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Sample records for modeling multispectral image

  1. Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

    1999-02-01

    The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: "End-to-end modeling and analysis (EEM)." We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term "end-to-end modeling and analysis." We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable.

  2. Multispectral thermal imaging

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W. [Los Alamos National Lab., NM (United States). Space and Remote Sensing Sciences Group; Garrett, A.; Pendergast, M.M. [Westinghouse Savannah River Corp., Aiken, SC (United States). Savannah River Technology Center; Kay, R.R. [Sandia National Lab., Albuquerque, NM (United States). Monitoring Systems and Technology Center

    1998-12-01

    Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

  3. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  4. Multispectral Panoramic Imaging System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — International Electronic Machines Corporation, a leader in the design of precision imaging systems, will develop an innovative multispectral, panoramic imaging...

  5. The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

    Science.gov (United States)

    Shimabukuro, Yosio Edemir; Smith, James A.

    1991-01-01

    Constrained-least-squares and weighted-least-squares mixing models for generating fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure, i.e., the fraction of inferred shade in the pixel is related to different eucalyptus ages.

  6. 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,

  7. Multi-spectral light interaction modeling and imaging of skin lesions

    Science.gov (United States)

    Patwardhan, Sachin Vidyanand

    Nevoscope as a diagnostic tool for melanoma was evaluated using a white light source with promising results. Information about the lesion depth and its structure will further improve the sensitivity and specificity of melanoma diagnosis. Wavelength-dependent variable penetration power of monochromatic light in the trans-illumination imaging using the Nevoscope can be used to obtain this information. Optimal selection of wavelengths for multi-spectral imaging requires light-tissue interaction modeling. For this, three-dimensional wavelength dependent voxel-based models of skin lesions with different depths are proposed. A Monte Carlo simulation algorithm (MCSVL) is developed in MATLAB and the tissue models are simulated using the Nevoscope optical geometry. 350--700nm optical wavelengths with an interval of 5nm are used in the study. A correlation analysis between the lesion depth and the diffuse reflectance is then used to obtain wavelengths that will produce diffuse reflectance suitable for imaging and give information related to the nevus depth and structure. Using the selected wavelengths, multi-spectral trans-illumination images of the skin lesions are collected and analyzed. An adaptive wavelet transform based tree-structure classification method (ADWAT) is proposed to classify epi-illuminance images of the skin lesions obtained using a white light source into melanoma and dysplastic nevus images classes. In this method, tree-structure models of melanoma and dysplastic nevus are developed and semantically compared with the tree-structure of the unknown image for classification. Development of the tree-structure is dependent on threshold selections obtained from a statistical analysis of the feature set. This makes the classification method adaptive. The true positive value obtained for this classifier is 90% with a false positive of 10%. The Extended ADWAT method and Fuzzy Membership Functions method using combined features from the epi-illuminance and multi-spectral

  8. Multispectral Landsat images of Antartica

    Energy Technology Data Exchange (ETDEWEB)

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

    1988-01-01

    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  9. Surgical wound debridement sequentially characterized in a porcine burn model with multispectral imaging.

    Science.gov (United States)

    King, Darlene R; Li, Weizhi; Squiers, John J; Mohan, Rachit; Sellke, Eric; Mo, Weirong; Zhang, Xu; Fan, Wensheng; DiMaio, J Michael; Thatcher, Jeffrey E

    2015-11-01

    Multispectral imaging (MSI) is an optical technique that measures specific wavelengths of light reflected from wound site tissue to determine the severity of burn wounds. A rapid MSI device to measure burn depth and guide debridement will improve clinical decision making and diagnoses. We used a porcine burn model to study partial thickness burns of varying severity. We made eight 4 × 4 cm burns on the dorsum of one minipig. Four burns were studied intact, and four burns underwent serial tangential excision. We imaged the burn sites with 400-1000 nm wavelengths. Histology confirmed that we achieved various partial thickness burns. Analysis of spectral images show that MSI detects significant variations in the spectral profiles of healthy tissue, superficial partial thickness burns, and deep partial thickness burns. The absorbance spectra of 515, 542, 629, and 669 nm were the most accurate in distinguishing superficial from deep partial thickness burns, while the absorbance spectra of 972 nm was the most accurate in guiding the debridement process. The ability to distinguish between partial thickness burns of varying severity to assess whether a patient requires surgery could be improved with an MSI device in a clinical setting. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

  10. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available This poster highlights the design and development of a camera which combines ultraviolet, infrared and visual imaging techniques for advanced diagnostic inspections, and also shows some evaluations carried out to demonstrate the operability...

  11. Multispectral Image Processing for Plants

    Science.gov (United States)

    Miles, Gaines E.

    1991-01-01

    The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

  12. Monitoring the influence of compression therapy on pathophysiology and structure of a swine scar model using multispectral imaging system

    Science.gov (United States)

    Ghassemi, Pejhman; Travis, Taryn E.; Shuppa, Jeffrey W.; Moffatt, Lauren T.; Ramella-Romana, Jessica C.

    2014-03-01

    Scar contractures can lead to significant reduction in function and inhibit patients from returning to work, participating in leisure activities and even render them unable to provide care for themselves. Compression therapy has long been a standard treatment for scar prevention but due to the lack of quantifiable metrics of scar formation scant evidence exists of its efficacy. We have recently introduced a multispectral imaging system to quantify pathophysiology (hemoglobin, blood oxygenation, melanin, etc) and structural features (roughness and collagen matrix) of scar. In this study, hypertrophic scars are monitored in-vivo in a porcine model using the imaging system to investigate influence of compression therapy on its quality.

  13. COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION

    Directory of Open Access Journals (Sweden)

    Preema Mole

    2016-07-01

    Full Text Available The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more perceptible to human eye. Multispectral Image fusion is the process of combining images optically acquired in more than one spectral band. In this paper, we present a pixel-level image fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um, mid infrared(1.55-1.75um,thermal- infrared(10.4-12.5um and mid infrared(2.08-2.35um to give a composite colour image. The work coalesces a fusion technique that involves linear transformation based on Cholesky decomposition of the covariance matrix of source data that converts multispectral source images which are in grayscale into colour image. This work is composed of different segments that includes estimation of covariance matrix of images, cholesky decomposition and transformation ones. Finally, the fused colour image is compared with the fused image obtained by PCA transformation.

  14. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

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

    2012-01-01

    only with fish oil. In this study, multispectral image analysis of pellets captured reflection in 20 wavelengths (385–1050 nm). Linear discriminant analysis (LDA), principal component analysis, and support vector machine were used as statistical analysis. The features extracted from the multispectral...

  15. A thermal inertia model for soil water content retrieval using thermal and multispectral images

    Science.gov (United States)

    Maltese, A.; Minacapilli, M.; Cammalleri, C.; Ciraolo, G.; D'Asaro, F.

    2010-10-01

    Soil moisture is difficult to quantify because of its high spatial variability. Consequently, great efforts have been undertaken by the research community to develop practical remote sensing approaches to estimate the spatial distribution of surface soil moisture over large areas and with high spatial detail. Many methodologies have been developed using remote sensing data acquiring information in different parts of the electromagnetic spectrum. Conventional field measurement techniques (including gravimetric and time-domain reflectometry) are point-based, involve on-site operators, are time expensive and, in any case, do not provide exhaustive information on the spatial distribution of soil moisture because it strongly depends on pedology, soil roughness and vegetation cover. The technological development of imaging sensors acquiring in the visible (VIS), near infrared (NIR) and thermal infrared (TIR), renewed the research interest in setting up remote sensed based techniques aimed to retrieve soil water content variability in the soil-plant-atmosphere system (SPA). In this context different approaches have been widely applied at regional scale throughout synthetic indexes based on VIS, NIR and TIR spectral bands. A laboratory experiment has been carried out to verify a physically based model based on the remote estimation of the soil thermal inertia, P, to indirectly retrieve the soil surface water content, θ. The paper shows laboratory retrievals using simultaneously a FLIR A320G thermal camera, a six bands customized TETRACAM MCA II (Multiple Camera Array) multispectral camera working in the VIS/NIR part of the spectrum. Using these two type of sensors a set of VIS/NIR and TIR images were acquired as the main input dataset to retrieve the spatial variability of the thermal inertia values. Moreover, given that the accuracy of the proposed approach strongly depends on the accurate estimation of the soil thermal conductivity, a Decagon Device KD2 PRO thermal

  16. A Gravitational Edge Detection for Multispectral Images

    Directory of Open Access Journals (Sweden)

    Genyun Sun

    2013-07-01

    Full Text Available Gravitational edge detection is one of the new edge detection algorithms that is based on the law of gravity. This algorithm assumes that each image pixel is a celestial body with a mass represented by its grayscale intensity and their interactions are based on the Newtonian laws of gravity. In this article, a multispectral version of the algorithm is introduced. The method uses gravitational techniques in combination with metric tensor to detect edges of multispectral images including color images. To evaluate the performances of the proposed algorithm, several experiments are performed. The experimental results confirm the efficiency of the multispectral gravitational edge detection.  

  17. SWNT Imaging Using Multispectral Image Processing

    Science.gov (United States)

    Blades, Michael; Pirbhai, Massooma; Rotkin, Slava V.

    2012-02-01

    A flexible optical system was developed to image carbon single-wall nanotube (SWNT) photoluminescence using the multispectral capabilities of a typical CCD camcorder. The built in Bayer filter of the CCD camera was utilized, using OpenCV C++ libraries for image processing, to decompose the image generated in a high magnification epifluorescence microscope setup into three pseudo-color channels. By carefully calibrating the filter beforehand, it was possible to extract spectral data from these channels, and effectively isolate the SWNT signals from the background.

  18. Cucumber disease diagnosis using multispectral images

    Science.gov (United States)

    Feng, Jie; Li, Hongning; Shi, Junsheng; Yang, Weiping; Liao, Ningfang

    2009-07-01

    In this paper, multispectral imaging technique for plant diseases diagnosis is presented. Firstly, multispectral imaging system is designed. This system utilizes 15 narrow-band filters, a panchromatic band, a monochrome CCD camera, and standard illumination observing environment. The spectral reflectance and color of 8 Macbeth color patches are reproduced between 400nm and 700nm in the process. In addition, spectral reflectance angle and color difference is obtained through measurements and analysis of color patches using spectrometer and multispectral imaging system. The result shows that 16 narrow-bands multispectral imaging system realizes good accuracy in spectral reflectance and color reproduction. Secondly, a horticultural plant, cucumber' familiar disease are the researching objects. 210 multispectral samples are obtained by multispectral and are classified by BP artificial neural network. The classification accuracies of Sphaerotheca fuliginea, Corynespora cassiicola, Pseudoperonospora cubensis are 100%. Trichothecium roseum and Cladosporium cucumerinum are 96.67% and 90.00%. It is confirmed that the multispectral imaging system realizes good accuracy in the cucumber diseases diagnosis.

  19. Simultaneous denoising and compression of multispectral images

    Science.gov (United States)

    Hagag, Ahmed; Amin, Mohamed; Abd El-Samie, Fathi E.

    2013-01-01

    A new technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process is presented. One type of multispectral images has been considered: Landsat Enhanced Thematic Mapper Plus. The discrete wavelet transform (DWT), the dual-tree DWT, and a simple Huffman coder are used in the compression process. Simulation results show that the proposed technique is more effective than other traditional compression-only techniques.

