multiple-output detection scheme to remove the mixed polarization-dependent interference. Compared to the previous scheme, which only removes ICI, the proposed scheme can further eliminate SSBI to achieve the improvement of ∼ 7 dB in signal-to-noise ratio. Without the need for polarization control, we successfully utilize 7-GHz bandwidth to transmit a 39.5-Gbps polarization multiplexed OFDM signal over 100 km.

  18. 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.

  19. 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.

  20. Spectral edge: gradient-preserving spectral mapping for image fusion.

    Science.gov (United States)

    Connah, David; Drew, Mark S; Finlayson, Graham D

    2015-12-01

    This paper describes a novel approach to image fusion for color display. Our goal is to generate an output image whose gradient matches that of the input as closely as possible. We achieve this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mapped exactly to that of a low-dimensional gradient field which is then reintegrated to form an output. Constraints on output colors are provided by an initial RGB rendering. Initially, we motivate our solution with a simple "ansatz" (educated guess) for projecting higher-D contrast onto color gradients, which we expand to a more rigorous theorem to incorporate color constraints. The solution to these constrained optimizations is closed-form, allowing for simple and hence fast and efficient algorithms. The approach can map any N-D image data to any M-D output and can be used in a variety of applications using the same basic algorithm. In this paper, we focus on the problem of mapping N-D inputs to 3D color outputs. We present results in five applications: hyperspectral remote sensing, fusion of color and near-infrared or clear-filter images, multilighting imaging, dark flash, and color visualization of magnetic resonance imaging diffusion-tensor imaging.

  1. The information spectrum as a measure of radiographic image quality and system performance

    International Nuclear Information System (INIS)

    Kanamori, H.; Matsumoto, M.

    1984-01-01

    The spectrum (spatial-frequency component) of the information capacity of a radiograph, here called the information spectrum, is offered as a measure of image quality and system performance. The information spectrum is a much more practical expression than information capacity by itself: it combines synthetically the contrast, the latitude, the sharpness and the granularity, and is expressed as a function of spatial frequency. The information spectrum can be readily calculated by using the dynamic density range and the MTF and noise Wiener spectrum at medium density range. A practical example is given. The appropriate system for each object can be selected by comparing the information spectral values of various imaging systems at the significant spatial frequency range predetermined for each object. (author)

  2. Area Spectral Efficiency and Energy Efficiency Tradeoff in Ultradense Heterogeneous Networks

    Directory of Open Access Journals (Sweden)

    Lanhua Xiang

    2017-01-01

    Full Text Available In order to meet the demand of explosive data traffic, ultradense base station (BS deployment in heterogeneous networks (HetNets as a key technique in 5G has been proposed. However, with the increment of BSs, the total energy consumption will also increase. So, the energy efficiency (EE has become a focal point in ultradense HetNets. In this paper, we take the area spectral efficiency (ASE into consideration and focus on the tradeoff between the ASE and EE in an ultradense HetNet. The distributions of BSs in the two-tier ultradense HetNet are modeled by two independent Poisson point processes (PPPs and the expressions of ASE and EE are derived by using the stochastic geometry tool. The tradeoff between the ASE and EE is formulated as a constrained optimization problem in which the EE is maximized under the ASE constraint, through optimizing the BS densities. It is difficult to solve the optimization problem analytically, because the closed-form expressions of ASE and EE are not easily obtained. Therefore, simulations are conducted to find optimal BS densities.

  3. The NASA earth resources spectral information system: A data compilation, second supplement

    Science.gov (United States)

    Vincent, R. K.

    1973-01-01

    The NASA Earth Resources Spectral Information System (ERSIS) and the information contained therein are described. It is intended for use as a second supplement to the NASA Earth Resources Spectral Information System: A Data Compilation, NASA CR-31650-24-T, May 1971. The current supplement includes approximately 100 rock and mineral, and 375 vegetation directional reflectance spectral curves in the optical region from 0.2 to 22.0 microns. The data were categorized by subject and each curve plotted on a single graph. Each graph is fully titled to indicate curve source and indexed by subject to facilitate user retrieval from ERSIS magnetic tape records.

  4. Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

    Science.gov (United States)

    Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

    2014-10-23

    A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

  5. Improving quantum efficiency and spectral resolution of a CCD through direct manipulation of the depletion region

    Science.gov (United States)

    Brown, Craig; Ambrosi, Richard M.; Abbey, Tony; Godet, Olivier; O'Brien, R.; Turner, M. J. L.; Holland, Andrew; Pool, Peter J.; Burt, David; Vernon, David

    2008-07-01

    Future generations of X-ray astronomy instruments will require position sensitive detectors in the form of charge-coupled devices (CCDs) for X-ray spectroscopy and imaging with the ability to probe the X-ray universe with greater efficiency. This will require the development of CCDs with structures that will improve their quantum efficiency over the current state of the art. The quantum efficiency improvements would have to span a broad energy range (0.2 keV to >15 keV). These devices will also have to be designed to withstand the harsh radiation environments associated with orbits that extend beyond the Earth's magnetosphere. This study outlines the most recent work carried out at the University of Leicester focused on improving the quantum efficiency of an X-ray sensitive CCD through direct manipulation of the device depletion region. It is also shown that increased spectral resolution is achieved using this method due to a decrease in the number of multi-pixel events. A Monte Carlo and analytical models of the CCD have been developed and used to determine the depletion depths achieved through variation of the device substrate voltage, Vss. The models are also used to investigate multi-pixel event distributions and quantum efficiency as a function of depletion depth.

  6. On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

    OpenAIRE

    Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

    2016-01-01

    The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through c...

  7. 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.

  8. 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.

  9. Bessel smoothing filter for spectral-element mesh

    Science.gov (United States)

    Trinh, P. T.; Brossier, R.; Métivier, L.; Virieux, J.; Wellington, P.

    2017-06-01

    Smoothing filters are extremely important tools in seismic imaging and inversion, such as for traveltime tomography, migration and waveform inversion. For efficiency, and as they can be used a number of times during inversion, it is important that these filters can easily incorporate prior information on the geological structure of the investigated medium, through variable coherent lengths and orientation. In this study, we promote the use of the Bessel filter to achieve these purposes. Instead of considering the direct application of the filter, we demonstrate that we can rely on the equation associated with its inverse filter, which amounts to the solution of an elliptic partial differential equation. This enhances the efficiency of the filter application, and also its flexibility. We apply this strategy within a spectral-element-based elastic full waveform inversion framework. Taking advantage of this formulation, we apply the Bessel filter by solving the associated partial differential equation directly on the spectral-element mesh through the standard weak formulation. This avoids cumbersome projection operators between the spectral-element mesh and a regular Cartesian grid, or expensive explicit windowed convolution on the finite-element mesh, which is often used for applying smoothing operators. The associated linear system is solved efficiently through a parallel conjugate gradient algorithm, in which the matrix vector product is factorized and highly optimized with vectorized computation. Significant scaling behaviour is obtained when comparing this strategy with the explicit convolution method. The theoretical numerical complexity of this approach increases linearly with the coherent length, whereas a sublinear relationship is observed practically. Numerical illustrations are provided here for schematic examples, and for a more realistic elastic full waveform inversion gradient smoothing on the SEAM II benchmark model. These examples illustrate well the

  10. Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information

    Science.gov (United States)

    Legleiter, Carl; Kinzel, Paul J.; Nelson, Jonathan M.

    2017-01-01

    Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquired thermal image time series from bridges spanning five streams in Alaska and observed strong agreement between velocities measured in situ and those inferred by Particle Image Velocimetry (PIV), which quantified advection of thermal features by the flow. The resulting surface velocities were converted to depth-averaged velocities by applying site-specific, calibrated velocity indices. Field spectra from three clear-flowing streams provided strong relationships between depth and reflectance, suggesting that, under favorable conditions, spectrally-based bathymetric mapping could complement thermal PIV in a hybrid approach to remote sensing of river discharge; this strategy would not be applicable to larger, more turbid rivers, however. A more flexible and efficient alternative might involve inferring depth from thermal data based on relationships between depth and integral length scales of turbulent fluctuations in temperature, captured as variations in image brightness. We observed moderately strong correlations for a site-aggregated data set that reduced station-to-station variability but encompassed a broad range of depths. Discharges calculated using thermal PIV-derived velocities were within 15% of in situ measurements when combined with depths measured directly in the field or estimated from field spectra and within 40% when the depth information also was derived from thermal images. The results of this initial, proof-of-concept investigation suggest that remote sensing techniques could facilitate measurement of river discharge.

  11. Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares

    Directory of Open Access Journals (Sweden)

    Jianjun Liu

    2017-11-01

    Full Text Available As a widely used classifier, sparse representation classification (SRC has shown its good performance for hyperspectral image classification. Recent works have highlighted that it is the collaborative representation mechanism under SRC that makes SRC a highly effective technique for classification purposes. If the dimensionality and the discrimination capacity of a test pixel is high, other norms (e.g., ℓ 2 -norm can be used to regularize the coding coefficients, except for the sparsity ℓ 1 -norm. In this paper, we show that in the kernel space the nonnegative constraint can also play the same role, and thus suggest the investigation of kernel fully constrained least squares (KFCLS for hyperspectral image classification. Furthermore, in order to improve the classification performance of KFCLS by incorporating spatial-spectral information, we investigate two kinds of spatial-spectral methods using two regularization strategies: (1 the coefficient-level regularization strategy, and (2 the class-level regularization strategy. Experimental results conducted on four real hyperspectral images demonstrate the effectiveness of the proposed KFCLS, and show which way to incorporate spatial-spectral information efficiently in the regularization framework.

  12. 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.

  13. 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...

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

    NARCIS (Netherlands)

    Stratoulias, D.; Tolpekin, Valentyn; De By, Rolf; Zurita-milla, Raul; Retsios, Bas; Bijker, Wietske; Hasan, Mohammad; Vermote, Eric

    2017-01-01

    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

  15. 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

  16. 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

  17. Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

    Directory of Open Access Journals (Sweden)

    Peng Shao

    2014-08-01

    Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

  18. 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

  19. 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...

  20. Digital mammography: Mixed feature neural network with spectral entropy decision for detection of microcalcifications

    Energy Technology Data Exchange (ETDEWEB)

    Zheng, B. [Univ. of South Florida, Tampa, FL (United States)]|[Nanjing Univ. of Posts and Telecommunications (China). Dept. of Telecommunication Engineering; Qian, W.; Clarke, L.P. [Univ. of South Florida, Tampa, FL (United States)

    1996-10-01

    A computationally efficient mixed feature based neural network (MFNN) is proposed for the detection of microcalcification clusters (MCC`s) in digitized mammograms. The MFNN employs features computed in both the spatial and spectral domain and uses spectral entropy as a decision parameter. Backpropagation with Kalman Filtering (KF) is employed to allow more efficient network training as required for evaluation of different features, input images, and related error analysis. A previously reported, wavelet-based image-enhancement method is also employed to enhance microcalcification clusters for improved detection. The relative performance of the MFNN for both the raw and enhanced images is evaluated using a common image database of 30 digitized mammograms, with 20 images containing 21 biopsy proven MCC`s and ten normal cases. The computed sensitivity (true positive (TP) detection rate) was 90.1% with an average low false positive (FP) detection of 0.71 MCCs/image for the enhanced images using a modified k-fold validation error estimation technique. The corresponding computed sensitivity for the raw images was reduced to 81.4% and with 0.59 FP`s MCCs/image. A relative comparison to an earlier neural network (NN) design, using only spatially related features, suggests the importance of the addition of spectral domain features when the raw image data are analyzed.

  1. Digital mammography: Mixed feature neural network with spectral entropy decision for detection of microcalcifications

    International Nuclear Information System (INIS)

    Zheng, B.

    1996-01-01

    A computationally efficient mixed feature based neural network (MFNN) is proposed for the detection of microcalcification clusters (MCC's) in digitized mammograms. The MFNN employs features computed in both the spatial and spectral domain and uses spectral entropy as a decision parameter. Backpropagation with Kalman Filtering (KF) is employed to allow more efficient network training as required for evaluation of different features, input images, and related error analysis. A previously reported, wavelet-based image-enhancement method is also employed to enhance microcalcification clusters for improved detection. The relative performance of the MFNN for both the raw and enhanced images is evaluated using a common image database of 30 digitized mammograms, with 20 images containing 21 biopsy proven MCC's and ten normal cases. The computed sensitivity (true positive (TP) detection rate) was 90.1% with an average low false positive (FP) detection of 0.71 MCCs/image for the enhanced images using a modified k-fold validation error estimation technique. The corresponding computed sensitivity for the raw images was reduced to 81.4% and with 0.59 FP's MCCs/image. A relative comparison to an earlier neural network (NN) design, using only spatially related features, suggests the importance of the addition of spectral domain features when the raw image data are analyzed

  2. 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.

  3. Evolutionary Computing Methods for Spectral Retrieval

    Science.gov (United States)

    Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

    2009-01-01

    A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

  4. Ultra-Widefield Steering-Based Spectral-Domain Optical Coherence Tomography Imaging of the Retinal Periphery.

    Science.gov (United States)

    Choudhry, Netan; Golding, John; Manry, Matthew W; Rao, Rajesh C

    2016-06-01

    To describe the spectral-domain optical coherence tomography (SD OCT) features of peripheral retinal findings using an ultra-widefield (UWF) steering technique to image the retinal periphery. Observational study. A total of 68 patients (68 eyes) with 19 peripheral retinal features. Spectral-domain OCT-based structural features. Nineteen peripheral retinal features, including vortex vein, congenital hypertrophy of the retinal pigment epithelium, pars plana, ora serrata pearl, typical cystoid degeneration (TCD), cystic retinal tuft, meridional fold, lattice and cobblestone degeneration, retinal hole, retinal tear, rhegmatogenous retinal detachment, typical degenerative senile retinoschisis, peripheral laser coagulation scars, ora tooth, cryopexy scars (retinal tear and treated retinoblastoma scar), bone spicules, white without pressure, and peripheral drusen, were identified by peripheral clinical examination. Near-infrared scanning laser ophthalmoscopy images and SD OCT of these entities were registered to UWF color photographs. Spectral-domain OCT resolved structural features of all peripheral findings. Dilated hyporeflective tubular structures within the choroid were observed in the vortex vein. Loss of retinal lamination, neural retinal attenuation, retinal pigment epithelium loss, or hypertrophy was seen in several entities, including congenital hypertrophy of the retinal pigment epithelium, ora serrata pearl, TCD, cystic retinal tuft, meridional fold, lattice, and cobblestone degenerations. Hyporeflective intraretinal spaces, indicating cystoid or schitic fluid, were seen in ora serrata pearl, ora tooth, TCD, cystic retinal tuft, meridional fold, retinal hole, and typical degenerative senile retinoschisis. The vitreoretinal interface, which often consisted of lamellae-like structures of the condensed cortical vitreous near or adherent to the neural retina, appeared clearly in most peripheral findings, confirming its association with many low-risk and vision

  5. Global sampling of the seasonal changes in vegetation biophysical properties and associated carbon flux dynamics: using the synergy of information captured by spectral time series

    Science.gov (United States)

    Campbell, P. K. E.; Huemmrich, K. F.; Middleton, E.; Voorhis, S.; Landis, D.

    2016-12-01

    Spatial heterogeneity and seasonal dynamics in vegetation function contribute significantly to the uncertainties in regional and global CO2 budgets. High spectral resolution imaging spectroscopy ( 10 nm, 400-2500 nm) provides an efficient tool for synoptic evaluation of the factors significantly affecting the ability of the vegetation to sequester carbon and to reflect radiation, due to changes in vegetation chemical and structural composition. EO-1 Hyperion has collected more than 15 years of repeated observations for vegetation studies, and currently Hyperion time series are available for study of vegetation carbon dynamics at a number of FLUX sites. This study presents results from the analysis of EO-1 Hyperion and FLUX seasonal composites for a range of ecosystems across the globe. Spectral differences and seasonal trends were evaluated for each vegetation type and specific phenology. Evaluating the relationships between CO2 flux parameters (e.g., Net ecosystem production - NEP; Gross Ecosystem Exchange - GEE, CO2 flux, μmol m-2 s-1) and spectral parameters for these very different ecosystems, high correlations were established to parameters associated with canopy water and chlorophyll content for deciduous, and photosynthetic function for conifers. Imaging spectrometry provided high spatial resolution maps of CO2 fluxes absorbed by vegetation, and was efficient in tracing seasonal flux dynamics. This study will present examples for key ecosystem tipes to demonstrate the ability of imaging spectrometry and EO-1 Hyperion to map and compare CO2 flux dynamics across the globe.

  6. 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.

  7. 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

  8. 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

  9. Orthogonal polarization spectral (OPS) imaging and topographical characteristics of oral squamous cell carcinoma

    NARCIS (Netherlands)

    Lindeboom, Jerome A.; Mathura, Keshen R.; Ince, Can

    2006-01-01

    Tumor microcirculatory characteristics until now have only been assessed by histological examination of biopsies or invasive imaging technique. The recent introduction of orthogonal polarization spectral (OPS) imaging as a new tool for in vivo visualization of human microcirculation makes it

  10. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal [Albuquerque, NM

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  11. Information theory, spectral geometry, and quantum gravity.