  20. Multispectral image segmentation of breast pathology

    Science.gov (United States)

    Hornak, Joseph P.; Blaakman, Andre; Rubens, Deborah; Totterman, Saara

    1991-06-01

    The signal intensity in a magnetic resonance image is not only a function of imaging parameters but also of several intrinsic tissue properties. Therefore, unlike other medical imaging modalities, magnetic resonance imaging (MRI) allows the imaging scientist to locate pathology using multispectral image segmentation. Multispectral image segmentation works best when orthogonal spectral regions are employed. In MRI, possible spectral regions are spin density (rho) , spin-lattice relaxation time T1, spin-spin relaxation time T2, and texture for each nucleus type and chemical shift. This study examines the ability of multispectral image segmentation to locate breast pathology using the total hydrogen T1, T2, and (rho) . The preliminary results indicate that our technique can locate cysts and fibroadenoma breast lesions with a minimum number of false-positives and false-negatives. Results, T1, T2, and (rho) algorithms, and segmentation techniques are presented.

  1. Multispectral and Photoplethysmography Optical Imaging Techniques Identify Important Tissue Characteristics in an Animal Model of Tangential Burn Excision.

    Science.gov (United States)

    Thatcher, Jeffrey E; Li, Weizhi; Rodriguez-Vaqueiro, Yolanda; Squiers, John J; Mo, Weirong; Lu, Yang; Plant, Kevin D; Sellke, Eric; King, Darlene R; Fan, Wensheng; Martinez-Lorenzo, Jose A; DiMaio, J Michael

    2016-01-01

    Burn excision, a difficult technique owing to the training required to identify the extent and depth of injury, will benefit from a tool that can cue the surgeon as to where and how much to resect. We explored two rapid and noninvasive optical imaging techniques in their ability to identify burn tissue from the viable wound bed using an animal model of tangential burn excision. Photoplethysmography (PPG) imaging and multispectral imaging (MSI) were used to image the initial, intermediate, and final stages of burn excision of a deep partial-thickness burn. PPG imaging maps blood flow in the skin's microcirculation, and MSI collects the tissue reflectance spectrum in visible and infrared wavelengths of light to classify tissue based on a reference library. A porcine deep partial-thickness burn model was generated and serial tangential excision accomplished with an electric dermatome set to 1.0 mm depth. Excised eschar was stained with hematoxylin and eosin to determine the extent of burn remaining at each excision depth. We confirmed that the PPG imaging device showed significantly less blood flow where burn tissue was present, and the MSI method could delineate burn tissue in the wound bed from the viable wound bed. These results were confirmed independently by a histological analysis. We found these devices can identify the proper depth of excision, and their images could cue a surgeon as to the preparedness of the wound bed for grafting. These image outputs are expected to facilitate clinical judgment in the operating room.

  2. Estimating atmospheric parameters and reducing noise for multispectral imaging

    Science.gov (United States)

    Conger, James Lynn

    2014-02-25

    A method and system for estimating atmospheric radiance and transmittance. An atmospheric estimation system is divided into a first phase and a second phase. The first phase inputs an observed multispectral image and an initial estimate of the atmospheric radiance and transmittance for each spectral band and calculates the atmospheric radiance and transmittance for each spectral band, which can be used to generate a "corrected" multispectral image that is an estimate of the surface multispectral image. The second phase inputs the observed multispectral image and the surface multispectral image that was generated by the first phase and removes noise from the surface multispectral image by smoothing out change in average deviations of temperatures.

  3. 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.

  4. Multispectral Imaging of Wok-Fried Vegetables

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Dissing, Bjørn Skovlund; Hyldig, Grethe;

    2012-01-01

    Quality control in the food industry is often performed by measuring various chemical compounds in the food involved. The authors propose an imaging concept for acquiring high-quality multispectral images to evaluate optical reflection changes in carrots and celeriac over a period of 14 days...

  5. Quality assessment of butter cookies applying multispectral imaging

    DEFF Research Database (Denmark)

    Stenby Andresen, Mette; Dissing, Bjørn Skovlund; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were...... in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis...

  6. Multispectral imaging of wok fried vegetables

    DEFF Research Database (Denmark)

    Løje, Hanne; Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder;

    2011-01-01

    This paper shows how multispectral images can be used to assess color change over time in wok fried vegetables. We present results where feature selection was performed with sparse methods from the multispectral images to detect the color changes of wok fried carrots and celeriac stored at +5°C...... over 14 days. A pairwise t-test was used to detect if the differences over days were significant. For both the original as well as a follow experiment significant differences were seen in particular for celeriac, but also to some extend for carrots....

  7. Multispectral imaging using a single bucket detector.

    Science.gov (United States)

    Bian, Liheng; Suo, Jinli; Situ, Guohai; Li, Ziwei; Fan, Jingtao; Chen, Feng; Dai, Qionghai

    2016-04-22

    Existing multispectral imagers mostly use available array sensors to separately measure 2D data slices in a 3D spatial-spectral data cube. Thus they suffer from low photon efficiency, limited spectrum range and high cost. To address these issues, we propose to conduct multispectral imaging using a single bucket detector, to take full advantage of its high sensitivity, wide spectrum range, low cost, small size and light weight. Technically, utilizing the detector's fast response, a scene's 3D spatial-spectral information is multiplexed into a dense 1D measurement sequence and then demultiplexed computationally under the single pixel imaging scheme. A proof-of-concept setup is built to capture multispectral data of 64 pixels × 64 pixels × 10 wavelength bands ranging from 450 nm to 650 nm, with the acquisition time being 1 minute. The imaging scheme holds great potentials for various low light and airborne applications, and can be easily manufactured as production-volume portable multispectral imagers.

  8. Multispectral Image Enhancement Through Adaptive Wavelet Fusion

    Science.gov (United States)

    2017-02-08

    Filtering. PeerJ Computer Science, 2, e72. doi: 10.7717/peerj-cs.72. https://peerj.com/articles/cs-72/ 6 Coloring multiband night vision images...decompose the source images into base and detail layers at multiple levels of resolution. Then, frequency-tuned filtering is used to compute saliency...obtains state-of-the-art performance for the fusion of multispectral night vision images. The method has a simple implementation and is computationally

  9. Comparison of multispectral images across the Internet

    NARCIS (Netherlands)

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

    2000-01-01

    Comparison in the RGB domain is not suitable for precise color matching, due to the strong dependency of this domain on factors like spectral power distribution of the light source and object geometry. We have studied the use of multispectral or hyperspectral images for color matching, since it can

  10. Characteristic variogram for land use in Multispectral Images

    Science.gov (United States)

    Mera, E.; Condal, A.; Rios, C.; Da Silva, L.

    2016-05-01

    In remote sensing is the concept of spectral signature in multispectral imagery to recognize different land uses in the area; This study proposes the existence of a characteristic variogram for land use in multispectral images. To test this idea we proceeded to work with a sector of a scene image of multispectral Landsat 7 ETM +, in 6 of their bands (1- 450nm to 520nm, 2 - 520nm to 600nm, 3 - 630nm to 690nm, 4 - 760nm to 900nm 5 - over 1550nm to 1.750nm and 7 - 2.080nm to 2.350nm), corresponding to two uses of urban land and agricultural, the omnidirectional variogram for each band was analyzed and modal variogram for each land use was established in the stripe set. Of the analyzed claims data for each land use is a model characteristic and modal cross variogram how their wavelengths.

  11. Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

    DEFF Research Database (Denmark)

    Peng, Yi; Xiong, Xiong; Adhikari, Kabindra

    2015-01-01

    results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain...

  12. Multispectral imaging of aircraft exhaust

    Science.gov (United States)

    Berkson, Emily E.; Messinger, David W.

    2016-05-01

    Aircraft pollutants emitted during the landing-takeoff (LTO) cycle have significant effects on the local air quality surrounding airports. There are currently no inexpensive, portable, and unobtrusive sensors to quantify the amount of pollutants emitted from aircraft engines throughout the LTO cycle or to monitor the spatial-temporal extent of the exhaust plume. We seek to thoroughly characterize the unburned hydrocarbon (UHC) emissions from jet engine plumes and to design a portable imaging system to remotely quantify the emitted UHCs and temporally track the distribution of the plume. This paper shows results from the radiometric modeling of a jet engine exhaust plume and describes a prototype long-wave infrared imaging system capable of meeting the above requirements. The plume was modeled with vegetation and sky backgrounds, and filters were selected to maximize the detectivity of the plume. Initial calculations yield a look-up chart, which relates the minimum amount of emitted UHCs required to detect the presence of a plume to the noise-equivalent radiance of a system. Future work will aim to deploy the prototype imaging system at the Greater Rochester International Airport to assess the applicability of the system on a national scale. This project will help monitor the local pollution surrounding airports and allow better-informed decision-making regarding emission caps and pollution bylaws.

  13. Multispectral imaging using a single bucket detector

    CERN Document Server

    Bian, Liheng; Situ, Guohai; Li, Ziwei; Chen, Feng; Dai, Qionghai

    2015-01-01

    Current multispectral imagers suffer from low photon efficiency and limited spectrum range. These limitations are partially due to the technological limitations from array sensors (CCD or CMOS), and also caused by separative measurement of the entries/slices of a spatial-spectral data cube. Besides, they are mostly expensive and bulky. To address above issues, this paper proposes to image the 3D multispectral data with a single bucket detector in a multiplexing way. Under the single pixel imaging scheme, we project spatial-spectral modulated illumination onto the target scene to encode the scene's 3D information into a 1D measurement sequence. Conventional spatial modulation is used to resolve the scene's spatial information. To avoid increasing requisite acquisition time for 2D to 3D extension of the latent data, we conduct spectral modulation in a frequency-division multiplexing manner in the speed gap between slow spatial light modulation and fast detector response. Then the sequential reconstruction falls...

  14. Multispectral Imaging in Cultural Heritage Conservation

    Science.gov (United States)

    Del Pozo, S.; Rodríguez-Gonzálvez, P.; Sánchez-Aparicio, L. J.; Muñoz-Nieto, A.; Hernández-López, D.; Felipe-García, B.; González-Aguilera, D.

    2017-08-01

    This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum). In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

  15. MULTISPECTRAL IMAGING IN CULTURAL HERITAGE CONSERVATION

    Directory of Open Access Journals (Sweden)

    S. Del Pozo

    2017-08-01

    Full Text Available This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum. In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

  16. Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra.

    Science.gov (United States)

    Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

    2015-01-01

    There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l'Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the 'upland model' was able to more accurately predict SOC compared with the 'upland & wetland model'. However, the separately calibrated 'upland and wetland model' did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis

  17. Multispectral imaging of acute wound tissue oxygenation

    Directory of Open Access Journals (Sweden)

    Audrey Huong

    2017-05-01

    Full Text Available This paper investigates the appropriate range of values for the transcutaneous blood oxygen saturation (StO2 of granulating tissues and the surrounding tissue that can ensure timely wound recovery. This work has used a multispectral imaging system to collect wound images at wavelengths ranging between 520nm and 600nm with a resolution of 10nm. As part of this research, a pilot study was conducted on three injured individuals with superficial wounds of different wound ages at different skin locations. The StO2 value predicted for the examined wounds using the Extended Modified Lambert–Beer model revealed a mean StO2 of 61±10.3% compared to 41.6±6.2% at the surrounding tissues, and 50.1±1.53% for control sites. These preliminary results contribute to the existing knowledge on the possible range and variation of wound bed StO2 that are to be used as indicators of the functioning of the vasomotion system and wound health. This study has concluded that a high StO2 of approximately 60% and a large fluctuation in this value should precede a good progression in wound healing.

  18. MULTISPECTRAL IMAGE ANALYSIS USING RANDOM FOREST

    OpenAIRE

    Barrett Lowe; Arun Kulkarni

    2015-01-01

    Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman proposed Random Forestin 2001 for classification and clustering. Random Forest grows many decision tre...

  19. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

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

    2012-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. The pellets were divided into two groups: one with pellets coated using synthetic astaxanthin in fish oil and the other with pellets coated...... images were pixel spectral values as well as using summary statistics such as the mean or median value of each pellet. Classification using LDA on pellet mean or median values showed overall good results. Multispectral imaging is a promising technique for noninvasive on-line quality food and feed...... products with optimal use of pigment and minimum amount of waste....

  20. Time-resolved multispectral imaging of combustion reaction

    Science.gov (United States)

    Huot, Alexandrine; Gagnon, Marc-André; Jahjah, Karl-Alexandre; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Lagueux, Philippe; Guyot, Éric; Chamberland, Martin; Marcotte, Fréderick

    2015-05-01

    Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal broadband cameras. This allows to perform target characterization in both the longwave (LWIR) and midwave (MWIR) infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases such as carbon dioxide (CO2) selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range. Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge about spectral emissivity. This information is not directly available from broadband images. However, spectral information is available using spectral filters. In this work, combustion analysis was carried out using Telops MS-IR MW camera which allows multispectral imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profile derived from information obtained with the different spectral filters. Comparison with temperatures obtained using conventional broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion processes.

  1. Time-resolved multispectral imaging of combustion reactions

    Science.gov (United States)

    Huot, Alexandrine; Gagnon, Marc-André; Jahjah, Karl-Alexandre; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Lagueux, Philippe; Guyot, Éric; Chamberland, Martin; Marcotte, Frédérick

    2015-10-01

    Thermal infrared imaging is a field of science that evolves rapidly. Scientists have used for years the simplest tool: thermal broadband cameras. These allow to perform target characterization in both the longwave (LWIR) and midwave (MWIR) infrared spectral range. Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. For example, it can be used to follow combustion reactions, in order to characterize the injection and the ignition in a combustion chamber or even to observe gases produced by a flare or smokestack. Most combustion gases, such as carbon dioxide (CO2), selectively absorb/emit infrared radiation at discrete energies, i.e. over a very narrow spectral range. Therefore, temperatures derived from broadband imaging are not reliable without prior knowledge of spectral emissivity. This information is not directly available from broadband images. However, spectral information is available using spectral filters. In this work, combustion analysis was carried out using a Telops MS-IR MW camera, which allows multispectral imaging at a high frame rate. A motorized filter wheel allowing synchronized acquisitions on eight (8) different channels was used to provide time-resolved multispectral imaging of combustion products of a candle in which black powder has been burnt to create a burst. It was then possible to estimate the temperature by modeling spectral profiles derived from information obtained with the different spectral filters. Comparison with temperatures obtained using conventional broadband imaging illustrates the benefits of time-resolved multispectral imaging for the characterization of combustion processes.

  2. Code-excited linear predictive coding of multispectral MR images

    Science.gov (United States)

    Hu, Jian-Hong; Wang, Yao; Cahill, Patrick

    1996-02-01

    This paper reports a multispectral code excited linear predictive coding method for the compression of well-registered multispectral MR images. Different linear prediction models and the adaptation schemes have been compared. The method which uses forward adaptive autoregressive (AR) model has proven to achieve a good compromise between performance, complexity and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over non-overlapping square macroblocks. Each macro-block is further divided into several micro-blocks and, the best excitation signals for each microblock are determined through an analysis-by-synthesis procedure. To satisfy the high quality requirement for medical images, the error between the original images and the synthesized ones are further specified using a vector quantizer. The MFCELP method has been applied to 26 sets of clinical MR neuro images (20 slices/set, 3 spectral bands/slice, 256 by 256 pixels/image, 12 bits/pixel). It provides a significant improvement over the discrete cosine transform (DCT) based JPEG method, a wavelet transform based embedded zero-tree wavelet (EZW) coding method, as well as the MSARMA method we developed before.

  3. Multispectral imaging for medical diagnosis

    Science.gov (United States)

    Anselmo, V. J.

    1977-01-01

    Photography technique determines amount of morbidity present in tissue. Imaging apparatus incorporates numerical filtering. Overall system operates in near-real time. Information gained from this system enables physician to understand extent of injury and leads to accelerated treatment.

  4. Quality assessment of butter cookies applying multispectral imaging

    Science.gov (United States)

    Andresen, Mette S; Dissing, Bjørn S; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center. PMID:24804036

  5. Efficient lossless compression scheme for multispectral images

    Science.gov (United States)

    Benazza-Benyahia, Amel; Hamdi, Mohamed; Pesquet, Jean-Christophe

    2001-12-01

    Huge amounts of data are generated thanks to the continuous improvement of remote sensing systems. Archiving this tremendous volume of data is a real challenge which requires lossless compression techniques. Furthermore, progressive coding constitutes a desirable feature for telebrowsing. To this purpose, a compact and pyramidal representation of the input image has to be generated. Separable multiresolution decompositions have already been proposed for multicomponent images allowing each band to be decomposed separately. It seems however more appropriate to exploit also the spectral correlations. For hyperspectral images, the solution is to apply a 3D decomposition according to the spatial and to the spectral dimensions. This approach is not appropriate for multispectral images because of the reduced number of spectral bands. In recent works, we have proposed a nonlinear subband decomposition scheme with perfect reconstruction which exploits efficiently both the spatial and the spectral redundancies contained in multispectral images. In this paper, the problem of coding the coefficients of the resulting subband decomposition is addressed. More precisely, we propose an extension to the vector case of Shapiro's embedded zerotrees of wavelet coefficients (V-EZW) with achieves further saving in the bit stream. Simulations carried out on SPOT images indicate the outperformance of the global compression package we performed.

  6. SLIM for multispectral FRET imaging

    Science.gov (United States)

    Rück, A.; Dolp, F.; Steiner, R.; Steinmetz, C.; von Einem, B.; von Arnim, C. A. F.

    2008-02-01

    Spectral fluorescence lifetime imaging (SLIM) is an advanced imaging technique, which combines spectral with time resolved detection. Real spectral information is achieved by using a grating in front of a PML-array, which allows time-correlated single photon counting (TCSPC). Whereas spectrally resolved fluorescence imaging alone has a reasonable sensitivity, the specificity of fluorescence detection can be improved by considering the fluorescence lifetime. The various possibilities which SLIM offers to improve FRET (resonant energy transfer) will be discussed as well as successfully realized applications. These include FRET measurements for protein interactions, related to Alzheimer's disease. Special attention will be focused on molecules involved in the processing and trafficking of the amyloid precursor protein (APP), as trafficking proteins of the GGA family and β-secretase BACE). Taking into account also the lifetime of the acceptor could enhance reliability of the FRET result.

  7. Multispectral image fusion based on fractal features

    Science.gov (United States)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  8. Supervised Classification Performance of Multispectral Images

    CERN Document Server

    Perumal, K

    2010-01-01

    Nowadays government and private agencies use remote sensing imagery for a wide range of applications from military applications to farm development. The images may be a panchromatic, multispectral, hyperspectral or even ultraspectral of terra bytes. Remote sensing image classification is one amongst the most significant application worlds for remote sensing. A few number of image classification algorithms have proved good precision in classifying remote sensing data. But, of late, due to the increasing spatiotemporal dimensions of the remote sensing data, traditional classification algorithms have exposed weaknesses necessitating further research in the field of remote sensing image classification. So an efficient classifier is needed to classify the remote sensing images to extract information. We are experimenting with both supervised and unsupervised classification. Here we compare the different classification methods and their performances. It is found that Mahalanobis classifier performed the best in our...

  9. Image quality (IQ) guided multispectral image compression

    Science.gov (United States)

    Zheng, Yufeng; Chen, Genshe; Wang, Zhonghai; Blasch, Erik

    2016-05-01

    Image compression is necessary for data transportation, which saves both transferring time and storage space. In this paper, we focus on our discussion on lossy compression. There are many standard image formats and corresponding compression algorithms, for examples, JPEG (DCT -- discrete cosine transform), JPEG 2000 (DWT -- discrete wavelet transform), BPG (better portable graphics) and TIFF (LZW -- Lempel-Ziv-Welch). The image quality (IQ) of decompressed image will be measured by numerical metrics such as root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural Similarity (SSIM) Index. Given an image and a specified IQ, we will investigate how to select a compression method and its parameters to achieve an expected compression. Our scenario consists of 3 steps. The first step is to compress a set of interested images by varying parameters and compute their IQs for each compression method. The second step is to create several regression models per compression method after analyzing the IQ-measurement versus compression-parameter from a number of compressed images. The third step is to compress the given image with the specified IQ using the selected compression method (JPEG, JPEG2000, BPG, or TIFF) according to the regressed models. The IQ may be specified by a compression ratio (e.g., 100), then we will select the compression method of the highest IQ (SSIM, or PSNR). Or the IQ may be specified by a IQ metric (e.g., SSIM = 0.8, or PSNR = 50), then we will select the compression method of the highest compression ratio. Our experiments tested on thermal (long-wave infrared) images (in gray scales) showed very promising results.

  10. Image Fusion Techniques for Multispectral Palm Image Enhancement

    OpenAIRE

    Rajashree Bhokare; Deepali Sale; Dr. (Mrs. ) M. A. Joshi; Dr. M. S. Gaikwad

    2013-01-01

    We proposed the multispectral image enhancement through image fusion by combining the data from the multiple spectrum to address the problem of accuracy and make the system robust against spoofing and to improve the accuracy of recognition, using more discriminating of palm images. Palm line features are clearer in the blue and green bands while red band can reveal some palm vein structure. The NIR band can show the palm vein structure as well as partial line information. Image fusion improve...

  11. Multispectral filter array design without training images

    Science.gov (United States)

    Shinoda, Kazuma; Yanagi, Yudai; Hayasaki, Yoshio; Hasegawa, Madoka

    2017-08-01

    Multispectral images (MSIs) have been studied for many applications; however, limitations persist in techniques to capture them due to the complexity of assembling one or more prisms and multiple sensor arrays in order to detect signals. Inspired by the application of color filter arrays to commercial digital RGB cameras, a number of researchers have studied multispectral filter arrays (MSFAs) to solve this problem. Determining the measurement wavelength and pattern of an MSFA is important for improving the quality of the demosaicked image. Some conventional studies for designing MSFAs have used training data and have optimized the measurement wavelengths and the pattern by iteratively minimizing the error between the training data and the demosaicked images. We propose a metric to evaluate an MSFA without MSIs, and optimize the measurement wavelengths and the pattern of the MSFA by minimizing the metric. The proposed metric measures the sampling distance between filters in a spatial-spectral domain and quantifies the dispersion of the sampling points by average nearest-neighbor distance (ANND) under a given arbitrary MSFA. Since the quality of the demosaicked image is assumed to be proportional to the degree of dispersion of the sampling points in the spatial-spectral domain, we optimize the MSFA by minimizing the ANND in a nested simulated annealing process. Experimental results show that the optimized MSFA obtained using our method attained a higher peak signal-to-noise ratio (PSNR) than conventional untrained MSFAs in many cases. In addition, the performance difference between some trained MSFAs and the proposed MSFA was small. We also confirmed the validity of the proposed ANND by a comparison with the mean square error obtained from MSI datasets.