    Science.gov (United States)

    Kempf, Achim; Martin, Robert

    2008-01-18

    We show that there exists a deep link between the two disciplines of information theory and spectral geometry. This allows us to obtain new results on a well-known quantum gravity motivated natural ultraviolet cutoff which describes an upper bound on the spatial density of information. Concretely, we show that, together with an infrared cutoff, this natural ultraviolet cutoff beautifully reduces the path integral of quantum field theory on curved space to a finite number of ordinary integrations. We then show, in particular, that the subsequent removal of the infrared cutoff is safe.

  12. Superharmonic imaging with chirp coded excitation: filtering spectrally overlapped harmonics.

    Science.gov (United States)

    Harput, Sevan; McLaughlan, James; Cowell, David M J; Freear, Steven

    2014-11-01

    Superharmonic imaging improves the spatial resolution by using the higher order harmonics generated in tissue. The superharmonic component is formed by combining the third, fourth, and fifth harmonics, which have low energy content and therefore poor SNR. This study uses coded excitation to increase the excitation energy. The SNR improvement is achieved on the receiver side by performing pulse compression with harmonic matched filters. The use of coded signals also introduces new filtering capabilities that are not possible with pulsed excitation. This is especially important when using wideband signals. For narrowband signals, the spectral boundaries of the harmonics are clearly separated and thus easy to filter; however, the available imaging bandwidth is underused. Wideband excitation is preferable for harmonic imaging applications to preserve axial resolution, but it generates spectrally overlapping harmonics that are not possible to filter in time and frequency domains. After pulse compression, this overlap increases the range side lobes, which appear as imaging artifacts and reduce the Bmode image quality. In this study, the isolation of higher order harmonics was achieved in another domain by using the fan chirp transform (FChT). To show the effect of excitation bandwidth in superharmonic imaging, measurements were performed by using linear frequency modulated chirp excitation with varying bandwidths of 10% to 50%. Superharmonic imaging was performed on a wire phantom using a wideband chirp excitation. Results were presented with and without applying the FChT filtering technique by comparing the spatial resolution and side lobe levels. Wideband excitation signals achieved a better resolution as expected, however range side lobes as high as -23 dB were observed for the superharmonic component of chirp excitation with 50% fractional bandwidth. The proposed filtering technique achieved >50 dB range side lobe suppression and improved the image quality without

  13. Automatic spectral imaging protocol selection and iterative reconstruction in abdominal CT with reduced contrast agent dose: initial experience.

    Science.gov (United States)

    Lv, Peijie; Liu, Jie; Chai, Yaru; Yan, Xiaopeng; Gao, Jianbo; Dong, Junqiang

    2017-01-01

    To evaluate the feasibility, image quality, and radiation dose of automatic spectral imaging protocol selection (ASIS) and adaptive statistical iterative reconstruction (ASIR) with reduced contrast agent dose in abdominal multiphase CT. One hundred and sixty patients were randomly divided into two scan protocols (n = 80 each; protocol A, 120 kVp/450 mgI/kg, filtered back projection algorithm (FBP); protocol B, spectral CT imaging with ASIS and 40 to 70 keV monochromatic images generated per 300 mgI/kg, ASIR algorithm. Quantitative parameters (image noise and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (image noise, small structures, organ enhancement, and overall image quality) were compared. Monochromatic images at 50 keV and 60 keV provided similar or lower image noise, but higher contrast and overall image quality as compared with 120-kVp images. Despite the higher image noise, 40-keV images showed similar overall image quality compared to 120-kVp images. Radiation dose did not differ between the two protocols, while contrast agent dose in protocol B was reduced by 33 %. Application of ASIR and ASIS to monochromatic imaging from 40 to 60 keV allowed contrast agent dose reduction with adequate image quality and without increasing radiation dose compared to 120 kVp with FBP. • Automatic spectral imaging protocol selection provides appropriate scan protocols. • Abdominal CT is feasible using spectral imaging and 300 mgI/kg contrast agent. • 50-keV monochromatic images with 50 % ASIR provide optimal image quality.

  14. A spectral blanking-out controller for demonstration of information barrier technology

    International Nuclear Information System (INIS)

    Liu Suping; Gong Jian; Hu Guangchun; Zhang Jianhua

    2006-01-01

    Information barrier technology has become more and more important in the R and D of radiation fingerprint verification associated with classified items such as nuclear warheads, nuclear components and military-used nuclear materials. The function of information barriers is two-fold: one is to prevent the classified information from leaking out; the other is to provide creditable verification. To fulfill these two functions, the information barriers for a viable verification system (including all its hardware and software) must be designed on the basic principles of protecting classified information and the ability to authenticate. The Spectral Blanking-out Controller (SBC) is developed to illustrate the two functions of the information barriers and to explore some practice measures to meet the required design fundamentals. This paper briefs the task assigned to the SBC, the specific design concerns and the practical information barrier measures. The R and D of the SBC embodies the concepts of information barrier technology and has to conform to the basic guidelines: If a verification system is expected to possess strict information barriers, the design of the system must be integrative with due considerations given to the factors such as the efficiency of the verification technique, the possible measures to protect the classified information from directly or indirectly leaking out, the complete openness in all aspects of the system for the inspectors to authenticate the system for the sake of achieving certain degree of confidence on the verification results. (authors)

  15. Wavelet analysis of molecular dynamics: Efficient extraction of time-frequency information in ultrafast optical processes

    International Nuclear Information System (INIS)

    Prior, Javier; Castro, Enrique; Chin, Alex W.; Almeida, Javier; Huelga, Susana F.; Plenio, Martin B.

    2013-01-01

    New experimental techniques based on nonlinear ultrafast spectroscopies have been developed over the last few years, and have been demonstrated to provide powerful probes of quantum dynamics in different types of molecular aggregates, including both natural and artificial light harvesting complexes. Fourier transform-based spectroscopies have been particularly successful, yet “complete” spectral information normally necessitates the loss of all information on the temporal sequence of events in a signal. This information though is particularly important in transient or multi-stage processes, in which the spectral decomposition of the data evolves in time. By going through several examples of ultrafast quantum dynamics, we demonstrate that the use of wavelets provide an efficient and accurate way to simultaneously acquire both temporal and frequency information about a signal, and argue that this greatly aids the elucidation and interpretation of physical process responsible for non-stationary spectroscopic features, such as those encountered in coherent excitonic energy transport

  16. Time lens based optical fourier transformation for advanced processing of spectrally-efficient OFDM and N-WDM signals

    DEFF Research Database (Denmark)

    Guan, Pengyu; Røge, Kasper Meldgaard; Morioka, Toshio

    2016-01-01

    We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals.......We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals....

  17. An explorative chemometric approach applied to hyperspectral images for the study of illuminated manuscripts

    Science.gov (United States)

    Catelli, Emilio; Randeberg, Lise Lyngsnes; Alsberg, Bjørn Kåre; Gebremariam, Kidane Fanta; Bracci, Silvano

    2017-04-01

    Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented. The method makes use of chemometric tools for spectral de-noising (minimum noise fraction (MNF)) and image analysis (multivariate image analysis (MIA) and iterative key set factor analysis (IKSFA)/spectral angle mapper (SAM)) which have given an efficient separation, classification and mapping of colorants from visible-near-infrared (VNIR) hyperspectral images of an ancient illuminated fragment. The identification of colorants was achieved by extracting and interpreting the VNIR spectra as well as by using a portable X-ray fluorescence (XRF) spectrometer.

  18. Preclinical evaluation and intraoperative human retinal imaging with a high-resolution microscope-integrated spectral domain optical coherence tomography device.

    Science.gov (United States)

    Hahn, Paul; Migacz, Justin; O'Donnell, Rachelle; Day, Shelley; Lee, Annie; Lin, Phoebe; Vann, Robin; Kuo, Anthony; Fekrat, Sharon; Mruthyunjaya, Prithvi; Postel, Eric A; Izatt, Joseph A; Toth, Cynthia A

    2013-01-01

    The authors have recently developed a high-resolution microscope-integrated spectral domain optical coherence tomography (MIOCT) device designed to enable OCT acquisition simultaneous with surgical maneuvers. The purpose of this report is to describe translation of this device from preclinical testing into human intraoperative imaging. Before human imaging, surgical conditions were fully simulated for extensive preclinical MIOCT evaluation in a custom model eye system. Microscope-integrated spectral domain OCT images were then acquired in normal human volunteers and during vitreoretinal surgery in patients who consented to participate in a prospective institutional review board-approved study. Microscope-integrated spectral domain OCT images were obtained before and at pauses in surgical maneuvers and were compared based on predetermined diagnostic criteria to images obtained with a high-resolution spectral domain research handheld OCT system (HHOCT; Bioptigen, Inc) at the same time point. Cohorts of five consecutive patients were imaged. Successful end points were predefined, including ≥80% correlation in identification of pathology between MIOCT and HHOCT in ≥80% of the patients. Microscope-integrated spectral domain OCT was favorably evaluated by study surgeons and scrub nurses, all of whom responded that they would consider participating in human intraoperative imaging trials. The preclinical evaluation identified significant improvements that were made before MIOCT use during human surgery. The MIOCT transition into clinical human research was smooth. Microscope-integrated spectral domain OCT imaging in normal human volunteers demonstrated high resolution comparable to tabletop scanners. In the operating room, after an initial learning curve, surgeons successfully acquired human macular MIOCT images before and after surgical maneuvers. Microscope-integrated spectral domain OCT imaging confirmed preoperative diagnoses, such as full-thickness macular hole

  19. Gamma-Ray Imager With High Spatial And Spectral Resolution

    Science.gov (United States)

    Callas, John L.; Varnell, Larry S.; Wheaton, William A.; Mahoney, William A.

    1996-01-01

    Gamma-ray instrument developed to enable both two-dimensional imaging at relatively high spatial resolution and spectroscopy at fractional-photon-energy resolution of about 10 to the negative 3rd power in photon-energy range from 10 keV to greater than 10 MeV. In its spectroscopic aspect, instrument enables identification of both narrow and weak gamma-ray spectral peaks.

  20. Conjugate Etalon Spectral Imager (CESI) & Scanning Etalon Methane Mapper (SEMM), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Development of the CESI focal plane and optics technology will lead to miniaturized hyperspectral and SWIR-band spectral imaging instrumentation compatible with...

  1. MODELLING OF CARBON MONOXIDE AIR POLLUTION IN LARG CITIES BY EVALUETION OF SPECTRAL LANDSAT8 IMAGES

    Directory of Open Access Journals (Sweden)

    M. Hamzelo

    2015-12-01

    Full Text Available Air pollution in large cities is one of the major problems that resolve and reduce it need multiple applications and environmental management. Of The main sources of this pollution is industrial activities, urban and transport that enter large amounts of contaminants into the air and reduces its quality. With Variety of pollutants and high volume manufacturing, local distribution of manufacturing centers, Testing and measuring emissions is difficult. Substances such as carbon monoxide, sulfur dioxide, and unburned hydrocarbons and lead compounds are substances that cause air pollution and carbon monoxide is most important. Today, data exchange systems, processing, analysis and modeling is of important pillars of management system and air quality control. In this study, using the spectral signature of carbon monoxide gas as the most efficient gas pollution LANDSAT8 images in order that have better spatial resolution than appropriate spectral bands and weather meters،SAM classification algorithm and Geographic Information System (GIS , spatial distribution of carbon monoxide gas in Tehran over a period of one year from the beginning of 2014 until the beginning of 2015 at 11 map have modeled and then to the model valuation ،created maps were compared with the map provided by the Tehran quality comparison air company. Compare involved plans did with the error matrix and results in 4 types of care; overall, producer, user and kappa coefficient was investigated. Results of average accuracy were about than 80%, which indicates the fit method and data used for modeling.

  2. 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

  3. 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.

  4. 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.

  5. Fast backprojection-based reconstruction of spectral-spatial EPR images from projections with the constant sweep of a magnetic field.

    Science.gov (United States)

    Komarov, Denis A; Hirata, Hiroshi

    2017-08-01

    In this paper, we introduce a procedure for the reconstruction of spectral-spatial EPR images using projections acquired with the constant sweep of a magnetic field. The application of a constant field-sweep and a predetermined data sampling rate simplifies the requirements for EPR imaging instrumentation and facilitates the backprojection-based reconstruction of spectral-spatial images. The proposed approach was applied to the reconstruction of a four-dimensional numerical phantom and to actual spectral-spatial EPR measurements. Image reconstruction using projections with a constant field-sweep was three times faster than the conventional approach with the application of a pseudo-angle and a scan range that depends on the applied field gradient. Spectral-spatial EPR imaging with a constant field-sweep for data acquisition only slightly reduces the signal-to-noise ratio or functional resolution of the resultant images and can be applied together with any common backprojection-based reconstruction algorithm. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. 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.

  7. Spectral and Energy Efficiencies in mmWave Cellular Networks for Optimal Utilization

    Directory of Open Access Journals (Sweden)

    Abdulbaset M. Hamed

    2018-01-01

    Full Text Available Millimeter wave (mmWave spectrum has been proposed for use in commercial cellular networks to relieve the already severely congested microwave spectrum. Thus, the design of an efficient mmWave cellular network has gained considerable importance and has to take into account regulations imposed by government agencies with regard to global warming and sustainable development. In this paper, a dense mmWave hexagonal cellular network with each cell consisting of a number of smaller cells with their own Base Stations (BSs is presented as a solution to meet the increasing demand for a variety of high data rate services and growing number of users of cellular networks. Since spectrum and power are critical resources in the design of such a network, a framework is presented that addresses efficient utilization of these resources in mmWave cellular networks in the 28 and 73 GHz bands. These bands are already an integral part of well-known standards such as IEEE 802.15.3c, IEEE 802.11ad, and IEEE 802.16.1. In the analysis, a well-known accurate mmWave channel model for Line of Sight (LOS and Non-Line of Sight (NLOS links is used. The cellular network is analyzed in terms of spectral efficiency, bit/s, energy efficiency, bit/J, area spectral efficiency, bit/s/m2, area energy efficiency, bit/J/m2, and network latency, s/bit. These efficiency metrics are illustrated, using Monte Carlo simulation, as a function of Signal-to-Noise Ratio (SNR, channel model parameters, user distance from BS, and BS transmission power. The efficiency metrics for optimum deployment of cellular networks in 28 and 73 GHz bands are identified. Results show that 73 GHz band achieves better spectrum efficiency and the 28 GHz band is superior in terms of energy efficiency. It is observed that while the latter band is expedient for indoor networks, the former band is appropriate for outdoor networks.

  8. Observer model optimization of a spectral mammography system

    Science.gov (United States)

    Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats

    2010-04-01

    Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

  9. Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

    KAUST Repository

    Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim

    2016-01-01

    Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

  10. Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

    KAUST Repository

    Abdelhady, Amr, M.

    2016-01-06

    Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

  11. Global Learning Spectral Archive- A new Way to deal with Unknown Urban Spectra -

    Science.gov (United States)

    Jilge, M.; Heiden, U.; Habermeyer, M.; Jürgens, C.

    2015-12-01

    Rapid urbanization processes and the need of identifying urban materials demand urban planners and the remote sensing community since years. Urban planners cannot overcome the issue of up-to-date information of urban materials due to time-intensive fieldwork. Hyperspectral remote sensing can facilitate this issue by interpreting spectral signals to provide information of occurring materials. However, the complexity of urban areas and the occurrence of diverse urban materials vary due to regional and cultural aspects as well as the size of a city, which makes identification of surface materials a challenging analysis task. For the various surface material identification approaches, spectral libraries containing pure material spectra are commonly used, which are derived from field, laboratory or the hyperspectral image itself. One of the requirements for successful image analysis is that all spectrally different surface materials are represented by the library. Currently, a universal library, applicable in every urban area worldwide and taking each spectral variability into account, is and will not be existent. In this study, the issue of unknown surface material spectra and the demand of an urban site-specific spectral library is tackled by the development of a learning spectral archive tool. Starting with an incomplete library of labelled image spectra from several German cities, surface materials of pure image pixels will be identified in a hyperspectral image based on a similarity measure (e.g. SID-SAM). Additionally, unknown image spectra of urban objects are identified based on an object- and spectral-based-rule set. The detected unknown surface material spectra are entered with additional metadata, such as regional occurrence into the existing spectral library and thus, are reusable for further studies. Our approach is suitable for pure surface material detection of urban hyperspectral images that is globally applicable by taking incompleteness into account

  12. 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.

  13. 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

  14. Maximizing the spectral and energy efficiency of ARQ with a fixed outage probability

    KAUST Repository

    Hadjtaieb, Amir; Chelli, Ali; Alouini, Mohamed-Slim

    2015-01-01

    This paper studies the spectral and energy efficiency of automatic repeat request (ARQ) in Nakagami-m block-fading channels. The source encodes each packet into L similar sequences and transmits them to the destination in the L subsequent time slots

  15. RELIABILITY OF CONFOCAL MICROSCOPY SPECTRAL IMAGING SYSTEMS: USE OF MULTISPECTRAL BEADS

    Science.gov (United States)

    Background: There is a need for a standardized, impartial calibration, and validation protocol on confocal spectral imaging (CSI) microscope systems. To achieve this goal, it is necessary to have testing tools to provide a reproducible way to evaluate instrument performance. ...