  12. Multispectral filter array design without training images

    Science.gov (United States)

    Shinoda, Kazuma; Yanagi, Yudai; Hayasaki, Yoshio; Hasegawa, Madoka

    2017-06-01

    Multispectral images (MSIs) have been studied for many applications; however, limitations persist in techniques to capture them due to the complexity of assembling one or more prisms and multiple sensor arrays in order to detect signals. Inspired by the application of color filter arrays to commercial digital RGB cameras, a number of researchers have studied multispectral filter arrays (MSFAs) to solve this problem. Determining the measurement wavelength and pattern of an MSFA is important for improving the quality of the demosaicked image. Some conventional studies for designing MSFAs have used training data and have optimized the measurement wavelengths and the pattern by iteratively minimizing the error between the training data and the demosaicked images. We propose a metric to evaluate an MSFA without MSIs, and optimize the measurement wavelengths and the pattern of the MSFA by minimizing the metric. The proposed metric measures the sampling distance between filters in a spatial-spectral domain and quantifies the dispersion of the sampling points by average nearest-neighbor distance (ANND) under a given arbitrary MSFA. Since the quality of the demosaicked image is assumed to be proportional to the degree of dispersion of the sampling points in the spatial-spectral domain, we optimize the MSFA by minimizing the ANND in a nested simulated annealing process. Experimental results show that the optimized MSFA obtained using our method attained a higher peak signal-to-noise ratio (PSNR) than conventional untrained MSFAs in many cases. In addition, the performance difference between some trained MSFAs and the proposed MSFA was small. We also confirmed the validity of the proposed ANND by a comparison with the mean square error obtained from MSI datasets.

  13. Slantlet Transform for Multispectral Image Fusion

    Directory of Open Access Journals (Sweden)

    Adnan H.M. Al-Helali

    2009-01-01

    Full Text Available Problem statement: Image fusion is a process by which multispectral and panchromatic images, or some of their features, are combined together to form a high spatial/high spectral resolutions image. The successful fusion of images acquired from different modalities or instruments is a great importance issue in remote sensing applications. Approach: A new method of image fusion was introduced. It was based on a hybrid transform, which is an extension of Ridgelet transform. It used the slantlet transform instead of wavelet transform in the final steps of Ridgelet transform. The slantlet transform was an orthogonal discrete wavelet transform with two zero moments and with improved time localization. Results: Since edges and noise played fundamental role in image understanding, this hybrid transform was proved to be good way to enhance the edges and reduce the noise. Conclusion: The proposed method of fusion presented richer information in spatial and spectral domains simultaneously as well as it had reached an optimum fusion result.

  14. Merging Panchromatic and Multispectral Images for Enhanced Image Analysis

    Science.gov (United States)

    1990-08-01

    Multispectral Images for Enhanced Image Analysis I, Curtis K. Munechika grant permission to the Wallace Memorial Library of the Rochester Institute of...0.0 ()0 (.0(%C’ trees 3. 5 2.5% 0.0%l 44. 1% 5 (.()0th ,crass .1 ().W 0.0% 0).0% 97. overall classification accuracy: 87.5%( T-able DlIb . Confusion

  15. Utilization of Multispectral Images for Meat Color Measurements

    DEFF Research Database (Denmark)

    Trinderup, Camilla Himmelstrup; Dahl, Anders Lindbjerg; Carstensen, Jens Michael;

    2013-01-01

    This short paper describes how the use of multispectral imaging for color measurement can be utilized in an efficient and descriptive way for meat scientists. The basis of the study is meat color measurements performed with a multispectral imaging system as well as with a standard colorimeter....... It is described how different color spaces can enhance the purpose of the analysis - whether that is investigation of a single sample or a comparison between samples. Moreover the study describes how a simple segmentation can be applied to the multispectral images in order to reach a more descriptive measure...... of color and color variance than what is obtained by the standard colorimeter....

  16. Fast Lossless Compression of Multispectral-Image Data

    Science.gov (United States)

    Klimesh, Matthew

    2006-01-01

    An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive-filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

  17. Vicarious Calibration of Beijing-1 Multispectral Imagers

    Directory of Open Access Journals (Sweden)

    Zhengchao Chen

    2014-02-01

    Full Text Available For on-orbit calibration of the Beijing-1 multispectral imagers (Beijing-1/MS, a field calibration campaign was performed at the Dunhuang calibration site during September and October of 2008. Based on the in situ data and images from Beijing-1 and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS, three vicarious calibration methods (i.e., reflectance-based, irradiance-based, and cross-calibration were used to calculate the top-of-atmosphere (TOA radiance of Beijing-1. An analysis was then performed to determine or identify systematic and accidental errors, and the overall uncertainty was assessed for each individual method. The findings show that the reflectance-based method has an uncertainty of more than 10% if the aerosol optical depth (AOD exceeds 0.2. The cross-calibration method is able to reach an error level within 7% if the images are selected carefully. The final calibration coefficients were derived from the irradiance-based data for 6 September 2008, with an uncertainty estimated to be less than 5%.

  18. Compact multi-spectral imaging system for dermatology and neurosurgery

    Science.gov (United States)

    Noordmans, Herke Jan; de Roode, Rowland; Verdaasdonk, Rudolf

    2007-03-01

    A compact multi-spectral imaging system is presented as diagnostic tool in dermatology and neurosurgery. Using an electronically tunable filter, a sensitive high resolution digital camera, 140 spectral images from 400 nm up to 720 nm are acquired in 40 s. Advanced image processing algorithms are used to enable interactive acquisition, viewing, image registration and image analysis. Experiments in the department of dermatology and neurosurgery show that multispectral imaging reveals much more detail than conventional medical photography or a surgical microscope, as images can be reprocessed to enhance the view on e.g. tumor boundaries. Using a hardware-based interactive registration algorithm, multi-spectral images can be aligned to correct for motion occurred during image acquisition or to compare acquisitions from different moments in time. The system shows to be a powerful diagnostics tool for medical imaging in the visual and near IR range.

  19. Fuzzy Markov random fields versus chains for multispectral image segmentation.

    Science.gov (United States)

    Salzenstein, Fabien; Collet, Christophe

    2006-11-01

    This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov chain model is developed in an unsupervised way. This method is compared with the fuzzy Markovian field model previously proposed by one of the authors. The segmentation task is processed with Bayesian tools, such as the well-known MPM (Mode of Posterior Marginals) criterion. Our goal is to compare the robustness and rapidity for both methods (fuzzy Markov fields versus fuzzy Markov chains). Indeed, such fuzzy-based procedures seem to be a good answer, e.g., for astronomical observations when the patterns present diffuse structures. Moreover, these approaches allow us to process missing data in one or several spectral bands which correspond to specific situations in astronomy. To validate both models, we perform and compare the segmentation on synthetic images and raw multispectral astronomical data.

  20. Multispectral Image Capturing with Foveon Sensors

    Science.gov (United States)

    Gehrke, R.; Greiwe, A.

    2013-08-01

    This article describes a specific image quality problem using an UAV and the commercially available multispectral camera Tetracam ADC Lite. The tests were carried out with commercially available UAV Multirotor MR-X 8 performed under normal use and conditions. The ADC Lite shows a remarkable rolling shutter effect caused by the movement and vibrations of the UAV and a slow readout speed of the sensor. Based on these studies the current state of a sensor development is presented, which is composed of two compact cameras with Foveon sensors. These cameras allow to record high quality image data without motion blur or rolling shutter effect. One camera captures the normal colour range; the second camera is modified for the near infrared. The moving parts of both cameras are glued to ensure that a geometric camera calibration is valid over a longer period of time. The success of the gluing procedure has been proven by multiple calibrations. For the matching of the colour- and infrared image the usability of calibrated relative orientation parameters between both cameras were tested. Despite absolutely synchronous triggering of the cameras by an electrical signal, a time delay can be found up to 3/100 s between the images. This time delay in combination with the movement and rotation of the UAV while taking the photos results in a significant error in the previously calibrated relative orientation. These parameters should not be used in further processing. This article concludes with a first result of a 4-channel image and an outlook on the following investigations.

  1. Monitoring human melanocytic cell responses to piperine using multispectral imaging

    Science.gov (United States)

    Samatham, Ravikant; Phillips, Kevin G.; Sonka, Julia; Yelma, Aznegashe; Reddy, Neha; Vanka, Meenakshi; Thuillier, Philippe; Soumyanath, Amala; Jacques, Steven

    2011-03-01

    Vitiligo is a depigmentary disease characterized by melanocyte loss attributed most commonly to autoimmune mechanisms. Currently vitiligo has a high incidence (1% worldwide) but a poor set of treatment options. Piperine, a compound found in black pepper, is a potential treatment for the depigmentary skin disease vitiligo, due to its ability to stimulate mouse epidermal melanocyte proliferation in vitro and in vivo. The present study investigates the use of multispectral imaging and an image processing technique based on local contrast to quantify the stimulatory effects of piperine on human melanocyte proliferation in reconstructed epidermis. We demonstrate the ability of the imaging method to quantify increased pigmentation in response to piperine treatment. The quantization of melanocyte stimulation by the proposed imaging technique illustrates the potential use of this technology to quickly assess therapeutic responses of vitiligo tissue culture models to treatment non-invasively.

  2. Multispectral image filtering method based on image fusion

    Science.gov (United States)

    Zhang, Wei; Chen, Wei

    2015-12-01

    This paper proposed a novel filter scheme by image fusion based on Nonsubsampled ContourletTransform(NSCT) for multispectral image. Firstly, an adaptive median filter is proposed which shows great advantage in speed and weak edge preserving. Secondly, the algorithm put bilateral filter and adaptive median filter on image respectively and gets two denoised images. Then perform NSCT multi-scale decomposition on the de-noised images and get detail sub-band and approximate sub-band. Thirdly, the detail sub-band and approximate sub-band are fused respectively. Finally, the object image is obtained by inverse NSCT. Simulation results show that the method has strong adaptability to deal with the textural images. And it can suppress noise effectively and preserve the image details. This algorithm has better filter performance than the Bilateral filter standard and median filter and theirs improved algorithms for different noise ratio.

  3. Mixture Segmentation of Multispectral MR Brain Images for Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Lihong Li

    2005-04-01

    Full Text Available We present a fully automatic mixture model-based tissue classification of multispectral (T1- and T2-weighted magnetic resonance (MR brain images. Unlike the conventional hard classification with a unique label for each voxel, our method models a mixture to estimate the partial volumes (PV of multiple tissue types within a voxel. A new Markov random field (MRF model is proposed to reflect the spatial information of tissue mixtures. A mixture classification algorithm is performed by the maximum a posterior (MAP criterion, where the expectation maximization (EM algorithm is utilized to estimate model parameters. The algorithm interleaves segmentation with parameter estimation and improves classification in an iterative manner. The presented method is evaluated by clinical MR image datasets for quantification of brain volumes and multiple sclerosis (MS.

  4. Multispectral Stokes polarimetry for dermatoscopic imaging

    Science.gov (United States)

    Castillejos, Y.; Martínez-Ponce, Geminiano; Mora-Nuñez, Azael; Castro-Sanchez, R.

    2015-12-01

    Most of skin pathologies, including melanoma and basal/squamous cell carcinoma, are related to alterations in external and internal order. Usually, physicians rely on their empirical expertise to diagnose these ills normally assisted with dermatoscopes. When there exists skin cancer suspicion, a cytology or biopsy is made, but both laboratory tests imply an invasive procedure. In this regard, a number of non-invasive optical techniques have been proposed recently to improve the diagnostic certainty and assist in the early detection of cutaneous cancer. Herein, skin optical properties are derived with a multispectral polarimetric dermatoscope using three different illumination wavelength intervals centered at 470, 530 and 635nm. The optical device consist of two polarizing elements, a quarter-wave plate and a linear polarizer, rotating at a different angular velocity and a CCD array as the photoreceiver. The modulated signal provided by a single pixel in the acquired image sequence is analyzed with the aim of computing the Stokes parameters. Changes in polarization state of selected wavelengths provide information about the presence of skin pigments such as melanin and hemoglobin species as well as collagen structure, among other components. These skin attributes determine the local physiology or pathology. From the results, it is concluded that optical polarimetry will provide additional elements to dermatologists in their diagnostic task.

  5. Whole-body and multispectral photoacoustic imaging of adult zebrafish

    Science.gov (United States)

    Huang, Na; Xi, Lei

    2016-10-01

    Zebrafish is a top vertebrate model to study developmental biology and genetics, and it is becoming increasingly popular for studying human diseases due to its high genome similarity to that of humans and the optical transparency in embryonic stages. However, it becomes difficult for pure optical imaging techniques to volumetric visualize the internal organs and structures of wild-type zebrafish in juvenile and adult stages with excellent resolution and penetration depth. Even with the establishment of mutant lines which remain transparent over the life cycle, it is still a challenge for pure optical imaging modalities to image the whole body of adult zebrafish with micro-scale resolution. However, the method called photoacoustic imaging that combines all the advantages of the optical imaging and ultrasonic imaging provides a new way to image the whole body of the zebrafish. In this work, we developed a non-invasive photoacoustic imaging system with optimized near-infrared illumination and cylindrical scanning to image the zebrafish. The lateral and axial resolution yield to 80 μm and 600 μm, respectively. Multispectral strategy with wavelengths from 690 nm to 930 nm was employed to image various organs inside the zebrafish. From the reconstructed images, most major organs and structures inside the body can be precisely imaged. Quantitative and statistical analysis of absorption for organs under illumination with different wavelengths were carried out.

  6. Precise acquisition and unsupervised segmentation of multi-spectral images

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2007-01-01

    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral images and a novel multi-spectral image segmentation algorithm are proposed. The system collects up to 20 different spectral bands within a range that vary from 395 nm to 970 nm. The system is designed...... to acquire geometrically and chromatically corrected images in homogeneous and diffuse illumination, so images can be compared over time. The proposed segmentation algorithm combines the information provided by all the spectral bands to segment the different regions of interest. Three experiments...

  7. Multispectral image pansharpening based on the contourlet transform

    Energy Technology Data Exchange (ETDEWEB)

    Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

    2010-02-01

    Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

  8. In vivo imaging of cancer cells with electroporation of quantum dots and multispectral imaging

    Science.gov (United States)

    Yoo, Jung Sun; Won, Nayoun; Kim, Hong Bae; Bang, Jiwon; Kim, Sungjee; Ahn, Saeyoung; Soh, Kwang-Sup

    2010-06-01

    Our understanding of dissemination and growth of cancer cells is limited by our inability for long-term followup of this process in vivo. Fluorescence molecular imaging has the potential to track cancer cells with high contrast and sensitivity in living animals. For this purpose, intracellular delivery of near-infrared fluorescence quantum dots (QDs) by electroporation offers considerable advantages over organic fluorophores and other cell tagging methods. In this research we developed a multispectral imaging system that could eliminate two major parameters compromising in vivo fluorescence imaging performance, i.e., variations in the tissue optical properties and tissue autofluorescence. We demonstrated that electroporation of QDs and multispectral imaging allowed in vivo assessment of cancer development and progression in the xenograft mouse tumor model for more than 1 month, providing a powerful means to learn more about the biology of cancer and metastasis.

  9. Multispectral code excited linear prediction coding and its application in magnetic resonance images.

    Science.gov (United States)

    Hu, J H; Wang, Y; Cahill, P T

    1997-01-01

    This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

  10. Use of Multispectral Imaging in Varietal Identification of Tomato

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Olesen, Merete Halkjær

    2015-01-01

    Abstract: Multispectral imaging is an emerging non-destructive technology. In this work its potential for varietal discrimination and identification of tomato cultivars of Nepal was investigated. Two sample sets were used for the study, one with two parents and their crosses and other with eleven...... of parents and offspring. nCDA was also used for pairwise discrimination of the eleven cultivars, which correctly discriminated upto 100% and only few pairs below 85%. Partial least square discriminant analysis (PLS-DA) was further used to classify all the cultivars. The model displayed an overall...... classification accuracy of 82%, which was further improved to 96% and 86% with stepwise PLS-DA models on high (seven) and poor (four) sensitivity cultivars, respectively. The stepwise PLS-DA models had satisfactory classification errors for cross-validation and prediction 7% and 7%, respectively. The results...

  11. Pollutant monitoring of aircraft exhaust with multispectral imaging

    Science.gov (United States)

    Berkson, Emily E.; Messinger, David W.

    2016-10-01

    Communities surrounding local airports are becoming increasingly concerned about the aircraft pollutants emitted during the landing-takeoff (LTO) cycle, and their potential for negative health effects. Chicago, Los Angeles, Boston and London have all recently been featured in the news regarding concerns over the amount of airport pollution being emitted on a daily basis, and several studies have been published on the increased risks of cancer for those living near airports. There are currently no inexpensive, portable, and unobtrusive sensors that can monitor the spatial and temporal nature of jet engine exhaust plumes. In this work we seek to design a multispectral imaging system that is capable of tracking exhaust plumes during the engine idle phase, with a specific focus on unburned hydrocarbon (UHC) emissions. UHCs are especially potent to local air quality, and their strong absorption features allow them to act as a spatial and temporal plume tracer. Using a Gaussian plume to radiometrically model jet engine exhaust, we have begun designing an inexpensive, portable, and unobtrusive imaging system to monitor the relative amount of pollutants emitted by aircraft in the idle phase. The LWIR system will use two broadband filters to detect emitted UHCs. This paper presents the spatial and temporal radiometric models of the exhaust plume from a typical jet engine used on 737s. We also select filters for plume tracking, and propose an imaging system layout for optimal detectibility. In terms of feasibility, a multispectral imaging system will be two orders of magnitude cheaper than current unobtrusive methods (PTR-MS) used to monitor jet engine emissions. Large-scale impacts of this work will include increased capabilities to monitor local airport pollution, and the potential for better-informed decision-making regarding future developments to airports.

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

    Science.gov (United States)

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

    2017-02-01

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

  13. Transmittance spectroscopy and transmitted multispectral imaging to map covered paints

    Directory of Open Access Journals (Sweden)

    Antonino Cosentino

    2016-01-01

    Full Text Available Transmitted spectroscopy and transmitted multispectral imaging in the 400-900 nm range have been applied for the mapping and tentative identification of paints covered by a white preparation as in the case of a ground laid for reusing a canvas for another painting. These methods can be applied to polychrome works of art, as long as their support and new preparation are sufficiently translucent. This work presents the transmittance spectra acquired from a test board consisting of a prepared canvas with swatches of 54 pigments covered with titanium white and the multispectral images realized with transmitted light to map covered paints on a mock-up painting. It was observed that 18 out of 54 historical pigments provide characteristic transmittance spectra even underneath a titanium white preparation layer and that transmitted light multispectral imaging can map hidden paint layers.

  14. Determining quality and maturity of pomegranates using multispectral imaging

    Directory of Open Access Journals (Sweden)

    Rasool Khodabakhshian

    2017-10-01

    Full Text Available In this paper, we investigated the use of multispectral imaging technique to quantify pomegranate fruit quality. Three quality factors including total soluble solids (TSS, pH and firmness were studied at four different maturity stages of 88, 109, 124 and 143 days after full bloom (DAFB and were correlated with the spectral information extracted from images taken at four wavelength spectra. TSS, pH and firmness of the same samples were recorded using nondestructive methods and then modeled with their corresponding spectral data using partial least squire regression (PLSR. The correlation coefficient (r, RMSEC and RPD for the calibration models was found to be: r = 0.97, RMSEC = 0.21 °Brix and RPD = 6.7 °Brix for TSS; r = 0.93, RMSEC = 0.035 and RPD = 5.01 for pH; r = 0.95, RMSEC = 0.65 N and RPD = 5.65 N for firmness. Also these parameters for the validation models were as follows: r = 0.97, RMSEP = 0.22 °Brix and RPD = 5.77 °Brix for TSS; r = 0.94, RMSEP = 0.038 and RPD = 4.98 for pH; r = 0.94, RMSEP = 0.68 N and RPD = 5.33 N for firmness. The results demonstrated the capability of multispectral imaging and chemometrics as useful techniques to nondestructively monitoring pomegranate main quality attributes.

  15. Multispectral UV imaging for determination of the tablet coating thickness

    DEFF Research Database (Denmark)

    Novikova, Anna; Carstensen, Jens Michael; Zeitler, J. Axel

    2017-01-01

    The applicability of off-line multispectral ultraviolet (UV) imaging in combination with multivariate data analysis was investigated to determine the coating thickness and its distribution on the tablet surface during lab scale coating. The UV imaging results were compared with the weight gain...

  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. Viability Prediction of Ricinus cummunis L. Seeds Using Multispectral Imaging

    DEFF Research Database (Denmark)

    Olesen, Merete Halkjær; Nikneshan, Pejman; Shrestha, Santosh;

    2015-01-01

    The purpose of this study was to highlight the use of multispectral imaging in seed quality testing of castor seeds. Visually, 120 seeds were divided into three classes: yellow, grey and black seeds. Thereafter, images at 19 different wavelengths ranging from 375–970 nm were captured of all the s...

  18. Chemometrics in multispectral imaging for quality inspection of postharvest products

    NARCIS (Netherlands)

    Noordam, Jan Corstiaan

    2005-01-01

    This thesis describes different novel chemometric techniques applied to multispectral images for quality inspection on agricultural food products. These images do not only have a huge number of spectral bands which makes training set selection a challenging task, they also contain classes with small

  19. Detection of sudden death syndrome using a multispectral imaging sensor

    Science.gov (United States)

    Sudden death syndrome (SDS), caused by the fungus Fusarium solani f. sp. glycines, is a widespread mid- to late-season disease with distinctive foliar symptoms. This paper reported the development of an image analysis based method to detect SDS using a multispectral image sensor. A hue, saturation a...

  20. Multispectral Microscopic Imager (MMI): Multispectral Imaging of Geological Materials at a Handlens Scale

    Science.gov (United States)

    Farmer, J. D.; Nunez, J. I.; Sellar, R. G.; Gardner, P. B.; Manatt, K. S.; Dingizian, A.; Dudik, M. J.; McDonnell, G.; Le, T.; Thomas, J. A.; Chu, K.

    2011-12-01

    The Multispectral Microscopic Imager (MMI) is a prototype instrument presently under development for future astrobiological missions to Mars. The MMI is designed to be a arm-mounted rover instrument for use in characterizing the microtexture and mineralogy of materials along geological traverses [1,2,3]. Such geological information is regarded as essential for interpreting petrogenesis and geological history, and when acquired in near real-time, can support hypothesis-driven exploration and optimize science return. Correlated microtexure and mineralogy also provides essential data for selecting samples for analysis with onboard lab instruments, and for prioritizing samples for potential Earth return. The MMI design employs multispectral light-emitting diodes (LEDs) and an uncooled focal plane array to achieve the low-mass (Robotic Arm Camera (RAC; 5) and the Mars Science Laboratory's Mars Hand Lens Imager (MAHLI; 6). In this report we will review the capabilities of the MMI by highlighting recent lab and field applications, including: 1) glove box deployments in the Astromaterials lab at Johnson Space Center to analyze Apollo lunar samples; 2) GeoLab glove box deployments during the 2011 Desert RATS field trials in northern AZ to characterize analog materials collected by astronauts during simulated EVAs; 3) field deployments on Mauna Kea Volcano, Hawaii, during NASA's 2010 ISRU field trials, to analyze materials at the primary feedstock mining site; 4) lab characterization of geological samples from a complex, volcanic-hydrothermal terrain in the Cady Mts., SE Mojave Desert, California. We will show how field and laboratory applications have helped drive the development and refinement of MMI capabilities, while identifying synergies with other potential payload instruments (e.g. X-ray Diffraction) for solving real geological problems.

  1. 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.