  16. Camouflaged target detection based on polarized spectral features

    Science.gov (United States)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  17. An Integrative Object-Based Image Analysis Workflow for Uav Images

    Science.gov (United States)

    Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

    2016-06-01

    In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  18. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  19. A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT

    Science.gov (United States)

    Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo

    2016-11-01

    Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.

  20. 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.

  1. [The design and implementation of the web typical surface object spectral information system in arid areas based on .NET and SuperMap].

    Science.gov (United States)

    Xia, Jun; Tashpolat, Tiyip; Zhang, Fei; Ji, Hong-jiang

    2011-07-01

    The characteristic of object spectrum is not only the base of the quantification analysis of remote sensing, but also the main content of the basic research of remote sensing. The typical surface object spectral database in arid areas oasis is of great significance for applied research on remote sensing in soil salinization. In the present paper, the authors took the Ugan-Kuqa River Delta Oasis as an example, unified .NET and the SuperMap platform with SQL Server database stored data, used the B/S pattern and the C# language to design and develop the typical surface object spectral information system, and established the typical surface object spectral database according to the characteristics of arid areas oasis. The system implemented the classified storage and the management of typical surface object spectral information and the related attribute data of the study areas; this system also implemented visualized two-way query between the maps and attribute data, the drawings of the surface object spectral response curves and the processing of the derivative spectral data and its drawings. In addition, the system initially possessed a simple spectral data mining and analysis capabilities, and this advantage provided an efficient, reliable and convenient data management and application platform for the Ugan-Kuqa River Delta Oasis's follow-up study in soil salinization. Finally, It's easy to maintain, convinient for secondary development and practically operating in good condition.

  2. 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.

  3. Efficiency of Lu2SiO5:Ce (LSO) powder phosphor as X-ray to light converter under mammographic imaging conditions

    International Nuclear Information System (INIS)

    David, S.; Michail, C.; Valais, I.; Nikolopoulos, D.; Liaparinos, P.; Kalivas, N.; Kalatzis, I.; Toutountzis, A.; Efthimiou, N.; Loudos, G.; Sianoudis, I.; Cavouras, D.; Dimitropoulos, N.; Nomicos, C.D.; Kandarakis, I.; Panayiotakis, G.S.

    2007-01-01

    The aim of the present study was to examine the light emission efficiency of Lu 2 SiO 5 :Ce (LSO) powder scintillator under X-ray mammographic imaging conditions. Powder LSO scintillator has never been used in X-ray imaging. For the purposes of the present study, a 25 mg/cm 2 thick scintillating screen was prepared in our laboratory, by sedimentation of Lu 2 SiO 5 :Ce powder. Absolute luminescence efficiency measurements were performed within the range of X-ray tube voltages (22-49 kVp) used in mammographic applications. Parameters related to X-ray detection, i.e. the energy absorption efficiency (EAE) and the quantum detection efficiency (QDE) were calculated. A theoretical model, describing radiation and light transfer, was employed to fit experimental data and to estimate values of the intrinsic conversion efficiency and the light attenuation coefficients of the screen. The spectral compatibility of the LSO powder scintillator to mammographic X-ray films and to various electronic optical detectors was determined by performing light emission spectrum measurements and by taking into account the spectral sensitivity of the optical detectors. Results in the voltage range used in mammography showed that Lu 2 SiO 5 :Ce powder scintillator has approximately 10% higher values of QDE and 4.5% higher values of EAE than Gd 2 O 2 S:Tb

  4. Frequency interleaving towards spectrally efficient directly detected optical OFDM for next-generation optical access networks.

    Science.gov (United States)

    Mehedy, Lenin; Bakaul, Masuduzzaman; Nirmalathas, Ampalavanapillai

    2010-10-25

    In this paper, we theoretically analyze and demonstrate that spectral efficiency of a conventional direct detection based optical OFDM system (DDO-OFDM) can be improved significantly using frequency interleaving of adjacent DDO-OFDM channels where OFDM signal band of one channel occupies the spectral gap of other channel and vice versa. We show that, at optimum operating condition, the proposed technique can effectively improve the spectral efficiency of the conventional DDO-OFDM system as much as 50%. We also show that such a frequency interleaved DDO-OFDM system, with a bit rate of 48 Gb/s within 25 GHz bandwidth, achieves sufficient power budget after transmission over 25 km single mode fiber to be used in next-generation time-division-multiplexed passive optical networks (TDM-PON). Moreover, by applying 64- quadrature amplitude modulation (QAM), the system can be further scaled up to 96 Gb/s with a power budget sufficient for 1:16 split TDM-PON.

  5. Efficient generation of image chips for training deep learning algorithms

    Science.gov (United States)

    Han, Sanghui; Fafard, Alex; Kerekes, John; Gartley, Michael; Ientilucci, Emmett; Savakis, Andreas; Law, Charles; Parhan, Jason; Turek, Matt; Fieldhouse, Keith; Rovito, Todd

    2017-05-01

    Training deep convolutional networks for satellite or aerial image analysis often requires a large amount of training data. For a more robust algorithm, training data need to have variations not only in the background and target, but also radiometric variations in the image such as shadowing, illumination changes, atmospheric conditions, and imaging platforms with different collection geometry. Data augmentation is a commonly used approach to generating additional training data. However, this approach is often insufficient in accounting for real world changes in lighting, location or viewpoint outside of the collection geometry. Alternatively, image simulation can be an efficient way to augment training data that incorporates all these variations, such as changing backgrounds, that may be encountered in real data. The Digital Imaging and Remote Sensing Image Image Generation (DIRSIG) model is a tool that produces synthetic imagery using a suite of physics-based radiation propagation modules. DIRSIG can simulate images taken from different sensors with variation in collection geometry, spectral response, solar elevation and angle, atmospheric models, target, and background. Simulation of Urban Mobility (SUMO) is a multi-modal traffic simulation tool that explicitly models vehicles that move through a given road network. The output of the SUMO model was incorporated into DIRSIG to generate scenes with moving vehicles. The same approach was used when using helicopters as targets, but with slight modifications. Using the combination of DIRSIG and SUMO, we quickly generated many small images, with the target at the center with different backgrounds. The simulations generated images with vehicles and helicopters as targets, and corresponding images without targets. Using parallel computing, 120,000 training images were generated in about an hour. Some preliminary results show an improvement in the deep learning algorithm when real image training data are augmented with

  6. 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.

  7. Secure and Efficient Transmission of Hyperspectral Images for Geosciences Applications

    Science.gov (United States)

    Carpentieri, Bruno; Pizzolante, Raffaele

    2017-12-01

    Hyperspectral images are acquired through air-borne or space-borne special cameras (sensors) that collect information coming from the electromagnetic spectrum of the observed terrains. Hyperspectral remote sensing and hyperspectral images are used for a wide range of purposes: originally, they were developed for mining applications and for geology because of the capability of this kind of images to correctly identify various types of underground minerals by analysing the reflected spectrums, but their usage has spread in other application fields, such as ecology, military and surveillance, historical research and even archaeology. The large amount of data obtained by the hyperspectral sensors, the fact that these images are acquired at a high cost by air-borne sensors and that they are generally transmitted to a base, makes it necessary to provide an efficient and secure transmission protocol. In this paper, we propose a novel framework that allows secure and efficient transmission of hyperspectral images, by combining a reversible invisible watermarking scheme, used in conjunction with digital signature techniques, and a state-of-art predictive-based lossless compression algorithm.

  8. Spectral unmixing of hyperspectral data to map bauxite deposits

    Science.gov (United States)

    Shanmugam, Sanjeevi; Abhishekh, P. V.

    2006-12-01

    This paper presents a study about the potential of remote sensing in bauxite exploration in the Kolli hills of Tamilnadu state, southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM - DEM in this study. A new approach of spectral unmixing of ASTER image data delineated areas rich in alumina. Various geological and geomorphological parameters that control bauxite formation were also derived from the ASTER image. All these information, when integrated, showed that there are 16 cappings (including the existing mines) that satisfy most of the conditions favouring bauxitization in the Kolli Hills. The study concludes that spectral unmixing of hyperspectral satellite data in the VNIR and SWIR regions may be combined with the terrain parameters to get accurate information about bauxite deposits, including their quality.

  9. a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

    Science.gov (United States)

    Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

    2018-04-01

    Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

  10. Outpatient Imaging Efficiency - State

    Data.gov (United States)

    U.S. Department of Health & Human Services — Use of medical imaging - state data. These measures give you information about hospitals' use of medical imaging tests for outpatients. Examples of medical imaging...

  11. Contrast-enhanced spectral mammography with a photon-counting detector.

    Science.gov (United States)

    Fredenberg, Erik; Hemmendorff, Magnus; Cederström, Björn; Aslund, Magnus; Danielsson, Mats

    2010-05-01

    Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system. Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

  12. Contrast-enhanced spectral mammography with a photon-counting detector

    Energy Technology Data Exchange (ETDEWEB)

    Fredenberg, Erik; Hemmendorff, Magnus; Cederstroem, Bjoern; Aaslund, Magnus; Danielsson, Mats [Department of Physics, Royal Institute of Technology, AlbaNova, SE-106 91 Stockholm (Sweden); Sectra Mamea AB, Smidesvaegen 5, SE-171 41 Solna (Sweden); Department of Physics, Royal Institute of Technology, AlbaNova, SE-106 91 Stockholm (Sweden); Sectra Mamea AB, Smidesvaegen 5, SE-171 41 Solna (Sweden); Department of Physics, Royal Institute of Technology, AlbaNova, SE-106 91 Stockholm (Sweden)

    2010-05-15

    Purpose: Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. Methods: A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Results: Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another {approx}70%-90% improvement was found to be within reach for an optimized system. Conclusions: Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

  13. 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.

  14. Enhancing solar cell efficiency: the search for luminescent materials as spectral converters.

    Science.gov (United States)

    Huang, Xiaoyong; Han, Sanyang; Huang, Wei; Liu, Xiaogang

    2013-01-07

    Photovoltaic (PV) technologies for solar energy conversion represent promising routes to green and renewable energy generation. Despite relevant PV technologies being available for more than half a century, the production of solar energy remains costly, largely owing to low power conversion efficiencies of solar cells. The main difficulty in improving the efficiency of PV energy conversion lies in the spectral mismatch between the energy distribution of photons in the incident solar spectrum and the bandgap of a semiconductor material. In recent years, luminescent materials, which are capable of converting a broad spectrum of light into photons of a particular wavelength, have been synthesized and used to minimize the losses in the solar-cell-based energy conversion process. In this review, we will survey recent progress in the development of spectral converters, with a particular emphasis on lanthanide-based upconversion, quantum-cutting and down-shifting materials, for PV applications. In addition, we will also present technical challenges that arise in developing cost-effective high-performance solar cells based on these luminescent materials.

  15. Vegetation species composition and canopy architecture information expressed in leaf water absorption measured in the 1000 nm and 2200 spectral region by an imaging spectrometer

    Science.gov (United States)

    Green, Robert O.; Roberts, Dar A.

    1995-01-01

    Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper

  16. A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

    Science.gov (United States)

    He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

    2014-06-27

    The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed

  17. D Reconstruction from Uav-Based Hyperspectral Images

    Science.gov (United States)

    Liu, L.; Xu, L.; Peng, J.

    2018-04-01

    Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

  18. 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)

  19. High spectral resolution image of Barnacle Bill

    Science.gov (United States)

    1997-01-01

    The rover Sojourner's first target for measurement by the Alpha-Proton-Xray Spectrometer (APXS) was the rock named Barnacle Bill, located close to the ramp down which the rover made its egress from the lander. The full spectral capability of the Imager for Mars Pathfinder (IMP), consisting of 13 wavelength filters, was used to characterize the rock's surface. The measured area is relatively dark, and is shown in blue. Nearby on the rock surface, soil material is trapped in pits (shown in red).Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator. JPL is an operating division of the California Institute of Technology (Caltech).

  20. Energy Efficient LED Spectrally Matched Smart Lighting, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Innovative Imaging and Research and the University of Houston Clear Lake have teamed to develop a widely extensible, affordable, energy efficient, smart lighting...

  1. Beam alignment based on two-dimensional power spectral density of a near-field image.

    Science.gov (United States)

    Wang, Shenzhen; Yuan, Qiang; Zeng, Fa; Zhang, Xin; Zhao, Junpu; Li, Kehong; Zhang, Xiaolu; Xue, Qiao; Yang, Ying; Dai, Wanjun; Zhou, Wei; Wang, Yuanchen; Zheng, Kuixing; Su, Jingqin; Hu, Dongxia; Zhu, Qihua

    2017-10-30

    Beam alignment is crucial to high-power laser facilities and is used to adjust the laser beams quickly and accurately to meet stringent requirements of pointing and centering. In this paper, a novel alignment method is presented, which employs data processing of the two-dimensional power spectral density (2D-PSD) for a near-field image and resolves the beam pointing error relative to the spatial filter pinhole directly. Combining this with a near-field fiducial mark, the operation of beam alignment is achieved. It is experimentally demonstrated that this scheme realizes a far-field alignment precision of approximately 3% of the pinhole size. This scheme adopts only one near-field camera to construct the alignment system, which provides a simple, efficient, and low-cost way to align lasers.

  2. 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

  3. Rare-earth-doped materials with application to optical signal processing, quantum information science, and medical imaging technology

    Science.gov (United States)

    Cone, R. L.; Thiel, C. W.; Sun, Y.; Böttger, Thomas; Macfarlane, R. M.

    2012-02-01

    Unique spectroscopic properties of isolated rare earth ions in solids offer optical linewidths rivaling those of trapped single atoms and enable a variety of recent applications. We design rare-earth-doped crystals, ceramics, and fibers with persistent or transient "spectral hole" recording properties for applications including high-bandwidth optical signal processing where light and our solids replace the high-bandwidth portion of the electronics; quantum cryptography and information science including the goal of storage and recall of single photons; and medical imaging technology for the 700-900 nm therapeutic window. Ease of optically manipulating rare-earth ions in solids enables capturing complex spectral information in 105 to 108 frequency bins. Combining spatial holography and spectral hole burning provides a capability for processing high-bandwidth RF and optical signals with sub-MHz spectral resolution and bandwidths of tens to hundreds of GHz for applications including range-Doppler radar and high bandwidth RF spectral analysis. Simply stated, one can think of these crystals as holographic recording media capable of distinguishing up to 108 different colors. Ultra-narrow spectral holes also serve as a vibration-insensitive sub-kHz frequency reference for laser frequency stabilization to a part in 1013 over tens of milliseconds. The unusual properties and applications of spectral hole burning of rare earth ions in optical materials are reviewed. Experimental results on the promising Tm3+:LiNbO3 material system are presented and discussed for medical imaging applications. Finally, a new application of these materials as dynamic optical filters for laser noise suppression is discussed along with experimental demonstrations and theoretical modeling of the process.

  4. 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.

  5. 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.

  6. A spectral k-means approach to bright-field cell image segmentation.

    Science.gov (United States)

    Bradbury, Laura; Wan, Justin W L

    2010-01-01

    Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

  7. From spectral information to animal colour vision: experiments and concepts

    OpenAIRE

    Kelber, Almut; Osorio, Daniel

    2010-01-01

    Many animals use the spectral distribution of light to guide behaviour, but whether they have colour vision has been debated for over a century. Our strong subjective experience of colour and the fact that human vision is the paradigm for colour science inevitably raises the question of how we compare with other species. This article outlines four grades of ‘colour vision’ that can be related to the behavioural uses of spectral information, and perhaps to the underlying mechanisms. In the fir...

  8. Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

    Science.gov (United States)

    Yang, Jie; Messinger, David W.; Dube, Roger R.

    2018-03-01

    Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

  9. A spectral image processing algorithm for evaluating the influence of the illuminants on the reconstructed reflectance

    Science.gov (United States)

    Toadere, Florin

    2017-12-01

    A spectral image processing algorithm that allows the illumination of the scene with different illuminants together with the reconstruction of the scene's reflectance is presented. Color checker spectral image and CIE A (warm light 2700 K), D65 (cold light 6500 K) and Cree TW Series LED T8 (4000 K) are employed for scene illumination. Illuminants used in the simulations have different spectra and, as a result of their illumination, the colors of the scene change. The influence of the illuminants on the reconstruction of the scene's reflectance is estimated. Demonstrative images and reflectance showing the operation of the algorithm are illustrated.