  2. Multispectral and panchromatic image fusion based on unsubsampled contourlet transform

    Science.gov (United States)

    Liu, Hui; Yuan, Yan; Su, Lijuan; Hu, Liang; Zhang, Siyuan

    2013-12-01

    In order to achieve the high-resolution multispectral image, we proposed an algorithm for MS image and PAN image fusion based on NSCT and improved fusion rule. This method takes into account two aspects, the spectral similarity between fused image and the original MS image and enhancing the spatial resolution of the fused image. According to local spectral similarity between MS and PAN images, it can help to select high frequency detail coefficients from PAN image, which are injected into MS image then. Thus, spectral distortion is limited; the spatial resolution is enhanced. The experimental results demonstrate that the proposed fusion algorithm perform some improvements in integrating MS and PAN images.

  3. Using Multispectral Imaging for Spoilage Detection of Pork Meat

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Papadopoulou, Olga S.; Tassou, Chrysoula

    2013-01-01

    The quality of stored minced pork meat was monitored using a rapid multispectral imaging device to quantify the degree of spoilage. Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two...... different storage conditions: aerobic and modified atmosphere packages as well as under different temperatures. Besides bacterial counts, a sensory panel has judged the spoilage degree of all meat samples into one of three classes. Results showed that the multispectral imaging device was able to classify 76...... for the detection of spoilage degree in minced pork meat....

  4. Multispectral Thermal Imager (MTI) Payload Overview

    Energy Technology Data Exchange (ETDEWEB)

    Bender, S.C.; Brock, B.C.; Bullington, D.M.; Byrd, D.A.; Claassen, P.J.; Decker, M.L.; Henson, T.D.; Kay, R.R.; Kidner, R.E.; Lanes, C.E.; Little, C.; Marbach, K.D.; Rackley, N.G.; Rienstra, J.L.; Smith, B.W.; Taplin, R.B.; Weber, P.G.

    1999-07-07

    MTI is a comprehensive research and development project that includes up-front modeling and analysis, satellite system design, fabrication, assembly and testing, on-orbit operations, and experimentation and data analysis. The satellite is designed to collect radiometrically calibrated, medium resolution imagery in 15 spectral bands ranging from 0.45 to 10.70 pm. The payload portion of the satellite includes the imaging system components, associated electronics boxes, and payload support structure. The imaging system includes a three-mirror anastigmatic off-axis telescope, a single cryogenically cooled focal plane assembly, a mechanical cooler, and an onboard calibration system. Payload electronic subsystems include image digitizers, real-time image compressors, a solid state recorder, calibration source drivers, and cooler temperature and vibration controllers. The payload support structure mechanically integrates all payload components and provides a simple four point interface to the spacecraft bus. All payload components have been fabricated and tested, and integrated.

  5. Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

    Directory of Open Access Journals (Sweden)

    Changhong Liu

    Full Text Available Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS, support vector machine (SVM and back propagation neural network (BPNN, were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

  6. High Throughput Multispectral Image Processing with Applications in Food Science.

    Science.gov (United States)

    Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

    2015-01-01

    Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  7. High Throughput Multispectral Image Processing with Applications in Food Science.

    Directory of Open Access Journals (Sweden)

    Panagiotis Tsakanikas

    Full Text Available Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  8. High Throughput Multispectral Image Processing with Applications in Food Science

    Science.gov (United States)

    Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

    2015-01-01

    Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing’s outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples. PMID:26466349

  9. Calibration for Relative Interior Orientation Relationship and Band-to-band Registration with High Accuracy of ZY-3 Multi-spectral Image

    Directory of Open Access Journals (Sweden)

    LI Qijun

    2016-06-01

    Full Text Available Using high accuracy match points extracted between the multi-spectral images that obtained at the same time,a position model of the CCD chips of the ZY-3 multi-spectral camera was proposed. Relative interior orientation relationship parameters were calculated and accurate band-to-band automatic registration of ZY-3 multi-spectral image was achieved based on the position model. The experimental result indicates that the band-to-band automatic registration accuracy of ZY-3 multi-spectral image is better than 0.3 pixels with the proposed method.

  10. 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.

  11. A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Weihua Dong

    2014-09-01

    Full Text Available This article focuses on the image fusion of high-resolution panchromatic and multispectral images. We propose a new image fusion method based on a Hue-Saturation-Value (HSV color space model and bidimensional empirical mode decomposition (BEMD, by integrating high-frequency component of panchromatic image into multispectral image and optimizing the BEMD in decreasing sifting time, simplifying extrema point locating and more efficient interpolation. This new method has been tested with a panchromatic image (SPOT, 10-m resolution and a multispectral image (TM, 28-m resolution. Visual and quantitative assessment methods are applied to evaluate the quality of the fused images. The experimental results show that the proposed method provided superior performance over conventional fusion algorithms in improving the quality of the fused images in terms of visual effectiveness, standard deviation, correlation coefficient, bias index and degree of distortion. Both five different land cover types WorldView-II images and three different sensor combinations (TM/SPOT, WorldView-II, 0.5 m/1 m resolution and IKONOS, 1 m/4 m resolution validated the robustness of BEMD fusion performance. Both of these results prove the capability of the proposed BEMD method as a robust image fusion method to prevent color distortion and enhance image detail.

  12. Retinal oxygen saturation evaluation by multi-spectral fundus imaging

    Science.gov (United States)

    Khoobehi, Bahram; Ning, Jinfeng; Puissegur, Elise; Bordeaux, Kimberly; Balasubramanian, Madhusudhanan; Beach, James

    2007-03-01

    Purpose: To develop a multi-spectral method to measure oxygen saturation of the retina in the human eye. Methods: Five Cynomolgus monkeys with normal eyes were anesthetized with intramuscular ketamine/xylazine and intravenous pentobarbital. Multi-spectral fundus imaging was performed in five monkeys with a commercial fundus camera equipped with a liquid crystal tuned filter in the illumination light path and a 16-bit digital camera. Recording parameters were controlled with software written specifically for the application. Seven images at successively longer oxygen-sensing wavelengths were recorded within 4 seconds. Individual images for each wavelength were captured in less than 100 msec of flash illumination. Slightly misaligned images of separate wavelengths due to slight eye motion were registered and corrected by translational and rotational image registration prior to analysis. Numerical values of relative oxygen saturation of retinal arteries and veins and the underlying tissue in between the artery/vein pairs were evaluated by an algorithm previously described, but which is now corrected for blood volume from averaged pixels (n > 1000). Color saturation maps were constructed by applying the algorithm at each image pixel using a Matlab script. Results: Both the numerical values of relative oxygen saturation and the saturation maps correspond to the physiological condition, that is, in a normal retina, the artery is more saturated than the tissue and the tissue is more saturated than the vein. With the multi-spectral fundus camera and proper registration of the multi-wavelength images, we were able to determine oxygen saturation in the primate retinal structures on a tolerable time scale which is applicable to human subjects. Conclusions: Seven wavelength multi-spectral imagery can be used to measure oxygen saturation in retinal artery, vein, and tissue (microcirculation). This technique is safe and can be used to monitor oxygen uptake in humans. This work

  13. Integration, Testing, and Analysis of Multispectral Imager on Small Unmanned Aerial System for Skin Detection

    Science.gov (United States)

    2014-03-01

    INTEGRATION, TESTING, AND ANALYSIS OF MULTISPECTRAL IMAGER ON SMALL UNMANNED AERIAL SYSTEM FOR SKIN......12 2.5 Image Registration ................................................................................................16 2.6

  14. Pulsed Raman fiber laser and multispectral imaging in three dimensions

    DEFF Research Database (Denmark)

    Andersen, Joachim F.; Busck, Jens; Heiselberg, Henning

    2006-01-01

    Raman scattering in single-mode optical fibers is exploited to generate multispectral light from a green nanolaser with high pulse repetition rate. Each pulse triggers a picosecond camera and measures the distance by time-of-flight in each of the 0.5 Mpixels. Three-dimensional images are then con......Raman scattering in single-mode optical fibers is exploited to generate multispectral light from a green nanolaser with high pulse repetition rate. Each pulse triggers a picosecond camera and measures the distance by time-of-flight in each of the 0.5 Mpixels. Three-dimensional images...... are then constructed with submillimeter accuracy for all visible colors. The generation of a series of Stokes peaks by Raman scattering in a Si fiber is discussed in detail and the laser radar technique is demonstrated. The data recording takes only a few seconds, and the high accuracy 3D color imaging works at ranges...

  15. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease

    Science.gov (United States)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-07-01

    Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  16. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    Energy Technology Data Exchange (ETDEWEB)

    Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

    2016-07-15

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  17. Multispectral imaging using a stereo camera: concept, design and assessment

    Directory of Open Access Journals (Sweden)

    Mansouri Alamin

    2011-01-01

    Full Text Available Abstract This paper proposes a one-shot six-channel multispectral color image acquisition system using a stereo camera and a pair of optical filters. The two filters from the best pair, selected from among readily available filters such that they modify the sensitivities of the two cameras in such a way that they produce optimal estimation of spectral reflectance and/or color, are placed in front of the two lenses of the stereo camera. The two images acquired from the stereo camera are then registered for pixel-to-pixel correspondence. The spectral reflectance and/or color at each pixel on the scene are estimated from the corresponding camera outputs in the two images. Both simulations and experiments have shown that the proposed system performs well both spectrally and colorimetrically. Since it acquires the multispectral images in one shot, the proposed system can solve the limitations of slow and complex acquisition process, and costliness of the state of the art multispectral imaging systems, leading to its possible uses in widespread applications.

  18. Rayleigh-Rice Mixture Parameter Estimation via EM Algorithm for Change Detection in Multispectral Images.

    Science.gov (United States)

    Zanetti, Massimo; Bovolo, Francesca; Bruzzone, Lorenzo

    2015-12-01

    The problem of estimating the parameters of a Rayleigh-Rice mixture density is often encountered in image analysis (e.g., remote sensing and medical image processing). In this paper, we address this general problem in the framework of change detection (CD) in multitemporal and multispectral images. One widely used approach to CD in multispectral images is based on the change vector analysis. Here, the distribution of the magnitude of the difference image can be theoretically modeled by a Rayleigh-Rice mixture density. However, given the complexity of this model, in applications, a Gaussian-mixture approximation is often considered, which may affect the CD results. In this paper, we present a novel technique for parameter estimation of the Rayleigh-Rice density that is based on a specific definition of the expectation-maximization algorithm. The proposed technique, which is characterized by good theoretical properties, iteratively updates the parameters and does not depend on specific optimization routines. Several numerical experiments on synthetic data demonstrate the effectiveness of the method, which is general and can be applied to any image processing problem involving the Rayleigh-Rice mixture density. In the CD context, the Rayleigh-Rice model (which is theoretically derived) outperforms other empirical models. Experiments on real multitemporal and multispectral remote sensing images confirm the validity of the model by returning significantly higher CD accuracies than those obtained by using the state-of-the-art approaches.

  19. Multispectral Cerenkov luminescence tomography for small animal optical imaging.

    Science.gov (United States)

    Spinelli, Antonello E; Kuo, Chaincy; Rice, Brad W; Calandrino, Riccardo; Marzola, Pasquina; Sbarbati, Andrea; Boschi, Federico

    2011-06-20

    Quite recently Cerenkov luminescence imaging (CLI) has been introduced as a novel pre-clinical imaging for the in vivo imaging of small animals such as mice. The CLI method is based on the detection of Cerenkov radiation (CR) generated by beta particles as they travel into the animal tissues with an energy such that Cerenkov emission condition is satisfied. This paper describes an image reconstruction method called multi spectral diffuse Cerenkov luminescence tomography (msCLT) in order to obtain 3D images from the detection of CR. The multispectral approach is based on a set of 2D planar images acquired using a number of narrow bandpass filters, and the distinctive information content at each wavelength is used in the 3D image reconstruction process. The proposed msCLT method was tested both in vitro and in vivo using 32P-ATP and all the images were acquired by using the IVIS 200 small animal optical imager (Caliper Life Sciences, Alameda USA). Source depth estimation and spatial resolution measurements were performed using a small capillary source placed between several slices of chicken breast. The theoretical Cerenkov emission spectrum and optical properties of chicken breast were used in the modelling of photon propagation. In vivo imaging was performed by injecting control nude mice with 10 MBq of 32P-ATP and the 3D tracer bio-distribution was reconstructed. Whole body MRI was acquired to provide an anatomical localization of the Cerenkov emission. The spatial resolution obtained from the msCLT reconstructed images of the capillary source showed that the FWHM is about 1.5 mm for a 6 mm depth. Co-registered MRI images showed that the Cerenkov emission regions matches fairly well with anatomical regions, such as the brain, heart and abdomen. Ex vivo imaging of the different organs such as intestine, brain, heart and ribs further confirms these findings. We conclude that in vivo 3D bio-distribution of a pure beta-minus emitting radiopharmaceutical such as 32P

  20. Extraction and classification of objects in multispectral images

    Science.gov (United States)

    Robertson, T. V.

    1973-01-01

    Presented here is an algorithm that partitions a digitized multispectral image into parts that correspond to objects in the scene being sensed. The algorithm partitions an image into successively smaller rectangles and produces a partition that tends to minimize a criterion function. Supervised and unsupervised classification techniques can be applied to partitioned images. This partition-then-classify approach is used to process images sensed from aircraft and the ERTS-1 satellite, and the method is shown to give relatively accurate results in classifying agricultural areas and extracting urban areas.

  1. Multispectral image analysis for object recognition and classification

    Science.gov (United States)

    Viau, C. R.; Payeur, P.; Cretu, A.-M.

    2016-05-01

    Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

  2. Adaptive ladar receiver for multispectral imaging

    Science.gov (United States)

    Johnson, Kenneth; Vaidyanathan, Mohan; Xue, Song; Tennant, William E.; Kozlowski, Lester J.; Hughes, Gary W.; Smith, Duane D.

    2001-09-01

    We are developing a novel 2D focal plane array (FPA) with read-out integrated circuit (ROIC) on a single chip for 3D laser radar imaging. The ladar will provide high-resolution range and range-resolved intensity images for detection and identification of difficult targets. The initial full imaging-camera-on-a-chip system will be a 64 by 64 element, 100-micrometers pixel-size detector array that is directly bump bonded to a low-noise 64 by 64 array silicon CMOS-based ROIC. The architecture is scalable to 256 by 256 or higher arrays depending on the system application. The system will provide all the required electronic processing at pixel level and the smart FPA enables directly producing the 3D or 4D format data to be captured with a single laser pulse. The detector arrays are made of uncooled InGaAs PIN device for SWIR imaging at 1.5 micrometers wavelength and cooled HgCdTe PIN device for MWIR imaging at 3.8 micrometers wavelength. We are also investigating concepts using multi-color detector arrays for simultaneous imaging at multiple wavelengths that would provide additional spectral dimension capability for enhanced detection and identification of deep-hide targets. The system is suited for flash ladar imaging, for combat identification of ground targets from airborne platforms, flash-ladar imaging seekers, and autonomous robotic/automotive vehicle navigation and collision avoidance applications.

  3. Use of multispectral images and chemometrics in tomato seed studies

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

    During the production of tomato seeds, green tomatoes are normally discarded before seed extraction irrespective of their maturity stage. Studies indicate that seeds from green tomatoes may reach be able to reach full germination capacity. Thus the potential of multispectral imaging for non......-destructive discrimination of seeds based on their germination capacity was investigated. A total of 840 seeds extracted from green and red tomatoes were divided into two sets; a training set and a test set consisting of 648 and 192 seeds respectively. Each set consisted of 96 seeds from green tomatoes. The multispectral......, respectively. Similarly, dead seeds were predicted with 98% of accuracy. Results also showed that 23 and 14 seeds from green tomatoes in the training and test sets respectively were viable, while only one viable seed in the test set was misclassified. The results indicate that green tomatoes might be mature...

  4. [Research on maize multispectral image accurate segmentation and chlorophyll index estimation].

    Science.gov (United States)

    Wu, Qian; Sun, Hong; Li, Min-zan; Song, Yuan-yuan; Zhang, Yan-e

    2015-01-01

    value of each channel was calculated including red (ARed), green (AGreen), blue (ABlue), and near-infrared (ANIR). Meanwhile, the vegetation indices (NDVI (normalized difference vegetation index), RVI (ratio vegetation index); and NDGI(normalized difference green index)) which are widely used in remote sensing were applied. The chlorophyll index detecting model based on partial least squares regression method (PLSR) was built with detecting R2=0. 5960 and predicting R2= 0. 568 5. It was feasible to diagnose chlorophyll index of maize based on multi-spectral images.

  5. Development and bench testing of a multi-spectral imaging technology built on a smartphone platform

    Science.gov (United States)

    Bolton, Frank J.; Weiser, Reuven; Kass, Alex J.; Rose, Donny; Safir, Amit; Levitz, David

    2016-03-01

    Cervical cancer screening presents a great challenge for clinicians across the developing world. In many countries, cervical cancer screening is done by visualization with the naked eye. Simple brightfield white light imaging with photo documentation has been shown to make a significant impact on cervical cancer care. Adoption of smartphone based cervical imaging devices is increasing across Africa. However, advanced imaging technologies such as multispectral imaging systems, are seldom deployed in low resource settings, where they are needed most. To address this challenge, the optical system of a smartphone-based mobile colposcopy imaging system was refined, integrating components required for low cost, portable multi-spectral imaging of the cervix. This paper describes the refinement of the mobile colposcope to enable it to acquire images of the cervix at multiple illumination wavelengths, including modeling and laboratory testing. Wavelengths were selected to enable quantifying the main absorbers in tissue (oxyand deoxy-hemoglobin, and water), as well as scattering parameters that describe the size distribution of scatterers. The necessary hardware and software modifications are reviewed. Initial testing suggests the multi-spectral mobile device holds promise for use in low-resource settings.

  6. Multispectral image fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.; Roeske, F.; Donetti, J.G.; Fields, D.J.; sherwood, R.J.; Schaich, P.C.

    1995-04-01

    This report details a system which fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts.

  7. Fusion of Hyperspectral and Vhr Multispectral Image Classifications in Urban Areas

    Science.gov (United States)

    Hervieu, Alexandre; Le Bris, Arnaud; Mallet, Clément

    2016-06-01

    An energetical approach is proposed for classification decision fusion in urban areas using multispectral and hyperspectral imagery at distinct spatial resolutions. Hyperspectral data provides a great ability to discriminate land-cover classes while multispectral data, usually at higher spatial resolution, makes possible a more accurate spatial delineation of the classes. Hence, the aim here is to achieve the most accurate classification maps by taking advantage of both data sources at the decision level: spectral properties of the hyperspectral data and the geometrical resolution of multispectral images. More specifically, the proposed method takes into account probability class membership maps in order to improve the classification fusion process. Such probability maps are available using standard classification techniques such as Random Forests or Support Vector Machines. Classification probability maps are integrated into an energy framework where minimization of a given energy leads to better classification maps. The energy is minimized using a graph-cut method called quadratic pseudo-boolean optimization (QPBO) with ?-expansion. A first model is proposed that gives satisfactory results in terms of classification results and visual interpretation. This model is compared to a standard Potts models adapted to the considered problem. Finally, the model is enhanced by integrating the spatial contrast observed in the data source of higher spatial resolution (i.e., the multispectral image). Obtained results using the proposed energetical decision fusion process are shown on two urban multispectral/hyperspectral datasets. 2-3% improvement is noticed with respect to a Potts formulation and 3-8% compared to a single hyperspectral-based classification.

  8. A multispectral testbed for cardiovascular sensing using imaging photoplethysmography

    Science.gov (United States)

    Blackford, Ethan B.; Estepp, Justin R.

    2017-02-01

    Imaging photoplethysmography uses image sensors to measure changes in light absorption resulting from skin microvascular blood volume pulsations throughout the cardiac cycle. Imaging photoplethysmography has been demonstrated as an effective, non-contact means of assessing pulse rate, pulse rate variability, and respiration rate. Other potential uses include measuring spatial blood perfusion, oxygenation, and flow dynamics. Herein we demonstrate the development of a multispectral testbed for imaging photoplethysmography consisting of 12 monochromatic, 120fps imagers with 50nm, bandpass filters distributed from 400-750nm and contained in a 3D-printed, 4x3 grid housing mounted on a tripod positioned orthogonal to the subject. A co-located dual-CCD RGB/near-infrared imager records conventional RGB and NIR images expanding the spectral window recorded. After image registration, a multispectral image cube of the 13, partially overlapping bands is created. A spectrometer records high (spectral) resolution data from the participant's right cheek using a collimating lens attached to the measurement fiber. In addition, a spatial array of 5 RGB imagers placed at 0°, +/-20° and +/-40° positions with respect to the subject is employed for motion and spatial robustness. All imagers are synchronized by a hardware trigger source synchronized with a reference, physiological measurement device recording the subject's electrocardiography, bilateral fingertip and/or ear lobe photoplethysmography, bilateral galvanic skin response, and respiration signals. The development of the testbed and pilot data is presented. A full-scale evaluation of the spectral components of the imaging photoplethysmographic signal, optimization of iPPG SNR, and spatial perfusion and blood flow dynamics is currently underway.

  9. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

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

    2004-01-01

    . 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...

  10. High speed multispectral fluorescence lifetime imaging

    NARCIS (Netherlands)

    Fereidouni, F.; Reitsma, K.; Gerritsen, H.C.

    2013-01-01

    We report a spectrally resolved fluorescence lifetime imaging system based on time gated single photon detection with a fixed gate width of 200 ps and 7 spectral channels. Time gated systems can operate at high count rates but usually have large gate widths and sample only part of the fluorescence d

  11. Dual plasmonic gold nanoparticles for multispectral photoacoustic imaging application

    Science.gov (United States)

    Raghavan, Vijay; Subhash, Hrebesh; Breathnach, Aedán.; Leahy, Martin; Dockery, Peter; Olivo, Malini

    2014-03-01

    Nanoparticle contrast agents for molecular targeted imaging have widespread interest in diagnostic applications with cellular resolution, specificity and selectivity for visualization and assessment of various disease processes. Of particular interest is gold nanoparticle owing to its tunability of the surface plasmon resonance (SPR) and its relative inertness. Here we present the synthesis of anisotropic multi-branched star shaped gold nanoparticles exhibiting dual-band plasmon absorption peaks and its application as a contrast agent for multispectral photoacoustic imaging. The transverse plasmon absorption peak of the synthesised dual plasmonic gold nanostar (DPGNS) was around 700 nm and that of longitudinal plasmon absorption in the longer wavelength region around 1050-1150 nm. Unlike most reported PA contrast agent with surface plasmon absorption in the range of 700 to 800 nm showing moderate tissue penetration, 1050-1200 nm range lies in the farther region of the optical window of biological tissue where scattering and the intrinsic optical extinction of endogenous chromophores is at its minimum. We also present a proof of principle demonstration of DPGNS as contrast agent for multispectral photoacoustic animal imaging. Our results show that DPGNS are promising for PA imaging with extended-depth imaging applications.

  12. Land mine detection using multispectral image fusion

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.; Roeske, F.; Donetti, J.G.; Fields, D.J.; Sherwood, R.J.; Schaich, P.C.

    1995-03-29

    Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.