  10. Colorimetry and efficiency of white LEDs: Spectral width dependence

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Elaine; Edwards, Paul R.; Martin, Robert W. [Department of Physics, SUPA, Strathclyde University, Glasgow (United Kingdom)

    2012-03-15

    The potential colour rendering capability and efficiency of white LEDs constructed by a combination of individual red, green and blue (RGB) LEDs are analysed. The conventional measurement of colour rendering quality, the colour rendering index (CRI), is used as well as a recently proposed colour quality scale (CQS), designed to overcome some of the limitations of CRI when narrow-band emitters are being studied. The colour rendering performance is maximised by variation of the peak emission wavelength and relative intensity of the component LEDs, with the constraint that the spectral widths follow those measured in actual devices. The highest CRI achieved is 89.5, corresponding to a CQS value of 79, colour temperature of 3800 K and a luminous efficacy of radiation (LER) of 365 lm/W. By allowing the spectral width of the green LED to vary the CRI can be raised to 90.9, giving values of 82.5 and 370 lm/W for the CQS and LER, respectively. The significance of these values are discussed in terms of optimising the possible performance of RGB LEDs. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  11. 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.

  12. Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control

    Directory of Open Access Journals (Sweden)

    Heekang Kim

    2016-07-01

    Full Text Available This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD or Complementary metal-Oxide-Semiconductor (CMOS camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC, the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs, High-intensity discharge (HID, and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM, Spectral Correlation Mapper (SCM, and Euclidean Distance Mapper (EDM. The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen.

  13. 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.

  14. Efficient and compact hyperspectral imager for space-borne applications

    Science.gov (United States)

    Pisani, Marco; Zucco, Massimo

    2017-11-01

    In the last decades Hyperspectral Imager (HI) have become irreplaceable space-borne instruments for an increasing number of applications. A number of HIs are now operative onboard (e.g. CHRIS on PROBA), others are going to be launched (e.g. PRISMA, EnMAP, HyspIRI), many others are at the breadboard level. The researchers goal is to realize HI with high spatial and spectral resolution, having low weight and contained dimensions. The most common HI technique is based on the use of a dispersive mean (a grating or a prism) or on the use of band pass filters (tunable or linear variable). These approaches have the advantages of allowing compact devices. Another approach is based on the use of interferometer based spectrometers (Michelson or Sagnac type). The advantage of the latter is a very high efficiency in light collection because of the well-known Felgett and Jaquinot principles.

  15. Automatic parquet block sorting using real-time spectral classification

    Science.gov (United States)

    Astrom, Anders; Astrand, Erik; Johansson, Magnus

    1999-03-01

    This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

  16. 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.

  17. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

    Directory of Open Access Journals (Sweden)

    Wei Gong

    2015-09-01

    Full Text Available The abilities of multispectral LiDAR (MSL as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

  18. Graph-Based Semi-Supervised Hyperspectral Image Classification Using Spatial Information

    Science.gov (United States)

    Jamshidpour, N.; Homayouni, S.; Safari, A.

    2017-09-01

    Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

  19. GRAPH-BASED SEMI-SUPERVISED HYPERSPECTRAL IMAGE CLASSIFICATION USING SPATIAL INFORMATION

    Directory of Open Access Journals (Sweden)

    N. Jamshidpour

    2017-09-01

    Full Text Available Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

  20. Spectral distribution of the efficiency of terahertz difference frequency generation upon collinear propagation of interacting waves in semiconductor crystals

    International Nuclear Information System (INIS)

    Orlov, Sergei N; Polivanov, Yurii N

    2007-01-01

    Dispersion phase matching curves and spectral distributions of the efficiency of difference frequency generation in the terahertz range are calculated for collinear propagation of interacting waves in zinc blende semiconductor crystals (ZnTe, CdTe, GaP, GaAs). The effect of the pump wavelength, the nonlinear crystal length and absorption in the terahertz range on the spectral distribution of the efficiency of difference frequency generation is analysed. (nonlinear optical phenomena)

  1. Efficient Multiple Exciton Generation Observed in Colloidal PbSe Quantum Dots with Temporally and Spectrally Resolved Intraband Excitation

    KAUST Repository

    Ji, Minbiao

    2009-03-11

    We have spectrally resolved the intraband transient absorption of photogenerated excitons to quantify the exciton population dynamics in colloidal PbSe quantum dots (QDs). These measurements demonstrate that the spectral distribution, as well as the amplitude, of the transient spectrum depends on the number of excitons excited in a QD. To accurately quantify the average number of excitons per QD, the transient spectrum must be spectrally integrated. With spectral integration, we observe efficient multiple exciton generation In colloidal PbSe QDs. © 2009 American Chemical Society.

  2. Efficient Multiple Exciton Generation Observed in Colloidal PbSe Quantum Dots with Temporally and Spectrally Resolved Intraband Excitation

    KAUST Repository

    Ji, Minbiao; Park, Sungnam; Connor, Stephen T.; Mokari, Taleb; Cui, Yi; Gaffney, Kelly J.

    2009-01-01

    We have spectrally resolved the intraband transient absorption of photogenerated excitons to quantify the exciton population dynamics in colloidal PbSe quantum dots (QDs). These measurements demonstrate that the spectral distribution, as well as the amplitude, of the transient spectrum depends on the number of excitons excited in a QD. To accurately quantify the average number of excitons per QD, the transient spectrum must be spectrally integrated. With spectral integration, we observe efficient multiple exciton generation In colloidal PbSe QDs. © 2009 American Chemical Society.

  3. Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

    Science.gov (United States)

    Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

    2018-01-01

    Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

  4. Orthogonal polarization spectral imaging of the microcirculation during acute hypervolemic hemodilution and epidural lidocaine injection

    NARCIS (Netherlands)

    van den Oever, Huub L. A.; Dzoljic, Misa; Ince, Can; Hollmann, Markus W.; Mokken, Fleur C.

    2006-01-01

    We used Orthogonal Polarization Spectral Imaging to examine the microcirculation of the vaginal mucosa in nine anesthetized patients during two consecutive anesthetic interventions: hypervolemic hemodilution using hydroxyethyl starch followed by thoracic epidural lidocaine. Images taken before and

  5. 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.

  6. LIFTERS-hyperspectral imaging at LLNL

    Energy Technology Data Exchange (ETDEWEB)

    Fields, D. [Lawrence Livermore National Lab., CA (United States); Bennett, C.; Carter, M.

    1994-11-15

    LIFTIRS, the Livermore Imaging Fourier Transform InfraRed Spectrometer, recently developed at LLNL, is an instrument which enables extremely efficient collection and analysis of hyperspectral imaging data. LIFTIRS produces a spatial format of 128x128 pixels, with spectral resolution arbitrarily variable up to a maximum of 0.25 inverse centimeters. Time resolution and spectral resolution can be traded off for each other with great flexibility. We will discuss recent measurements made with this instrument, and present typical images and spectra.

  7. 16 W output power by high-efficient spectral beam combining of DBR-tapered diode lasers

    DEFF Research Database (Denmark)

    Müller, André; Vijayakumar, Deepak; Jensen, Ole Bjarlin

    2011-01-01

    output power achieved by spectral beam combining of two single element tapered diode lasers. Since spectral beam combining does not affect beam propagation parameters, M2-values of 1.8 (fast axis) and 3.3 (slow axis) match the M2- values of the laser with lowest spatial coherence. The principle......Up to 16 W output power has been obtained using spectral beam combining of two 1063 nm DBR-tapered diode lasers. Using a reflecting volume Bragg grating, a combining efficiency as high as 93.7% is achieved, resulting in a single beam with high spatial coherence. The result represents the highest...... of spectral beam combining used in our experiments can be expanded to combine more than two tapered diode lasers and hence it is expected that the output power may be increased even further in the future....

  8. 16 W output power by high-efficient spectral beam combining of DBR-tapered diode lasers.

    Science.gov (United States)

    Müller, André; Vijayakumar, Deepak; Jensen, Ole Bjarlin; Hasler, Karl-Heinz; Sumpf, Bernd; Erbert, Götz; Andersen, Peter E; Petersen, Paul Michael

    2011-01-17

    Up to 16 W output power has been obtained using spectral beam combining of two 1063 nm DBR-tapered diode lasers. Using a reflecting volume Bragg grating, a combining efficiency as high as 93.7% is achieved, resulting in a single beam with high spatial coherence. The result represents the highest output power achieved by spectral beam combining of two single element tapered diode lasers. Since spectral beam combining does not affect beam propagation parameters, M2-values of 1.8 (fast axis) and 3.3 (slow axis) match the M2-values of the laser with lowest spatial coherence. The principle of spectral beam combining used in our experiments can be expanded to combine more than two tapered diode lasers and hence it is expected that the output power may be increased even further in the future.

  9. Spectral-spatial classification of hyperspectral data with mutual information based segmented stacked autoencoder approach

    Science.gov (United States)

    Paul, Subir; Nagesh Kumar, D.

    2018-04-01

    Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.

  10. 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.

  11. 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.

  12. Towards Efficient Spectral Converters through Materials Design for Luminescent Solar Devices.

    Science.gov (United States)

    McKenna, Barry; Evans, Rachel C

    2017-07-01

    Single-junction photovoltaic devices exhibit a bottleneck in their efficiency due to incomplete or inefficient harvesting of photons in the low- or high-energy regions of the solar spectrum. Spectral converters can be used to convert solar photons into energies that are more effectively captured by the photovoltaic device through a photoluminescence process. Here, recent advances in the fields of luminescent solar concentration, luminescent downshifting, and upconversion are discussed. The focus is specifically on the role that materials science has to play in overcoming barriers in the optical performance in all spectral converters and on their successful integration with both established (e.g., c-Si, GaAs) and emerging (perovskite, organic, dye-sensitized) cell types. Current challenges and emerging research directions, which need to be addressed for the development of next-generation luminescent solar devices, are also discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy.

    Science.gov (United States)

    Meisamy, Sina; Hines, Catherine D G; Hamilton, Gavin; Sirlin, Claude B; McKenzie, Charles A; Yu, Huanzhou; Brittain, Jean H; Reeder, Scott B

    2011-03-01

    To prospectively compare an investigational version of a complex-based chemical shift-based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantification of hepatic steatosis. This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-five patients (31 women, 24 men; age range, 24-71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction on fat quantification with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation (r(2)), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2 correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (significance level, P = .05) were used to determine whether estimated slopes and intercepts were significantly different from 1.0 and 0.0, respectively. Sensitivity and specificity for the classification of clinically significant steatosis were evaluated. Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction were used (r(2

  14. Outpatient Imaging Efficiency - National

    Data.gov (United States)

    U.S. Department of Health & Human Services — Use of medical imaging - national data. These measures give you information about hospitals' use of medical imaging tests for outpatients. Examples of medical...

  15. Color quality improvement of reconstructed images in color digital holography using speckle method and spectral estimation

    Science.gov (United States)

    Funamizu, Hideki; Onodera, Yusei; Aizu, Yoshihisa

    2018-05-01

    In this study, we report color quality improvement of reconstructed images in color digital holography using the speckle method and the spectral estimation. In this technique, an object is illuminated by a speckle field and then an object wave is produced, while a plane wave is used as a reference wave. For three wavelengths, the interference patterns of two coherent waves are recorded as digital holograms on an image sensor. Speckle fields are changed by moving a ground glass plate in an in-plane direction, and a number of holograms are acquired to average the reconstructed images. After the averaging process of images reconstructed from multiple holograms, we use the Wiener estimation method for obtaining spectral transmittance curves in reconstructed images. The color reproducibility in this method is demonstrated and evaluated using a Macbeth color chart film and staining cells of onion.

  16. Spectrally resolved digital holography using a white light LED

    Science.gov (United States)

    Claus, D.; Pedrini, G.; Buchta, D.; Osten, W.

    2017-06-01

    This paper introduces the concept of spectrally resolved digital holography. The measurement principle and the analysis of the data will be discussed in detail. The usefulness of spectrally resolved digital holography is demonstrated for colour imaging and optical metrology with regards to the recovery of modulus information and phase information, respectively. The phase information will be used to measure the shape of an object via the application of the dual wavelength method. Based on the large degree of data available, multiple speckle de-correlated dual wavelength phase maps can be obtained, which when averaged result in a signal to noise ratio improvement.

  17. Photoreceptor layer map using spectral-domain optical coherence tomography.

    Science.gov (United States)

    Lee, Ji Eun; Lim, Dae Won; Bae, Han Yong; Park, Hyun Jin

    2009-12-01

    To develop a novel method for analysis of the photoreceptor layer map (PLM) generated using spectral-domain optical coherence tomography (OCT). OCT scans were obtained from 20 eyes, 10 with macular holes (MH) and 10 with central serous chorioretinopathy (CSC) using the Macular Cube (512 x 128) protocol of the Cirrus HD-OCT (Carl Zeiss). The scanned data were processed using embedded tools of the advanced visualization. A partial thickness OCT fundus image of the photoreceptor layer was generated by setting the region of interest to a 50-microm thick layer that was parallel and adjacent to the retinal pigment epithelium. The resulting image depicted the photoreceptor layer as a map of the reflectivity in OCT. The PLM was compared with fundus photography, auto-fluorescence, tomography, and retinal thickness map. The signal from the photoreceptor layer of every OCT scan in each case was demonstrated as a single image of PLM in a fundus photograph fashion. In PLM images, detachment of the sensory retina is depicted as a hypo-reflective area, which represents the base of MH and serous detachment in CSC. Relative hypo-reflectivity, which was also noted at closed MH and at recently reattached retina in CSC, was associated with reduced signal from the junction between the inner and outer segments of photoreceptors in OCT images. Using PLM, changes in the area of detachment and reflectivity of the photoreceptor layer could be efficiently monitored. The photoreceptor layer can be analyzed as a map using spectral-domain OCT. In the treatment of both MH and CSC, PLM may provide new pathological information about the photoreceptor layer to expand our understanding of these diseases.

  18. Analytical bounds on the area spectral efficiency of uplink heterogeneous networks over generalized fading channels

    KAUST Repository

    Shakir, Muhammad; Tabassum, Hina; Alouini, Mohamed-Slim

    2014-01-01

    Heterogeneous networks (HetNets) are envisioned to enable next-generation cellular networks by providing higher spectral and energy efficiency. A HetNet is typically composed of multiple radio access technologies where several low-power low

  19. Composite multilobe descriptors for cross-spectral recognition of full and partial face

    Science.gov (United States)

    Cao, Zhicheng; Schmid, Natalia A.; Bourlai, Thirimachos

    2016-08-01

    Cross-spectral image matching is a challenging research problem motivated by various applications, including surveillance, security, and identity management in general. An example of this problem includes cross-spectral matching of active infrared (IR) or thermal IR face images against a dataset of visible light images. A summary of recent developments in the field of cross-spectral face recognition by the authors is presented. In particular, it describes the original form and two variants of a local operator named composite multilobe descriptor (CMLD) for facial feature extraction with the purpose of cross-spectral matching of near-IR, short-wave IR, mid-wave IR, and long-wave IR to a gallery of visible light images. The experiments demonstrate that the variants of CMLD outperform the original CMLD and other recently developed composite operators used for comparison. In addition to different IR spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated. Performance of CMLD I to III is evaluated for each of the three cases of distances. The newly developed operators, CMLD I to III, are further utilized to conduct a study on cross-spectral partial face recognition where different facial regions are compared in terms of the amount of useful information they contain for the purpose of conducting cross-spectral face recognition. The experimental results show that among three facial regions considered in the experiments the eye region is the most informative for all IR spectra at all standoff distances.

  20. 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.

  1. Spectral CT of carotid atherosclerotic plaque: comparison with histology

    Energy Technology Data Exchange (ETDEWEB)

    Zainon, R.; Doesburg, R.M. [University of Canterbury, Department of Physics and Astronomy, Christchurch (New Zealand); Ronaldson, J.P.; Gieseg, S.P. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); Janmale, T. [University of Canterbury, Free Radical Biochemistry Laboratory, School of Biological Sciences, Christchurch (New Zealand); Scott, N.J. [University of Otago, Department of Medicine, Christchurch (New Zealand); Buckenham, T.M. [University of Otago, Department of Academic Radiology, Christchurch (New Zealand); Butler, A.P.H. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); University of Otago, Department of Academic Radiology, Christchurch (New Zealand); University of Canterbury, Department of Electrical and Computer Engineering, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); Butler, P.H. [University of Canterbury, Department of Physics and Astronomy, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); Roake, J.A. [Christchurch Hospital, Department of Vascular, Endovascular and Transplant Surgery, Christchurch (New Zealand); Anderson, N.G. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); University of Otago, Department of Academic Radiology, Christchurch (New Zealand); University of Otago, Christchurch, Department of Radiology, PO Box 4345, Christchurch (New Zealand)

    2012-12-15

    To distinguish components of vulnerable atherosclerotic plaque by imaging their energy response using spectral CT and comparing images with histology. After spectroscopic calibration using phantoms of plaque surrogates, excised human carotid atherosclerotic plaques were imaged using MARS CT using a photon-processing detector with a silicon sensor layer and microfocus X-ray tube (50 kVp, 0.5 mA) at 38-{mu}m voxel size. The plaques were imaged, sectioned and re-imaged using four threshold energies: 10, 16, 22 and 28 keV; then sequentially stained with modified Von Kossa, Perl's Prussian blue and Oil-Red O, and photographed. Relative Hounsfield units across the energies were entered into a linear algebraic material decomposition model to identify the unknown plaque components. Lipid, calcium, iron and water-like components of plaque have distinguishable energy responses to X-ray, visible on spectral CT images. CT images of the plaque surface correlated very well with histological photographs. Calcium deposits (>1,000 {mu}m) in plaque are larger than iron deposits (<100 {mu}m), but could not be distinguished from each other within the same voxel using the energy range available. Spectral CT displays energy information in image form at high spatial resolution, enhancing the intrinsic contrast of lipid, calcium and iron within atheroma. (orig.)

  2. 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.

  3. Application of a spectral sky in Radiance for daylighting calculations including non-image-forming light effects

    NARCIS (Netherlands)

    Khademagha, P.; Aries, M.B.C.; Rosemann, A.L.P.; van Loenen, E.J.

    2016-01-01

    Daylight is dynamic and rich in the blue part of the spectrum. To date, the spectral composition of daylight is ignored in sky models used in Radiance. Spectral sky composition is particularly important when non-image-forming (NIF) light effects are concerned, since the action spectrum for these

  4. Constellation Shaping for Fiber-optic Channels with QAM and High Spectral Efficiency

    DEFF Research Database (Denmark)

    Yankov, Metodi Plamenov; Zibar, Darko; Larsen, Knud J.

    2014-01-01

    In this letter the fiber-optic communication channel with Quadrature Amplitude Modulation (QAM) input constella- tion is treated. Using probabilistic shaping, we show that high order QAM constellations can achieve and slightly exceed the lower bound on the channel capacity, set by ring constellat......In this letter the fiber-optic communication channel with Quadrature Amplitude Modulation (QAM) input constella- tion is treated. Using probabilistic shaping, we show that high order QAM constellations can achieve and slightly exceed the lower bound on the channel capacity, set by ring...... constellations in [1]. We then propose a mapping function for turbo coded bit interleaved coded modulation based on optimization of the mu- tual information between the channel input and output. Using this mapping, spectral efficiency as high as 6.5 bits/s/Hz/polarization is achieved on a simulated single...... channel long-haul fiber-optical link excluding the pilot overhead, used for synchronization, and taking into account frequency and phase mismatch impairments, as well as laser phase noise and analog-to-digital conversion quantization impairments. The simulations suggest that major improvements can...

  5. Scalable modulation technology and the tradeoff of reach, spectral efficiency, and complexity

    Science.gov (United States)

    Bosco, Gabriella; Pilori, Dario; Poggiolini, Pierluigi; Carena, Andrea; Guiomar, Fernando

    2017-01-01

    Bandwidth and capacity demand in metro, regional, and long-haul networks is increasing at several tens of percent per year, driven by video streaming, cloud computing, social media and mobile applications. To sustain this traffic growth, an upgrade of the widely deployed 100-Gbit/s long-haul optical systems, based on polarization multiplexed quadrature phase-shift keying (PM-QPSK) modulation format associated with coherent detection and digital signal processing (DSP), is mandatory. In fact, optical transport techniques enabling a per-channel bit rate beyond 100 Gbit/s have recently been the object of intensive R and D activities, aimed at both improving the spectral efficiency and lowering the cost per bit in fiber transmission systems. In this invited contribution, we review the different available options to scale the per-channel bit-rate to 400 Gbit/s and beyond, i.e. symbol-rate increase, use of higher-order quadrature amplitude modulation (QAM) modulation formats and use of super-channels with DSP-enabled spectral shaping and advanced multiplexing technologies. In this analysis, trade-offs of system reach, spectral efficiency and transceiver complexity are addressed. Besides scalability, next generation optical networks will require a high degree of flexibility in the transponders, which should be able to dynamically adapt the transmission rate and bandwidth occupancy to the light path characteristics. In order to increase the flexibility of these transponders (often referred to as "flexponders"), several advanced modulation techniques have recently been proposed, among which sub-carrier multiplexing, hybrid formats (over time, frequency and polarization), and constellation shaping. We review these techniques, highlighting their limits and potential in terms of performance, complexity and flexibility.

  6. Spectral gamuts and spectral gamut mapping

    Science.gov (United States)

    Rosen, Mitchell R.; Derhak, Maxim W.

    2006-01-01

    All imaging devices have two gamuts: the stimulus gamut and the response gamut. The response gamut of a print engine is typically described in CIE colorimetry units, a system derived to quantify human color response. More fundamental than colorimetric gamuts are spectral gamuts, based on radiance, reflectance or transmittance units. Spectral gamuts depend on the physics of light or on how materials interact with light and do not involve the human's photoreceptor integration or brain processing. Methods for visualizing a spectral gamut raise challenges as do considerations of how to utilize such a data-set for producing superior color reproductions. Recent work has described a transformation of spectra reduced to 6-dimensions called LabPQR. LabPQR was designed as a hybrid space with three explicit colorimetric axes and three additional spectral reconstruction axes. In this paper spectral gamuts are discussed making use of LabPQR. Also, spectral gamut mapping is considered in light of the colorimetric-spectral duality of the LabPQR space.

  7. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-12-16

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

  8. ARCTIS — A MATLAB® Toolbox for Archaeological Imaging Spectroscopy

    Directory of Open Access Journals (Sweden)

    Clement Atzberger

    2014-09-01

    Full Text Available Imaging spectroscopy acquires imagery in hundreds or more narrow contiguous spectral bands. This offers unprecedented information for archaeological research. To extract the maximum of useful archaeological information from it, however, a number of problems have to be solved. Major problems relate to data redundancy and the visualization of the large amount of data. This makes data mining approaches necessary, as well as efficient data visualization tools. Additional problems relate to data quality. Indeed, the upwelling electromagnetic radiation is recorded in small spectral bands that are only about ten nanometers wide. The signal received by the sensor is, thus quite low compared to sensor noise and possible atmospheric perturbations. The often small, instantaneous field of view (IFOV—essential for archaeologically relevant imaging spectrometer datasets—further limits the useful signal stemming from the ground. The combination of both effects makes radiometric smoothing techniques mandatory. The present study details the functionality of a MATLAB®-based toolbox, called ARCTIS (ARChaeological Toolbox for Imaging Spectroscopy, for filtering, enhancing, analyzing, and visualizing imaging spectrometer datasets. The toolbox addresses the above-mentioned problems. Its Graphical User Interface (GUI is designed to allow non-experts in remote sensing to extract a wealth of information from imaging spectroscopy for archaeological research. ARCTIS will be released under creative commons license, free of charge, via website (http://luftbildarchiv.univie.ac.at.

  9. Ontology-based classification of remote sensing images using spectral rules

    Science.gov (United States)

    Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

    2017-05-01

    Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

  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. 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. 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

  13. The importance of spectral separation: an assessment of dual-energy spectral separation for quantitative ability and dose efficiency.

    Science.gov (United States)

    Krauss, Bernhard; Grant, Katharine L; Schmidt, Bernhard T; Flohr, Thomas G

    2015-02-01

    One method to acquire dual-energy (DE) computed tomography (CT) data is to perform CT scans at 2 different x-ray tube voltages, typically 80 and 140 kV, either as 2 separate scans, by means of rapid kV switching, or with the use of 2 x-ray sources as in dual-source CT (DSCT) systems. In DSCT, it is possible to improve spectral separation with tin prefiltration (Sn) of the high-kV beam. Recently, x-ray tube voltages beyond the established range of 80 to 140 kV were commercially introduced, which enable additional voltage combinations for DE acquisitions, such as 80/150 Sn or 90/150 Sn kV. Here, we investigate the DE performance of several x-ray tube voltages and prefilter combinations on 2 DSCT scanners and the impact of the spectra on quantitative analysis and dose efficiency. Circular phantoms of different sizes (10-40 cm in diameter) equipped with cylindrical inserts containing water and diluted iodine contrast agent (14.5 mg/cm) were scanned using 2 different DSCT systems (SOMATOM Definition Flash and SOMATOM Force; Siemens AG, Forchheim, Germany). Five x-ray tube voltage combinations (80/140 Sn, 100/140 Sn, 80/150 Sn, 90/150 Sn, and 100/150 Sn kV) were investigated, and the results were compared with the previous standard acquisition technique (80/140 kV). As an example, 80/140 Sn kV means that 1 x-ray tube of the DSCT system was operated at 80 kV, whereas the other was operated at 140 kV with additional tin prefiltration (Sn). Dose values in terms of computed tomography dose index (CTDIvol) were kept constant between the different voltage combinations but adjusted with regard to object size according to automatic exposure control recommendations. Reconstructed images were processed using linear blending of the low- and high-kV CT images to combined images, as well as 3-material decomposition techniques to generate virtual noncontrast (VNC) images and iodine images. Contrast and pixel noise were evaluated, as well as DE ratios, which are defined as the CT value

  14. Single-energy pediatric chest computed tomography with spectral filtration at 100 kVp: effects on radiation parameters and image quality

    Energy Technology Data Exchange (ETDEWEB)

    Bodelle, Boris; Fischbach, Constanze; Booz, Christian; Yel, Ibrahim; Frellesen, Claudia; Kaup, Moritz; Beeres, Martin; Vogl, Thomas J.; Scholtz, Jan-Erik [Goethe University of Frankfurt, Department of Diagnostic and Interventional Radiology, Frankfurt (Germany)

    2017-06-15

    Most of the applied radiation dose at CT is in the lower photon energy range, which is of limited diagnostic importance. To investigate image quality and effects on radiation parameters of 100-kVp spectral filtration single-energy chest CT using a tin-filter at third-generation dual-source CT in comparison to standard 100-kVp chest CT. Thirty-three children referred for a non-contrast chest CT performed on a third-generation dual-source CT scanner were examined at 100 kVp with a dedicated tin filter with a tube current-time product resulting in standard protocol dose. We compared resulting images with images from children examined using standard single-source chest CT at 100 kVp. We assessed objective and subjective image quality and compared radiation dose parameters. Radiation dose was comparable for children 5 years old and younger, and it was moderately decreased for older children when using spectral filtration (P=0.006). Effective tube current increased significantly (P=0.0001) with spectral filtration, up to a factor of 10. Signal-to-noise ratio and image noise were similar for both examination techniques (P≥0.06). Subjective image quality showed no significant differences (P≥0.2). Using 100-kVp spectral filtration chest CT in children by means of a tube-based tin-filter on a third-generation dual-source CT scanner increases effective tube current up to a factor of 10 to provide similar image quality at equivalent dose compared to standard single-source CT without spectral filtration. (orig.)

  15. Single-energy pediatric chest computed tomography with spectral filtration at 100 kVp: effects on radiation parameters and image quality

    International Nuclear Information System (INIS)

    Bodelle, Boris; Fischbach, Constanze; Booz, Christian; Yel, Ibrahim; Frellesen, Claudia; Kaup, Moritz; Beeres, Martin; Vogl, Thomas J.; Scholtz, Jan-Erik

    2017-01-01

    Most of the applied radiation dose at CT is in the lower photon energy range, which is of limited diagnostic importance. To investigate image quality and effects on radiation parameters of 100-kVp spectral filtration single-energy chest CT using a tin-filter at third-generation dual-source CT in comparison to standard 100-kVp chest CT. Thirty-three children referred for a non-contrast chest CT performed on a third-generation dual-source CT scanner were examined at 100 kVp with a dedicated tin filter with a tube current-time product resulting in standard protocol dose. We compared resulting images with images from children examined using standard single-source chest CT at 100 kVp. We assessed objective and subjective image quality and compared radiation dose parameters. Radiation dose was comparable for children 5 years old and younger, and it was moderately decreased for older children when using spectral filtration (P=0.006). Effective tube current increased significantly (P=0.0001) with spectral filtration, up to a factor of 10. Signal-to-noise ratio and image noise were similar for both examination techniques (P≥0.06). Subjective image quality showed no significant differences (P≥0.2). Using 100-kVp spectral filtration chest CT in children by means of a tube-based tin-filter on a third-generation dual-source CT scanner increases effective tube current up to a factor of 10 to provide similar image quality at equivalent dose compared to standard single-source CT without spectral filtration. (orig.)

  16. Gold nanoparticles : A novel application of spectral imaging in proteomics - preliminary results

    NARCIS (Netherlands)

    Dietrich, H.R.C.; Young, I.T.; Garini, Y.

    2005-01-01

    The intense research in proteomics is demanding for fast, reliable and easy-to-use methods in order to study the proteome. In this proceeding we report the development of such a novel research tool based on spectral imaging and Resonance Light Scattering gold particles. This method will allow the

  17. Making Image More Energy Efficient for OLED Smart Devices

    Directory of Open Access Journals (Sweden)

    Deguang Li

    2016-01-01

    Full Text Available Now, more and more mobile smart devices are emerging massively; energy consumption of these devices has become an important consideration due to the limitation of battery capacity. Displays are the dominant energy consuming component of battery-operated devices, giving rise to organic light-emitting diode (OLED as a new promising display technology, which consumes different power when displaying different content due to their emissive nature. Based on this property, we propose an approach to improve image energy efficiency on OLED displays by perceiving image content. The key idea of our approach is to eliminate undesired details while preserving the region of interest of the image by leveraging the color and spatial information. First, we use edge detection algorithm to extract region of interest (ROI of an image. Next, we gradually change luminance and saturation of region of noninterest (NON-ROI of the image. Then we perform detailed experiment and case study to validate our approach; experiment results show that our approach can save 22.5% energy on average while preserving high quality of the image.

  18. 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

  19. (LMRG): Microscope Resolution, Objective Quality, Spectral Accuracy and Spectral Un-mixing

    Science.gov (United States)

    Bayles, Carol J.; Cole, Richard W.; Eason, Brady; Girard, Anne-Marie; Jinadasa, Tushare; Martin, Karen; McNamara, George; Opansky, Cynthia; Schulz, Katherine; Thibault, Marc; Brown, Claire M.

    2012-01-01

    The second study by the LMRG focuses on measuring confocal laser scanning microscope (CLSM) resolution, objective lens quality, spectral imaging accuracy and spectral un-mixing. Affordable test samples for each aspect of the study were designed, prepared and sent to 116 labs from 23 countries across the globe. Detailed protocols were designed for the three tests and customized for most of the major confocal instruments being used by the study participants. One protocol developed for measuring resolution and objective quality was recently published in Nature Protocols (Cole, R. W., T. Jinadasa, et al. (2011). Nature Protocols 6(12): 1929–1941). The first study involved 3D imaging of sub-resolution fluorescent microspheres to determine the microscope point spread function. Results of the resolution studies as well as point spread function quality (i.e. objective lens quality) from 140 different objective lenses will be presented. The second study of spectral accuracy looked at the reflection of the laser excitation lines into the spectral detection in order to determine the accuracy of these systems to report back the accurate laser emission wavelengths. Results will be presented from 42 different spectral confocal systems. Finally, samples with double orange beads (orange core and orange coating) were imaged spectrally and the imaging software was used to un-mix fluorescence signals from the two orange dyes. Results from 26 different confocal systems will be summarized. Time will be left to discuss possibilities for the next LMRG study.

  20. 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

  1. Delineation of subsurface hydrocarbon contamination at a former hydrogenation plant using spectral induced polarization imaging

    Science.gov (United States)

    Flores Orozco, Adrián; Kemna, Andreas; Oberdörster, Christoph; Zschornack, Ludwig; Leven, Carsten; Dietrich, Peter; Weiss, Holger

    2012-08-01

    Broadband spectral induced polarization (SIP) measurements were conducted at a former hydrogenation plant in Zeitz (NE Germany) to investigate the potential of SIP imaging to delineate areas with different BTEX (benzene, toluene, ethylbenzene, and xylene) concentrations. Conductivity images reveal a poor correlation with the distribution of contaminants; whereas phase images exhibit two main anomalies: low phase shift values (product (BTEX concentrations > 1.7 g/l), and higher phase values for lower BTEX concentrations. Moreover, the spectral response of the areas with high BTEX concentration and free-phase products reveals a flattened spectrum in the low frequencies (< 40 Hz), while areas with lower BTEX concentrations exhibit a response characterized by a frequency peak. The SIP response was modelled using a Debye decomposition to compute images of the median relaxation-time. Consistent with laboratory studies, we observed an increase in the relaxation-time associated with an increase in BTEX concentrations. Measurements were also collected in the time domain (TDIP), revealing imaging results consistent with those obtained for frequency domain (SIP) measurements. Results presented here demonstrate the potential of the SIP imaging method to discriminate source and plume of dissolved contaminants at BTEX contaminated sites.

  2. SPATIAL-SPECTRAL CLASSIFICATION BASED ON THE UNSUPERVISED CONVOLUTIONAL SPARSE AUTO-ENCODER FOR HYPERSPECTRAL REMOTE SENSING IMAGERY

    Directory of Open Access Journals (Sweden)

    X. Han

    2016-06-01

    Full Text Available Current hyperspectral remote sensing imagery spatial-spectral classification methods mainly consider concatenating the spectral information vectors and spatial information vectors together. However, the combined spatial-spectral information vectors may cause information loss and concatenation deficiency for the classification task. To efficiently represent the spatial-spectral feature information around the central pixel within a neighbourhood window, the unsupervised convolutional sparse auto-encoder (UCSAE with window-in-window selection strategy is proposed in this paper. Window-in-window selection strategy selects the sub-window spatial-spectral information for the spatial-spectral feature learning and extraction with the sparse auto-encoder (SAE. Convolution mechanism is applied after the SAE feature extraction stage with the SAE features upon the larger outer window. The UCSAE algorithm was validated by two common hyperspectral imagery (HSI datasets – Pavia University dataset and the Kennedy Space Centre (KSC dataset, which shows an improvement over the traditional hyperspectral spatial-spectral classification methods.

  3. Information efficiency in visual communication

    Science.gov (United States)

    Alter-Gartenberg, Rachel; Rahman, Zia-Ur

    1993-01-01

    This paper evaluates the quantization process in the context of the end-to-end performance of the visual-communication channel. Results show that the trade-off between data transmission and visual quality revolves around the information in the acquired signal, not around its energy. Improved information efficiency is gained by frequency dependent quantization that maintains the information capacity of the channel and reduces the entropy of the encoded signal. Restorations with energy bit-allocation lose both in sharpness and clarity relative to restorations with information bit-allocation. Thus, quantization with information bit-allocation is preferred for high information efficiency and visual quality in optimized visual communication.

  4. Information efficiency in visual communication

    Science.gov (United States)

    Alter-Gartenberg, Rachel; Rahman, Zia-ur

    1993-08-01

    This paper evaluates the quantization process in the context of the end-to-end performance of the visual-communication channel. Results show that the trade-off between data transmission and visual quality revolves around the information in the acquired signal, not around its energy. Improved information efficiency is gained by frequency dependent quantization that maintains the information capacity of the channel and reduces the entropy of the encoded signal. Restorations with energy bit-allocation lose both in sharpness and clarity relative to restorations with information bit-allocation. Thus, quantization with information bit-allocation is preferred for high information efficiency and visual quality in optimized visual communication.

  5. 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.

  6. PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA

    Directory of Open Access Journals (Sweden)

    Y. Z. Gu

    2017-09-01

    Full Text Available Massive trajectory data contains wealth useful information and knowledge. Spectral clustering, which has been shown to be effective in finding clusters, becomes an important clustering approaches in the trajectory data mining. However, the traditional spectral clustering lacks the temporal expansion on the algorithm and limited in its applicability to large-scale problems due to its high computational complexity. This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment carried out on the massive taxi trajectory dataset in Wuhan city, China.

  7. Quantification of Hepatic Steatosis with T1-independent, T2*-corrected MR Imaging with Spectral Modeling of Fat: Blinded Comparison with MR Spectroscopy

    Science.gov (United States)

    Hines, Catherine D. G.; Hamilton, Gavin; Sirlin, Claude B.; McKenzie, Charles A.; Yu, Huanzhou; Brittain, Jean H.; Reeder, Scott B.

    2011-01-01

    Purpose: To prospectively compare an investigational version of a complex-based chemical shift–based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantification of hepatic steatosis. Materials and Methods: This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-five patients (31 women, 24 men; age range, 24–71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2* correction, spectral modeling of fat, and magnitude fitting for eddy current correction on fat quantification with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation (r2), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2* correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (significance level, P = .05) were used to determine whether estimated slopes and intercepts were significantly different from 1.0 and 0.0, respectively. Sensitivity and specificity for the classification of clinically significant steatosis were evaluated. Results: Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2* correction, spectral modeling of fat, and magnitude

  8. 3D imaging of intrinsic crystalline defects in zinc oxide by spectrally resolved two-photon fluorescence microscopy

    Science.gov (United States)

    Al-Tabich, A.; Inami, W.; Kawata, Y.; Jablonski, R.; Worasawat, S.; Mimura, H.

    2017-05-01

    We present a method for three-dimensional intrinsic defect imaging in zinc oxide (ZnO) by spectrally resolved two-photon fluorescence microscopy, based on the previously presented method of observing a photoluminescence distribution in wide-gap semiconductor crystals [Noor et al., Appl. Phys. Lett. 92(16), 161106 (2008)]. A tightly focused light beam radiated by a titanium-sapphire laser is used to obtain a two-photon excitation of selected area of the ZnO sample. Photoluminescence intensity of a specific spectral range is then selected by optical band pass filters and measured by a photomultiplier tube. Reconstruction of the specimen image is done by scanning the volume of interest by a piezoelectric positioning stage and measuring the spectrally resolved photoluminescence intensity at each point. The method has been proved to be effective at locating intrinsic defects of the ZnO crystalline structure in the volume of the crystal. The method was compared with other defect imaging and 3D imaging techniques like scanning tunneling microscopy and confocal microscopy. In both cases, our method shows superior penetration abilities and, as the only method, allows location of the defects of the chosen type in 3D. In this paper, we present the results of oxygen vacancies and zinc antisites imaging in ZnO nanorods.

  9. Spectral domain optical coherence tomography imaging of spectacular ecdysis in the royal python (Python regius).

    Science.gov (United States)

    Tusler, Charlotte A; Maggs, David J; Kass, Philip H; Paul-Murphy, Joanne R; Schwab, Ivan R; Murphy, Christopher J

    2015-01-01

    To describe using spectral domain optical coherence tomography (SD-OCT), digital slit-lamp biomicroscopy, and external photography, changes in the ophidian cuticle, spectacle, and cornea during ecdysis. Four normal royal pythons (Python regius). Snakes were assessed once daily throughout a complete shed cycle using nasal, axial, and temporal SD-OCT images, digital slit-lamp biomicroscopy, and external photography. Spectral domain optical coherence tomography (SD-OCT) images reliably showed the spectacular cuticle and stroma, subcuticular space (SCS), cornea, anterior chamber, iris, and Schlemm's canal. When visible, the subspectacular space (SSS) was more distended peripherally than axially. Ocular surface changes throughout ecdysis were relatively conserved among snakes at all three regions imaged. From baseline (7 days following completion of a full cycle), the spectacle gradually thickened before separating into superficial cuticular and deep, hyper-reflective stromal components, thereby creating the SCS. During spectacular separation, the stroma regained original reflectivity, and multiple hyper-reflective foci (likely fragments from the cuticular-stromal interface) were noted within the SCS. The cornea was relatively unchanged in character or thickness throughout all stages of ecdysis. Slit-lamp images did not permit observation of these changes. Spectral domain optical coherence tomography (SD-OCT) provided excellent high-resolution images of the snake anterior segment, and especially the cuticle, spectacle, and cornea of manually restrained normal snakes at all stages of ecdysis and warrants investigation in snakes with anterior segment disease. The peripheral spectacle may be the preferred entry point for diagnostic or therapeutic injections into the SSS and for initiating spectacular surgery. © 2014 American College of Veterinary Ophthalmologists.

  10. Compression of Multispectral Images with Comparatively Few Bands Using Posttransform Tucker Decomposition

    Directory of Open Access Journals (Sweden)

    Jin Li

    2014-01-01

    Full Text Available Up to now, data compression for the multispectral charge-coupled device (CCD images with comparatively few bands (MSCFBs is done independently on each multispectral channel. This compression codec is called a “monospectral compressor.” The monospectral compressor does not have a removing spectral redundancy stage. To fill this gap, we propose an efficient compression approach for MSCFBs. In our approach, the one dimensional discrete cosine transform (1D-DCT is performed on spectral dimension to exploit the spectral information, and the posttransform (PT in 2D-DWT domain is performed on each spectral band to exploit the spatial information. A deep coupling approach between the PT and Tucker decomposition (TD is proposed to remove residual spectral redundancy between bands and residual spatial redundancy of each band. Experimental results on multispectral CCD camera data set show that the proposed compression algorithm can obtain a better compression performance and significantly outperforms the traditional compression algorithm-based TD in 2D-DWT and 3D-DCT domain.

  11. Information asymmetries, information externalities, oil companies strategies and oil exploration information efficiency

    International Nuclear Information System (INIS)

    Nyouki, E.

    1998-07-01

    Both for economics (in general) and energy economics matters, it is important to reach oil exploration efficiency. To achieve this aim, a pragmatic approach is to use the concept of information efficiency which means that the different tracts have to be drilled in the decreasing order of estimated profitabilities, estimations being made on the basis of the best (in the sense of reliability) available information. What does 'best available information' mean? It corresponds either to the information held by the most experienced oil companies (due to the existence of information asymmetries to the profit of these companies), or to information revealed by the drilling and which allows to revise probabilities of success on neighboring tracts with similar geological features (due to the existence of information externalities). In consideration of these information asymmetries and externalities, we will say that exploration is information efficient when. -- on the one hand, initial exploration choices are directed by the most experienced companies, - and, on the other hand, during the drilling phase, in the face of the information externality, companies adopt a sequential drilling, i.e. excluding both over-investment and strategic under-investment. The topic we deal with in this thesis is then to know if oil companies, when they are put in normal competition conditions, are likely to make emerge a state of information efficiency in exploration, the analysis being conducted theoretically and empirically. (author)

  12. 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.

  13. Near infrared spectral imaging of explosives using a tunable laser source

    Energy Technology Data Exchange (ETDEWEB)

    Klunder, G L; Margalith, E; Nguyen, L K

    2010-03-26

    Diffuse reflectance near infrared hyperspectral imaging is an important analytical tool for a wide variety of industries, including agriculture consumer products, chemical and pharmaceutical development and production. Using this technique as a method for the standoff detection of explosive particles is presented and discussed. The detection of the particles is based on the diffuse reflectance of light from the particle in the near infrared wavelength range where CH, NH, OH vibrational overtones and combination bands are prominent. The imaging system is a NIR focal plane array camera with a tunable OPO/laser system as the illumination source. The OPO is programmed to scan over a wide spectral range in the NIR and the camera is synchronized to record the light reflected from the target for each wavelength. The spectral resolution of this system is significantly higher than that of hyperspectral systems that incorporate filters or dispersive elements. The data acquisition is very fast and the entire hyperspectral cube can be collected in seconds. A comparison of data collected with the OPO system to data obtained with a broadband light source with LCTF filters is presented.

  14. 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.

  15. Spectral beam combining of diode lasers with high efficiency

    DEFF Research Database (Denmark)

    Müller, André; Vijayakumar, Deepak; Jensen, Ole Bjarlin

    2012-01-01

    Based on spectral beam combining we obtain 16 W of output power, combining two 1063 nm DBR-tapered diode lasers. The spectral separation within the combined beam can be used for subsequent sum-frequency generation.......Based on spectral beam combining we obtain 16 W of output power, combining two 1063 nm DBR-tapered diode lasers. The spectral separation within the combined beam can be used for subsequent sum-frequency generation....

  16. Spectral interpolation - Zero fill or convolution. [image processing

    Science.gov (United States)

    Forman, M. L.

    1977-01-01

    Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

  17. Multiplex CARS imaging with spectral notch shaped laser pulses delivered by optical fibers.

    Science.gov (United States)

    Oh, Seung Ryeol; Park, Joo Hyun; Kim, Kyung-Soo; Lee, Jae Yong; Kim, Soohyun

    2017-12-11

    We present an experimental demonstration of single-pulse coherent anti-Stokes Raman spectroscopy (CARS) using a spectrally shaped broadband laser that is delivered by an optical fiber to a sample at its distal end. The optical fiber consists of a fiber Bragg grating component to serve as a narrowband notch filter and a combined large-mode-area fiber to transmit such shaped ultrashort laser pulses without spectral distortion in a long distance. Experimentally, our implementation showed a capability to measure CARS spectra of various samples with molecular vibrations in the fingerprint region. Furthermore, CARS imaging of poly(methyl methacrylate) bead samples was carried out successfully under epi-CARS geometry in which backward-scattered CARS signals were collected into a multimode optical fiber. A compatibility of single-pulse CARS scheme with fiber optics, verified in this study, implies a potential for future realization of compact all-fiber CARS spectroscopic imaging systems.

  18. Infrared upconversion hyperspectral imaging

    DEFF Research Database (Denmark)

    Kehlet, Louis Martinus; Tidemand-Lichtenberg, Peter; Dam, Jeppe Seidelin

    2015-01-01

    In this Letter, hyperspectral imaging in the mid-IR spectral region is demonstrated based on nonlinear frequency upconversion and subsequent imaging using a standard Si-based CCD camera. A series of upconverted images are acquired with different phase match conditions for the nonlinear frequency...... conversion process. From this, a sequence of monochromatic images in the 3.2-3.4 mu m range is generated. The imaged object consists of a standard United States Air Force resolution target combined with a polystyrene film, resulting in the presence of both spatial and spectral information in the infrared...... image. (C) 2015 Optical Society of America...

  19. Extraction of neutron spectral information from Bonner-Sphere data

    CERN Document Server

    Haney, J H; Zaidins, C S

    1999-01-01

    We have extended a least-squares method of extracting neutron spectral information from Bonner-Sphere data which was previously developed by Zaidins et al. (Med. Phys. 5 (1978) 42). A pulse-height analysis with background stripping is employed which provided a more accurate count rate for each sphere. Newer response curves by Mares and Schraube (Nucl. Instr. and Meth. A 366 (1994) 461) were included for the moderating spheres and the bare detector which comprise the Bonner spectrometer system. Finally, the neutron energy spectrum of interest was divided using the philosophy of fuzzy logic into three trapezoidal regimes corresponding to slow, moderate, and fast neutrons. Spectral data was taken using a PuBe source in two different environments and the analyzed data is presented for these cases as slow, moderate, and fast neutron fluences. (author)

  20. High Spectral Resolution, High Cadence, Imaging X-ray Microcalorimeters for Solar Physics - Phase 2 Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Microcalorimeter x-ray instruments are non-dispersive, high spectral resolution, broad-band, high cadence imaging spectrometers. We have been developing these...

  1. Multispectral Image classification using the theories of neural networks

    International Nuclear Information System (INIS)

    Ardisasmita, M.S.; Subki, M.I.R.

    1997-01-01

    Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

  2. SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

    Energy Technology Data Exchange (ETDEWEB)

    Morris, R [Durham, NC (United States); Lakshmanan, M; Fong, G; Kapadia, A [Carl E Ravin Advanced Imaging Laboratories, Durham, NC (United States); Greenberg, J [Duke University, Durham, NC (United States)

    2016-06-15

    Purpose: Coherent scatter based imaging has shown improved contrast and molecular specificity over conventional digital mammography however the biological risks have not been quantified due to a lack of accurate information on absorbed dose. This study intends to characterize the dose distribution and average glandular dose from coded aperture coherent scatter spectral imaging of the breast. The dose deposited in the breast from this new diagnostic imaging modality has not yet been quantitatively evaluated. Here, various digitized anthropomorphic phantoms are tested in a Monte Carlo simulation to evaluate the absorbed dose distribution and average glandular dose using clinically feasible scan protocols. Methods: Geant4 Monte Carlo radiation transport simulation software is used to replicate the coded aperture coherent scatter spectral imaging system. Energy sensitive, photon counting detectors are used to characterize the x-ray beam spectra for various imaging protocols. This input spectra is cross-validated with the results from XSPECT, a commercially available application that yields x-ray tube specific spectra for the operating parameters employed. XSPECT is also used to determine the appropriate number of photons emitted per mAs of tube current at a given kVp tube potential. With the implementation of the XCAT digital anthropomorphic breast phantom library, a variety of breast sizes with differing anatomical structure are evaluated. Simulations were performed with and without compression of the breast for dose comparison. Results: Through the Monte Carlo evaluation of a diverse population of breast types imaged under real-world scan conditions, a clinically relevant average glandular dose for this new imaging modality is extrapolated. Conclusion: With access to the physical coherent scatter imaging system used in the simulation, the results of this Monte Carlo study may be used to directly influence the future development of the modality to keep breast dose to

  3. Radiographic information theory: correction for x-ray spectral distribution

    International Nuclear Information System (INIS)

    Brodie, I.; Gutcheck, R.A.

    1983-01-01

    A more complete computational method is developed to account for the effect of the spectral distribution of the incident x-ray fluence on the minimum exposure required to record a specified information set in a diagnostic radiograph. It is shown that an earlier, less rigorous, but simpler computational technique does not introduce serious errors provided that both a good estimate of the mean energy per photon can be made and the detector does not contain an absorption edge in the spectral range. Also shown is that to a first approximation, it is immaterial whether the detecting surface counts the number of photons incident from each pixel or measures the energy incident on each pixel. A previous result is confirmed that, for mammography, the present methods of processing data from the detector utilize only a few percent of the incident information, suggesting that techniques can be developed for obtaining mammograms at substantially lower doses than those presently used. When used with film-screen combinations, x-ray tubes with tungsten anodes should require substantially lower exposures than devices using molybdenum anodes, when both are operated at their optimal voltage

  4. Pure sources and efficient detectors for optical quantum information processing

    Science.gov (United States)

    Zielnicki, Kevin

    Over the last sixty years, classical information theory has revolutionized the understanding of the nature of information, and how it can be quantified and manipulated. Quantum information processing extends these lessons to quantum systems, where the properties of intrinsic uncertainty and entanglement fundamentally defy classical explanation. This growing field has many potential applications, including computing, cryptography, communication, and metrology. As inherently mobile quantum particles, photons are likely to play an important role in any mature large-scale quantum information processing system. However, the available methods for producing and detecting complex multi-photon states place practical limits on the feasibility of sophisticated optical quantum information processing experiments. In a typical quantum information protocol, a source first produces an interesting or useful quantum state (or set of states), perhaps involving superposition or entanglement. Then, some manipulations are performed on this state, perhaps involving quantum logic gates which further manipulate or entangle the intial state. Finally, the state must be detected, obtaining some desired measurement result, e.g., for secure communication or computationally efficient factoring. The work presented here concerns the first and last stages of this process as they relate to photons: sources and detectors. Our work on sources is based on the need for optimized non-classical states of light delivered at high rates, particularly of single photons in a pure quantum state. We seek to better understand the properties of spontaneous parameteric downconversion (SPDC) sources of photon pairs, and in doing so, produce such an optimized source. We report an SPDC source which produces pure heralded single photons with little or no spectral filtering, allowing a significant rate enhancement. Our work on detectors is based on the need to reliably measure single-photon states. We have focused on

  5. Infrared imaging of skin lesions

    Science.gov (United States)

    McIntosh, Laura M.; Mansfield, James R.; Jackson, Michael; Crowson, A. Neil; Mantsch, Henry H.

    2002-02-01

    IR spectroscopy produces spectra in which detailed information concerning chemical structure is inherent. Numerous studies have demonstrated that the most useful IR methods for analysis of biological tissues are microscopic image-based techniques in which fine-scaled spatial and high-quality spectral information is integrated. Unlike traditional visible microscopic methods, the contrast in IR imaging is gained by differences in spectra and the spatial heterogeneity of biochemical components, not by the addition of stains. In order for IR imaging to be more broadly accepted, non-subjective data processing methods are being developed to extract the most out of the large spectral images that are acquired. This paper demonstrates data processing techniques that have been extremely useful in the analysis of normal and abnormal skin. Analysis of skin specimens is of particular clinical importance due to the difficulty in rendering a differential diagnosis. Unstained frozen skin sections were mapped using an IR microscope. Functional group mapping, clustering routines and linear discriminant analysis were used to process the data. Functional group mapping and clustering routines were useful in the initial interpretation of images and to research for trends in uncharacterized spectral images. LDA was useful for differentiating normal from abnormal tissue once a well- defined training spectral set was established. Representative spectroscopic images are shown that demonstrate the power of IR imaging.

  6. The Interaction of Temporal and Spectral Acoustic Information with Word Predictability on Speech Intelligibility

    Science.gov (United States)

    Shahsavarani, Somayeh Bahar

    High-level, top-down information such as linguistic knowledge is a salient cortical resource that influences speech perception under most listening conditions. But, are all listeners able to exploit these resources for speech facilitation to the same extent? It was found that children with cochlear implants showed different patterns of benefit from contextual information in speech perception compared with their normal-haring peers. Previous studies have discussed the role of non-acoustic factors such as linguistic and cognitive capabilities to account for this discrepancy. Given the fact that the amount of acoustic information encoded and processed by auditory nerves of listeners with cochlear implants differs from normal-hearing listeners and even varies across individuals with cochlear implants, it is important to study the interaction of specific acoustic properties of the speech signal with contextual cues. This relationship has been mostly neglected in previous research. In this dissertation, we aimed to explore how different acoustic dimensions interact to affect listeners' abilities to combine top-down information with bottom-up information in speech perception beyond the known effects of linguistic and cognitive capacities shown previously. Specifically, the present study investigated whether there were any distinct context effects based on the resolution of spectral versus slowly-varying temporal information in perception of spectrally impoverished speech. To that end, two experiments were conducted. In both experiments, a noise-vocoded technique was adopted to generate spectrally-degraded speech to approximate acoustic cues delivered to listeners with cochlear implants. The frequency resolution was manipulated by varying the number of frequency channels. The temporal resolution was manipulated by low-pass filtering of amplitude envelope with varying low-pass cutoff frequencies. The stimuli were presented to normal-hearing native speakers of American

  7. Installation of spectrally selective imaging system in RF negative ion source

    International Nuclear Information System (INIS)

    Ikeda, K.; Kisaki, M.; Nagaoka, K.; Nakano, H.; Osakabe, M.; Tsumori, K.; Kaneko, O.; Takeiri, Y.; Wünderlich, D.; Fantz, U.; Heinemann, B.; Geng, S.

    2016-01-01

    A spectrally selective imaging system has been installed in the RF negative ion source in the International Thermonuclear Experimental Reactor-relevant negative ion beam test facility ELISE (Extraction from a Large Ion Source Experiment) to investigate distribution of hydrogen Balmer-α emission (H α ) close to the production surface of hydrogen negative ion. We selected a GigE vision camera coupled with an optical band-path filter, which can be controlled remotely using high speed network connection. A distribution of H α emission near the bias plate has been clearly observed. The same time trend on H α intensities measured by the imaging diagnostic and the optical emission spectroscopy is confirmed

  8. A COMPARISON STUDY OF DIFFERENT MARKER SELECTION METHODS FOR SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    D. Akbari

    2015-12-01

    Full Text Available An effective approach based on the Minimum Spanning Forest (MSF, grown from automatically selected markers using Support Vector Machines (SVM, has been proposed for spectral-spatial classification of hyperspectral images by Tarabalka et al. This paper aims at improving this approach by using image segmentation to integrate the spatial information into marker selection process. In this study, the markers are extracted from the classification maps, obtained by both SVM and segmentation algorithms, and then are used to build the MSF. The segmentation algorithms are the watershed, expectation maximization (EM and hierarchical clustering. These algorithms are used in parallel and independently to segment the image. Moreover, the pixels of each class, with the largest population in the classification map, are kept for each region of the segmentation map. Lastly, the most reliable classified pixels are chosen from among the exiting pixels as markers. Two benchmark urban hyperspectral datasets are used for evaluation: Washington DC Mall and Berlin. The results of our experiments indicate that, compared to the original MSF approach, the marker selection using segmentation algorithms leads in more accurate classification maps.

  9. Ultra-thin infrared metamaterial detector for multicolor imaging applications.

    Science.gov (United States)

    Montoya, John A; Tian, Zhao-Bing; Krishna, Sanjay; Padilla, Willie J

    2017-09-18

    The next generation of infrared imaging systems requires control of fundamental electromagnetic processes - absorption, polarization, spectral bandwidth - at the pixel level to acquire desirable information about the environment with low system latency. Metamaterial absorbers have sparked interest in the infrared imaging community for their ability to enhance absorption of incoming radiation with color, polarization and/or phase information. However, most metamaterial-based sensors fail to focus incoming radiation into the active region of a ultra-thin detecting element, thus achieving poor detection metrics. Here our multifunctional metamaterial absorber is directly integrated with a novel mid-wave infrared (MWIR) and long-wave infrared (LWIR) detector with an ultra-thin (~λ/15) InAs/GaSb Type-II superlattice (T2SL) interband cascade detector. The deep sub-wavelength metamaterial detector architecture proposed and demonstrated here, thus significantly improves the detection quantum efficiency (QE) and absorption of incoming radiation in a regime typically dominated by Fabry-Perot etalons. Our work evinces the ability of multifunctional metamaterials to realize efficient wavelength selective detection across the infrared spectrum for enhanced multispectral infrared imaging applications.

  10. Quantifying Optical Microangiography Images Obtained from a Spectral Domain Optical Coherence Tomography System

    Directory of Open Access Journals (Sweden)

    Roberto Reif

    2012-01-01

    Full Text Available The blood vessel morphology is known to correlate with several diseases, such as cancer, and is important for describing several tissue physiological processes, like angiogenesis. Therefore, a quantitative method for characterizing the angiography obtained from medical images would have several clinical applications. Optical microangiography (OMAG is a method for obtaining three-dimensional images of blood vessels within a volume of tissue. In this study we propose to quantify OMAG images obtained with a spectral domain optical coherence tomography system. A technique for determining three measureable parameters (the fractal dimension, the vessel length fraction, and the vessel area density is proposed and validated. Finally, the repeatability for acquiring OMAG images is determined, and a new method for analyzing small areas from these images is proposed.

  11. 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

  12. The optimal monochromatic spectral computed tomographic imaging plus adaptive statistical iterative reconstruction algorithm can improve the superior mesenteric vessel image quality

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Xiao-Ping; Zuo, Zi-Wei; Xu, Ying-Jin; Wang, Jia-Ning [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Liu, Huai-Jun, E-mail: hebeiliu@outlook.com [Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000 (China); Liang, Guang-Lu [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Gao, Bu-Lang, E-mail: browngao@163.com [Department of Medical Research, Shijiazhuang First Hospital, Shijiazhuang, Hebei, 050011 (China)

    2017-04-15

    Objective: To investigate the effect of the optimal monochromatic spectral computed tomography (CT) plus adaptive statistical iterative reconstruction on the improvement of the image quality of the superior mesenteric artery and vein. Materials and methods: The gemstone spectral CT angiographic data of 25 patients were reconstructed in the following three groups: 70 KeV, the optimal monochromatic imaging, and the optimal monochromatic plus 40%iterative reconstruction mode. The CT value, image noises (IN), background CT value and noises, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image scores of the vessels and surrounding tissues were analyzed. Results: In the 70 KeV, the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group, the mean scores of image quality were 3.86, 4.24 and 4.25 for the superior mesenteric artery and 3.46, 3.78 and 3.81 for the superior mesenteric vein, respectively. The image quality scores for the optimal monochromatic and the optimal monochromatic plus 40% iterative reconstruction groups were significantly greater than for the 70 KeV group (P < 0.05). The vascular CT value, image noise, background noise, CNR and SNR were significantly (P < 0.001) greater in the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group than in the 70 KeV group. The optimal monochromatic plus 40% iterative reconstruction group had significantly (P < 0.05) lower image and background noise but higher CNR and SNR than the other two groups. Conclusion: The optimal monochromatic imaging combined with 40% iterative reconstruction using low-contrast agent dosage and low injection rate can significantly improve the image quality of the superior mesenteric artery and vein.

  13. EVALUATION OF VARIOUS SPECTRAL INPUTS FOR ESTIMATION OF FOREST BIOCHEMICAL AND STRUCTURAL PROPERTIES FROM AIRBORNE IMAGING SPECTROSCOPY DATA

    Directory of Open Access Journals (Sweden)

    L. Homolová

    2016-06-01

    Full Text Available In this study we evaluated various spectral inputs for retrieval of forest chlorophyll content (Cab and leaf area index (LAI from high spectral and spatial resolution airborne imaging spectroscopy data collected for two forest study sites in the Czech Republic (beech forest at Štítná nad Vláří and spruce forest at Bílý Kříž. The retrieval algorithm was based on a machine learning method – support vector regression (SVR. Performance of the four spectral inputs used to train SVR was evaluated: a all available hyperspectral bands, b continuum removal (CR 645 – 710 nm, c CR 705 – 780 nm, and d CR 680 – 800 nm. Spectral inputs and corresponding SVR models were first assessed at the level of spectral databases simulated by combined leaf-canopy radiative transfer models PROSPECT and DART. At this stage, SVR models using all spectral inputs provided good performance (RMSE for Cab −2 and for LAI < 1.5, with consistently better performance for beech over spruce site. Since application of trained SVRs on airborne hyperspectral images of the spruce site produced unacceptably overestimated values, only the beech site results were analysed. The best performance for the Cab estimation was found for CR bands in range of 645 – 710 nm, whereas CR bands in range of 680 – 800 nm were the most suitable for LAI retrieval. The CR transformation reduced the across-track bidirectional reflectance effect present in airborne images due to large sensor field of view.

  14. 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

  15. 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

  16. Energy efficiency information systems. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-31

    It is well known that different cultures and countries are receptive in different ways to information transfer. Modern information technology, including computers, videos, and telecommunications, can provide a very useful tool for the dissemination of information. At the same time, however, the use of new media involves many new and varied challenges. It is important therefore that the new dissemination methods are developed and utilised in the most effective way depending on the subjects distinctive character, needs and traditions. This workshop was designed to gather experts from all the CADDET member countries, to share knowledge, experiences and ideas about the use of new methods of information exchange and training in the field of energy efficiency. The workshop was divided into four plenary sessions: dissemination of information on energy efficient technologies; training technologies and effective learning; computer-based training tools on energy efficiency; databases and network resources. Two discussion groups followed the plenary sessions, to concentrate on: different aspects of information exchange; and different aspects of state-of-the-art training tools. The workshop was attended by 44 participants from 17 countries, and included 14 speakers

  17. 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

  18. Hyperspectral image processing methods

    Science.gov (United States)

    Hyperspectral image processing refers to the use of computer algorithms to extract, store and manipulate both spatial and spectral information contained in hyperspectral images across the visible and near-infrared portion of the electromagnetic spectrum. A typical hyperspectral image processing work...

  19. Diagnosis of skin cancer using image processing

    Science.gov (United States)

    Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué; Coronel-Beltrán, Ángel

    2014-10-01

    In this papera methodology for classifying skin cancerin images of dermatologie spots based on spectral analysis using the K-law Fourier non-lineartechnique is presented. The image is segmented and binarized to build the function that contains the interest area. The image is divided into their respective RGB channels to obtain the spectral properties of each channel. The green channel contains more information and therefore this channel is always chosen. This information is point to point multiplied by a binary mask and to this result a Fourier transform is applied written in nonlinear form. If the real part of this spectrum is positive, the spectral density takeunit values, otherwise are zero. Finally the ratio of the sum of the unit values of the spectral density with the sum of values of the binary mask are calculated. This ratio is called spectral index. When the value calculated is in the spectral index range three types of cancer can be detected. Values found out of this range are benign injure.

  20. 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.

  1. Dual-Energy Computed Tomography Gemstone Spectral Imaging: A Novel Technique to Determine Human Cardiac Calculus Composition.

    Science.gov (United States)

    Cheng, Ching-Li; Chang, Hsiao-Huang; Ko, Shih-Chi; Huang, Pei-Jung; Lin, Shan-Yang

    2016-01-01

    Understanding the chemical composition of any calculus in different human organs is essential for choosing the best treatment strategy for patients. The purpose of this study was to assess the capability of determining the chemical composition of a human cardiac calculus using gemstone spectral imaging (GSI) mode on a single-source dual-energy computed tomography (DECT) in vitro. The cardiac calculus was directly scanned on the Discovery CT750 HD FREEdom Edition using GSI mode, in vitro. A portable fiber-optic Raman spectroscopy was also applied to verify the quantitative accuracy of the DECT measurements. The results of spectral DECT measurements indicate that effective Z values in 3 designated positions located in this calculus were 15.02 to 15.47, which are close to values of 15.74 to 15.86, corresponding to the effective Z values of calcium apatite and hydroxyapatite. The Raman spectral data were also reflected by the predominant Raman peak at 960 cm for hydroxyapatite and the minor peak at 875 cm for calcium apatite. A potential single-source DECT with GSI mode was first used to examine the morphological characteristics and chemical compositions of a giant human cardiac calculus, in vitro. The CT results were consistent with the Raman spectral data, suggesting that spectral CT imaging techniques could be accurately used to diagnose and characterize the compositional materials in the cardiac calculus.

  2. 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.

  3. Thermodynamic efficiency of information and heat flow

    International Nuclear Information System (INIS)

    Allahverdyan, Armen E; Janzing, Dominik; Mahler, Guenter

    2009-01-01

    A basic task of information processing is information transfer (flow). Here we study a pair of Brownian particles each coupled to a thermal bath at temperatures T 1 and T 2 . The information flow in such a system is defined via the time-shifted mutual information. The information flow nullifies at equilibrium, and its efficiency is defined as the ratio of the flow to the total entropy production in the system. For a stationary state the information flows from higher to lower temperatures, and its efficiency is bounded from above by (max[T 1 ,T 2 ])/(|T 1 −T 2 |). This upper bound is imposed by the second law and it quantifies the thermodynamic cost for information flow in the present class of systems. It can be reached in the adiabatic situation, where the particles have widely different characteristic times. The efficiency of heat flow—defined as the heat flow over the total amount of dissipated heat—is limited from above by the same factor. There is a complementarity between heat and information flow: the set-up which is most efficient for the former is the least efficient for the latter and vice versa. The above bound for the efficiency can be (transiently) overcome in certain non-stationary situations, but the efficiency is still limited from above. We study yet another measure of information processing (transfer entropy) proposed in the literature. Though this measure does not require any thermodynamic cost, the information flow and transfer entropy are shown to be intimately related for stationary states

  4. Simultaneous high-speed spectral and infrared imaging of engine combustion

    Science.gov (United States)

    Jansons, Marcis

    2005-11-01

    A novel and unique diagnostic apparatus has been developed and applied to combustion gas mixtures in engine cylinders. The computer-controlled system integrates a modified Fastie-Ebert type spectrophotometer with four infrared CCD imagers, allowing the simultaneous acquisition of the spectrum and four spatial images, each at a discrete wavelength. Data buffering allows continuous imaging of the power stroke over consecutive engine cycles at framing rates of 1850 frames/second. Spectral resolution is 28nm with an uncertainty better than 58nm. The nominal response of the instrument is in the range 1.8--4.5mum, with a peak responsivity near the important 2.7mum bands of CO2 and H2O. The spectral range per scan is approximately 1.78mum. To interpret the measured data, a line-by-line radiation model was created utilizing the High-Resolution Transmission (HITRAN) database of molecular parameters, incorporating soot and wall emission effects. Although computationally more intensive, this model represents an improvement in accuracy over the NASA single-line-group (SLG) model which does not include the 'hot' CO2 lines of the 3.8mum region. Methane/air combustion mixture thermodynamic parameters are estimated by the iteration of model variables to yield a synthetic spectrum that, when corrected for wall effects, instrument function, responsivity, window and laboratory path transmissivity, correspond to the measured spectrum. The values of the model variables are used to interpret the corresponding spatial images. For the first time in the infrared an entire engine starting sequence has been observed over consecutive cycles. Preflame spectra measured during the compression stroke of a spark-ignition engine operating with various fuels correlate well with the synthetic spectra of the particular hydrocarbon reactants. The ability to determine concentration and spatial distribution of fuel in the engine cylinder prior to ignition has applications in stratified charge studies and

  5. Automatic spectral imaging protocol selection and iterative reconstruction in abdominal CT with reduced contrast agent dose: initial experience

    Energy Technology Data Exchange (ETDEWEB)

    Lv, Peijie; Liu, Jie; Chai, Yaru; Yan, Xiaopeng; Gao, Jianbo; Dong, Junqiang [The First Affiliated Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan Province (China)

    2017-01-15

    To evaluate the feasibility, image quality, and radiation dose of automatic spectral imaging protocol selection (ASIS) and adaptive statistical iterative reconstruction (ASIR) with reduced contrast agent dose in abdominal multiphase CT. One hundred and sixty patients were randomly divided into two scan protocols (n = 80) each; protocol A, 120 kVp/450 mgI/kg, filtered back projection algorithm (FBP); protocol B, spectral CT imaging with ASIS and 40 to 70 keV monochromatic images generated per 300 mgI/kg, ASIR algorithm. Quantitative parameters (image noise and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (image noise, small structures, organ enhancement, and overall image quality) were compared. Monochromatic images at 50 keV and 60 keV provided similar or lower image noise, but higher contrast and overall image quality as compared with 120-kVp images. Despite the higher image noise, 40-keV images showed similar overall image quality compared to 120-kVp images. Radiation dose did not differ between the two protocols, while contrast agent dose in protocol B was reduced by 33 %. Application of ASIR and ASIS to monochromatic imaging from 40 to 60 keV allowed contrast agent dose reduction with adequate image quality and without increasing radiation dose compared to 120 kVp with FBP. (orig.)

  6. Automatic spectral imaging protocol selection and iterative reconstruction in abdominal CT with reduced contrast agent dose: initial experience

    International Nuclear Information System (INIS)

    Lv, Peijie; Liu, Jie; Chai, Yaru; Yan, Xiaopeng; Gao, Jianbo; Dong, Junqiang

    2017-01-01

    To evaluate the feasibility, image quality, and radiation dose of automatic spectral imaging protocol selection (ASIS) and adaptive statistical iterative reconstruction (ASIR) with reduced contrast agent dose in abdominal multiphase CT. One hundred and sixty patients were randomly divided into two scan protocols (n = 80) each; protocol A, 120 kVp/450 mgI/kg, filtered back projection algorithm (FBP); protocol B, spectral CT imaging with ASIS and 40 to 70 keV monochromatic images generated per 300 mgI/kg, ASIR algorithm. Quantitative parameters (image noise and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (image noise, small structures, organ enhancement, and overall image quality) were compared. Monochromatic images at 50 keV and 60 keV provided similar or lower image noise, but higher contrast and overall image quality as compared with 120-kVp images. Despite the higher image noise, 40-keV images showed similar overall image quality compared to 120-kVp images. Radiation dose did not differ between the two protocols, while contrast agent dose in protocol B was reduced by 33 %. Application of ASIR and ASIS to monochromatic imaging from 40 to 60 keV allowed contrast agent dose reduction with adequate image quality and without increasing radiation dose compared to 120 kVp with FBP. (orig.)

  7. Optimisation of chromatographic resolution using objective functions including both time and spectral information.

    Science.gov (United States)

    Torres-Lapasió, J R; Pous-Torres, S; Ortiz-Bolsico, C; García-Alvarez-Coque, M C

    2015-01-16

    The optimisation of the resolution in high-performance liquid chromatography is traditionally performed attending only to the time information. However, even in the optimal conditions, some peak pairs may remain unresolved. Such incomplete resolution can be still accomplished by deconvolution, which can be carried out with more guarantees of success by including spectral information. In this work, two-way chromatographic objective functions (COFs) that incorporate both time and spectral information were tested, based on the peak purity (analyte peak fraction free of overlapping) and the multivariate selectivity (figure of merit derived from the net analyte signal) concepts. These COFs are sensitive to situations where the components that coelute in a mixture show some spectral differences. Therefore, they are useful to find out experimental conditions where the spectrochromatograms can be recovered by deconvolution. Two-way multivariate selectivity yielded the best performance and was applied to the separation using diode-array detection of a mixture of 25 phenolic compounds, which remained unresolved in the chromatographic order using linear and multi-linear gradients of acetonitrile-water. Peak deconvolution was carried out using the combination of orthogonal projection approach and alternating least squares. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Efficient Variational Approaches for Deformable Registration of Images

    Directory of Open Access Journals (Sweden)

    Mehmet Ali Akinlar

    2012-01-01

    Full Text Available Dirichlet, anisotropic, and Huber regularization terms are presented for efficient registration of deformable images. Image registration, an ill-posed optimization problem, is solved using a gradient-descent-based method and some fundamental theorems in calculus of variations. Euler-Lagrange equations with homogeneous Neumann boundary conditions are obtained. These equations are discretized by multigrid and finite difference numerical techniques. The method is applied to the registration of brain MR images of size 65×65. Computational results indicate that the presented method is quite fast and efficient in the registration of deformable medical images.

  9. Breaking camouflage and detecting targets require optic flow and image structure information.

    Science.gov (United States)

    Pan, Jing Samantha; Bingham, Ned; Chen, Chang; Bingham, Geoffrey P

    2017-08-01

    Use of motion to break camouflage extends back to the Cambrian [In the Blink of an Eye: How Vision Sparked the Big Bang of Evolution (New York Basic Books, 2003)]. We investigated the ability to break camouflage and continue to see camouflaged targets after motion stops. This is crucial for the survival of hunting predators. With camouflage, visual targets and distracters cannot be distinguished using only static image structure (i.e., appearance). Motion generates another source of optical information, optic flow, which breaks camouflage and specifies target locations. Optic flow calibrates image structure with respect to spatial relations among targets and distracters, and calibrated image structure makes previously camouflaged targets perceptible in a temporally stable fashion after motion stops. We investigated this proposal using laboratory experiments and compared how many camouflaged targets were identified either with optic flow information alone or with combined optic flow and image structure information. Our results show that the combination of motion-generated optic flow and target-projected image structure information yielded efficient and stable perception of camouflaged targets.

  10. A Weighted Spatial-Spectral Kernel RX Algorithm and Efficient Implementation on GPUs

    Directory of Open Access Journals (Sweden)

    Chunhui Zhao

    2017-02-01

    Full Text Available The kernel RX (KRX detector proposed by Kwon and Nasrabadi exploits a kernel function to obtain a better detection performance. However, it still has two limits that can be improved. On the one hand, reasonable integration of spatial-spectral information can be used to further improve its detection accuracy. On the other hand, parallel computing can be used to reduce the processing time in available KRX detectors. Accordingly, this paper presents a novel weighted spatial-spectral kernel RX (WSSKRX detector and its parallel implementation on graphics processing units (GPUs. The WSSKRX utilizes the spatial neighborhood resources to reconstruct the testing pixels by introducing a spectral factor and a spatial window, thereby effectively reducing the interference of background noise. Then, the kernel function is redesigned as a mapping trick in a KRX detector to implement the anomaly detection. In addition, a powerful architecture based on the GPU technique is designed to accelerate WSSKRX. To substantiate the performance of the proposed algorithm, both synthetic and real data are conducted for experiments.

  11. Design of high-efficiency diffractive optical elements towards ultrafast mid-infrared time-stretched imaging and spectroscopy

    Science.gov (United States)

    Xie, Hongbo; Ren, Delun; Wang, Chao; Mao, Chensheng; Yang, Lei

    2018-02-01

    Ultrafast time stretch imaging offers unprecedented imaging speed and enables new discoveries in scientific research and engineering. One challenge in exploiting time stretch imaging in mid-infrared is the lack of high-quality diffractive optical elements (DOEs), which encode the image information into mid-infrared optical spectrum. This work reports the design and optimization of mid-infrared DOE with high diffraction-efficiency, broad bandwidth and large field of view. Using various typical materials with their refractive indices ranging from 1.32 to 4.06 in ? mid-infrared band, diffraction efficiencies of single-layer and double-layer DOEs have been studied in different wavelength bands with different field of views. More importantly, by replacing the air gap of double-layer DOE with carefully selected optical materials, one optimized ? triple-layer DOE, with efficiency higher than 95% in the whole ? mid-infrared window and field of view greater than ?, is designed and analyzed. This new DOE device holds great potential in ultrafast mid-infrared time stretch imaging and spectroscopy.

  12. 16QAM transmission with 5.2 bits/s/Hz spectral efficiency over transoceanic distance.

    Science.gov (United States)

    Zhang, H; Cai, J-X; Batshon, H G; Davidson, C R; Sun, Y; Mazurczyk, M; Foursa, D G; Pilipetskii, A; Mohs, G; Bergano, Neal S

    2012-05-21

    We transmit 160 x 100 G PDM RZ 16 QAM channels with 5.2 bits/s/Hz spectral efficiency over 6,860 km. There are more than 3 billion 16 QAM symbols, i.e., 12 billion bits, processed in total. Using coded modulation and iterative decoding between a MAP decoder and an LDPC based FEC all channels are decoded with no remaining errors.

  13. Using Deduplicating Storage for Efficient Disk Image Deployment

    Directory of Open Access Journals (Sweden)

    Xing Lin

    2015-08-01

    Full Text Available Many clouds and network testbeds use disk images to initialize local storage on their compute devices. Large facilities must manage thousands or more images, requiring significant amounts of storage. At the same time, to provide a good user experience, they must be able to deploy those images quickly. Driven by our experience in operating the Emulab site at the University of Utah---a long-lived and heavily-used testbed---we have created a new service for efficiently storing and deploying disk images. This service exploits the redundant data found in similar images, using deduplication to greatly reduce the amount of physical storage required. In addition to space savings, our system is also designed for highly efficient image deployment---it integrates with an existing highly-optimized disk image deployment system, Frisbee, without significantly increasing the time required to distribute and install images. In this paper, we explain the design of our system and discuss the trade-offs we made to strike a balance between efficient storage and fast disk image deployment. We also propose a new chunking algorithm, called AFC, which enables fixed-size chunking for deduplicating allocated disk sectors. Experimental results show that our system reduces storage requirements by up to 3x while imposing only a negligible runtime overhead on the end-to-end disk-deployment process.

  14. 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.

  15. A hyperspectral fluorescence system for 3D in vivo optical imaging

    International Nuclear Information System (INIS)

    Zavattini, Guido; Vecchi, Stefania; Mitchell, Gregory; Weisser, Ulli; Leahy, Richard M; Pichler, Bernd J; Smith, Desmond J; Cherry, Simon R

    2006-01-01

    In vivo optical instruments designed for small animal imaging generally measure the integrated light intensity across a broad band of wavelengths, or make measurements at a small number of selected wavelengths, and primarily use any spectral information to characterize and remove autofluorescence. We have developed a flexible hyperspectral imaging instrument to explore the use of spectral information to determine the 3D source location for in vivo fluorescence imaging applications. We hypothesize that the spectral distribution of the emitted fluorescence signal can be used to provide additional information to 3D reconstruction algorithms being developed for optical tomography. To test this hypothesis, we have designed and built an in vivo hyperspectral imaging system, which can acquire data from 400 to 1000 nm with 3 nm spectral resolution and which is flexible enough to allow the testing of a wide range of illumination and detection geometries. It also has the capability to generate a surface contour map of the animal for input into the reconstruction process. In this paper, we present the design of the system, demonstrate the depth dependence of the spectral signal in phantoms and show the ability to reconstruct 3D source locations using the spectral data in a simple phantom. We also characterize the basic performance of the imaging system

  16. 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.

  17. Near infrared spectral polarization imaging of prostate cancer tissues using Cybesin: a receptor-targeted contrast agent

    Science.gov (United States)

    Pu, Yang; Wang, W. B.; Tang, G. C.; Liang, Kexian; Achilefu, S.; Alfano, R. R.

    2013-03-01

    Cybesin, a smart contrast agent to target cancer cells, was investigated using a near infrared (NIR) spectral polarization imaging technique for prostate cancer detection. The approach relies on applying a contrast agent that can target cancer cells. Cybesin, as a small ICG-derivative dye-peptide, emit fluorescence between 750 nm and 900 nm, which is in the "tissue optical window". Cybesin was reported targeting the over-expressed bombesin receptors in cancer cells in animal model and the human prostate cancers over-expressing bombesin receptors. The NIR spectral polarization imaging study reported here demonstrated that Cybesin can be used as a smart optical biomarker and as a prostate cancer receptor targeted contrast agent.

  18. 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.

  19. Information mining in remote sensing imagery

    Science.gov (United States)

    Li, Jiang

    The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and

  20. Abdominal CT: An intra-individual comparison between virtual monochromatic spectral and polychromatic 120-kVp images obtained during the same examination

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, Yoshitake, E-mail: yamada@rad.med.keio.ac.jp [Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Jinzaki, Masahiro, E-mail: jinzaki@rad.med.keio.ac.jp [Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Hosokawa, Takahiro, E-mail: snowglobe@infoseek.jp [Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Tanami, Yutaka, E-mail: tanami@rad.med.keio.ac.jp [Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Abe, Takayuki, E-mail: tabe@z5.keio.jp [Center for Clinical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Kuribayashi, Sachio, E-mail: skuribay@med.keio.ac.jp [Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan)

    2014-10-15

    Highlights: • We compared virtual monochromatic spectral (VMS) images with 120-kVp images. • VMS images are generated using accurate two-material beam-hardening correction. • Abdominal 70-keV VMS images provide better image quality than 120-kVp images. • Iterative reconstruction can further improve the image quality of VMS images. - Abstract: Objectives: To compare quantitative and subjective image quality between virtual monochromatic spectral (VMS) and conventional polychromatic 120-kVp imaging performed during the same abdominal computed tomography (CT) examination. Materials and methods: Our institutional review board approved this prospective study; each participant provided written informed consent. 51 patients underwent sequential fast kVp-switching dual-energy (80/140 kVp, volume CT dose index: 12.7 mGy) and single-energy (120-kVp, 12.7 mGy) abdominal enhanced CT over an 8 cm scan length with a random acquisition order and a 4.3-s interval. VMS images with filtered back projection (VMS-FBP) and adaptive statistical iterative reconstruction (so-called hybrid IR) (VMS-ASIR) (at 70 keV), as well as 120-kVp images with FBP (120-kVp-FBP) and ASIR (120-kVp-ASIR), were generated from dual-energy and single-energy CT data, respectively. The objective image noises, signal-to-noise ratios and contrast-to-noise ratios of the liver, kidney, pancreas, spleen, portal vein and aorta, and the lesion-to-liver and lesion-to-kidney contrast-to-noise ratios were measured. Two radiologists independently and blindly assessed the subjective image quality. The results were analyzed using the paired t-test, Wilcoxon signed rank sum test and mixed-effects model with Bonferroni correction. Results: VMS-ASIR images were superior to 120-kVp-FBP, 120-kVp-ASIR and VMS-FBP images for all the quantitative assessments and the subjective overall image quality (all P < 0.001), while VMS-FBP images were superior to 120-kVp-FBP and 120-kVp-ASIR images (all P < 0.004). Conclusions: VMS

  1. Abdominal CT: An intra-individual comparison between virtual monochromatic spectral and polychromatic 120-kVp images obtained during the same examination

    International Nuclear Information System (INIS)

    Yamada, Yoshitake; Jinzaki, Masahiro; Hosokawa, Takahiro; Tanami, Yutaka; Abe, Takayuki; Kuribayashi, Sachio

    2014-01-01

    Highlights: • We compared virtual monochromatic spectral (VMS) images with 120-kVp images. • VMS images are generated using accurate two-material beam-hardening correction. • Abdominal 70-keV VMS images provide better image quality than 120-kVp images. • Iterative reconstruction can further improve the image quality of VMS images. - Abstract: Objectives: To compare quanti