  13. Multispectral Imaging of Meat Quality - Color and Texture

    DEFF Research Database (Denmark)

    Trinderup, Camilla Himmelstrup

    of meat quality parameters, especially with regards to meat color and texture. Several image modalities have been applied, all considering multi- or hyper spectral imaging. The work demonstrates the use of computer vision systems for meat color measurements. The color is assessed by suitable...... transformations to the CIELAB color space, the common color space within food science. The results show that meat color assessment with a multispectral imaging is a great alternative to the traditional colorimeter, i.e. the vision system meets some of the limitations that the colorimeter possesses. To mention one......, it is possible to assess color of very complicated structures, such as salamis, with a vision system. More importantly though, the vision system embraces the complicated scattering properties of meat. The images can also lead to other analyses, e.g. image texture analysis relating to the structure of the meat...

  14. Multispectral imaging of organ viability during uterine transplantation surgery

    Science.gov (United States)

    Clancy, Neil T.; Saso, Srdjan; Stoyanov, Danail; Sauvage, Vincent; Corless, David J.; Boyd, Michael; Noakes, David E.; Thum, Meen-Yau; Ghaem-Maghami, Sadaf; Smith, J. R.; Elson, Daniel S.

    2014-02-01

    Uterine transplantation surgery has been proposed as a treatment for permanent absolute uterine factor infertility (AUFI) in the case of loss of the uterus. Due to the complexity of the vasculature correct reanastomosis of the blood supply during transplantation surgery is a crucial step to ensure reperfusion and viability of the organ. While techniques such as fluorescent dye imaging have been proposed to visualise perfusion there is no gold standard for intraoperative visualisation of tissue oxygenation. In this paper results from a liquid crystal tuneable filter (LCTF)-based multispectral imaging (MSI) laparoscope are described. The system was used to monitor uterine oxygen saturation (SaO2) before and after transplantation. Results from surgeries on two animal models (rabbits and sheep) are presented. A feature-based registration algorithm was used to correct for misalignment induced by breathing or peristalsis in the tissues of interest prior to analysis. An absorption spectrum was calculated at each spatial pixel location using reflectance data from a reference standard, and the relative contributions from oxy- and deoxyhaemoglobin were calculated using a least squares regression algorithm with non-negativity constraints. Results acquired during animal surgeries show that cornual oxygenation changes are consistent with those observed in point measurements taken using a pulse oximeter, showing reduced SaO2 following reanastomosis. Values obtained using the MSI laparoscope were lower than those taken with the pulse oximeter, which may be due to the latter's use of the pulsatile arterial blood signal. Future work incorporating immunological test results will help to correlate SaO2 levels with surgical outcomes.

  15. Multispectral therapeutic endoscopy imaging and intervention

    Science.gov (United States)

    Bala, John L.; Schwaitzberg, Steven D.

    2007-02-01

    With the debut of antibiotic drug therapy, and as a result of its ease of use and general success in treating infection, drugs have become the treatment of choice for most bacterial infections. However, the advent of multiple, very aggressive drug-resistant bacteria, an increasing population which cannot tolerate drugs, and the high cost of drug therapy suggest that a new modality for treating infections is needed. The complex interplay of clonal spread, persistence, transfer of resistance elements and cell-to-cell interaction all contribute to the difficulty in developing drugs to treat new antibiotic-resistant bacterial strains. A dynamic non-drug system, using extant pulsed ultraviolet lightwave technology to kill infection, is being developed to destroy pathogens. This paper theorizes that the shock effect of pulsed xenon's high energy ultraviolet pulses at wavelengths between 250-270nm separates the bacteria's DNA bands, and, subsequently, destroys them. Preliminary laboratory tests have demonstrated the ability of the technology to destroy Staphylococcus aureus, Pseudomonas aeruginosa Escherichia coli, Helicobacter pylori, Acinetobacter baumannii, Klebsiella punemonia, Bacillus subtillis, and Aspergillus fumigates at penetration depths of greater than 3mm in fluids with 100% effectiveness in less than five seconds of exposure to pulsed xenon lightwaves. Micro Invasive Technology, Inc is developing .pulsed xenon therapeutic catheters and endoscopic instruments for internal antimicrobial eradication and topographical devices for prophylactic wound, burn and surgical entrance/exit site sterilization. Pulsed Xenon light sources have a broad optical spectrum (190-1200nm), and can generate light pulses with sufficient energy for combined imaging and therapeutic intervention by multiplexing a fiber optic pathway into the body. In addition, Pulsed Xenon has proven ability to activate photo reactive dyes; share endoscopic lightguides with lasers while, simultaneously

  16. Multispectral Image Analysis for Robust Prediction of Astaxanthin Coating

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Frosch, Stina; Nielsen, Michael Engelbrecht

    2013-01-01

    The aim of this study was to investigate the possibility of predicting the type and concentration level of astaxanthin coating of aquaculture feed pellets using multispectral image analysis. We used both natural and synthetic astaxanthin, and we used several different concentration levels...... of synthetic astaxanthin in combination with four different recipes of feed pellets. We used a VideometerLab with 20 spectral bands in the range of 385-1050 nm. We used linear discriminant analysis and sparse linear discriminant analysis for classification and variable selection. We used partial least squares...

  17. An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

    Science.gov (United States)

    Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

    2017-09-01

    Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights

  18. Improving multispectral satellite image compression using onboard subpixel registration

    Science.gov (United States)

    Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin

    2013-09-01

    Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

  19. A Multispectral Micro-Imager for Lunar Field Geology

    Science.gov (United States)

    Nunez, Jorge; Farmer, Jack; Sellar, Glenn; Allen, Carlton

    2009-01-01

    Field geologists routinely assign rocks to one of three basic petrogenetic categories (igneous, sedimentary or metamorphic) based on microtextural and mineralogical information acquired with a simple magnifying lens. Indeed, such observations often comprise the core of interpretations of geological processes and history. The Multispectral Microscopic Imager (MMI) uses multi-wavelength, light-emitting diodes (LEDs) and a substrate-removed InGaAs focal-plane array to create multispectral, microscale reflectance images of geological samples (FOV 32 X 40 mm). Each pixel (62.5 microns) of an image is comprised of 21 spectral bands that extend from 470 to 1750 nm, enabling the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases. MMI images provide crucial context information for in situ robotic analyses using other onboard analytical instruments (e.g. XRD), or for the selection of return samples for analysis in terrestrial labs. To further assess the value of the MMI as a tool for lunar exploration, we used a field-portable, tripod-mounted version of the MMI to image a variety of Apollo samples housed at the Lunar Experiment Laboratory, NASA s Johnson Space Center. MMI images faithfully resolved the microtextural features of samples, while the application of ENVI-based spectral end member mapping methods revealed the distribution of Fe-bearing mineral phases (olivine, pyroxene and magnetite), along with plagioclase feldspars within samples. Samples included a broad range of lithologies and grain sizes. Our MMI-based petrogenetic interpretations compared favorably with thin section-based descriptions published in the Lunar Sample Compendium, revealing the value of MMI images for astronaut and rover-mediated lunar exploration.

  20. A Multispectral Micro-Imager for Lunar Field Geology

    Science.gov (United States)

    Nunez, Jorge; Farmer, Jack; Sellar, Glenn; Allen, Carlton

    2009-01-01

    Field geologists routinely assign rocks to one of three basic petrogenetic categories (igneous, sedimentary or metamorphic) based on microtextural and mineralogical information acquired with a simple magnifying lens. Indeed, such observations often comprise the core of interpretations of geological processes and history. The Multispectral Microscopic Imager (MMI) uses multi-wavelength, light-emitting diodes (LEDs) and a substrate-removed InGaAs focal-plane array to create multispectral, microscale reflectance images of geological samples (FOV 32 X 40 mm). Each pixel (62.5 microns) of an image is comprised of 21 spectral bands that extend from 470 to 1750 nm, enabling the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases. MMI images provide crucial context information for in situ robotic analyses using other onboard analytical instruments (e.g. XRD), or for the selection of return samples for analysis in terrestrial labs. To further assess the value of the MMI as a tool for lunar exploration, we used a field-portable, tripod-mounted version of the MMI to image a variety of Apollo samples housed at the Lunar Experiment Laboratory, NASA s Johnson Space Center. MMI images faithfully resolved the microtextural features of samples, while the application of ENVI-based spectral end member mapping methods revealed the distribution of Fe-bearing mineral phases (olivine, pyroxene and magnetite), along with plagioclase feldspars within samples. Samples included a broad range of lithologies and grain sizes. Our MMI-based petrogenetic interpretations compared favorably with thin section-based descriptions published in the Lunar Sample Compendium, revealing the value of MMI images for astronaut and rover-mediated lunar exploration.

  1. Multimodal tissue perfusion imaging using multi-spectral and thermographic imaging systems applied on clinical data

    Science.gov (United States)

    Klaessens, John H. G. M.; Nelisse, Martin; Verdaasdonk, Rudolf M.; Noordmans, Herke Jan

    2013-03-01

    Clinical interventions can cause changes in tissue perfusion, oxygenation or temperature. Real-time imaging of these phenomena could be useful for surgical strategy or understanding of physiological regulation mechanisms. Two noncontact imaging techniques were applied for imaging of large tissue areas: LED based multispectral imaging (MSI, 17 different wavelengths 370 nm-880 nm) and thermal imaging (7.5 to 13.5 μm). Oxygenation concentration changes were calculated using different analyzing methods. The advantages of these methods are presented for stationary and dynamic applications. Concentration calculations of chromophores in tissue require right choices of wavelengths The effects of different wavelength choices for hemoglobin concentration calculations were studied in laboratory conditions and consequently applied in clinical studies. Corrections for interferences during the clinical registrations (ambient light fluctuations, tissue movements) were performed. The wavelength dependency of the algorithms were studied and wavelength sets with the best results will be presented. The multispectral and thermal imaging systems were applied during clinical intervention studies: reperfusion of tissue flap transplantation (ENT), effectiveness of local anesthetic block and during open brain surgery in patients with epileptic seizures. The LED multispectral imaging system successfully imaged the perfusion and oxygenation changes during clinical interventions. The thermal images show local heat distributions over tissue areas as a result of changes in tissue perfusion. Multispectral imaging and thermal imaging provide complementary information and are promising techniques for real-time diagnostics of physiological processes in medicine.

  2. Statistical Quality Assessment of Pre-fried Carrots Using Multispectral Imaging

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Clemmensen, Line Katrine Harder; Løje, Hanne

    2013-01-01

    Multispectral imaging is increasingly being used for quality assessment of food items due to its non-invasive benefits. In this paper, we investigate the use of multispectral images of pre-fried carrots, to detect changes over a period of 14 days. The idea is to distinguish changes in quality from...

  3. Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

    Science.gov (United States)

    Shinoda, Kazuma; Watanabe, Aya; Hasegawa, Madoka; Kato, Shigeo

    2015-06-01

    Although it was expected that multispectral images would be implemented in many applications, such as remote sensing and medical imaging, their use has not been widely diffused in these fields. The development of a compact multispectral camera and display will be needed for practical use, but the format compatibility between multispectral and RGB images is also important for reducing the introduction cost and having high usability. We propose a method of embedding the spectral information into an RGB image by watermarking. The RGB image is calculated from the multispectral image, and then, the original multispectral image is estimated from the RGB image using Wiener estimation. The residual data between the original and the estimated multispectral image are compressed and embedded in the lower bit planes of the RGB image. The experimental results show that, as compared with Wiener estimation, the proposed method leads to more than a 10 dB gain in the peak signal-to-noise ratio of the reconstructed multispectral image, while there are almost no significant perceptual differences in the watermarked RGB image.

  4. Pairwise KLT-Based Compression for Multispectral Images

    Science.gov (United States)

    Nian, Yongjian; Liu, Yu; Ye, Zhen

    2016-12-01

    This paper presents a pairwise KLT-based compression algorithm for multispectral images. Although the KLT has been widely employed for spectral decorrelation, its complexity is high if it is performed on the global multispectral images. To solve this problem, this paper presented a pairwise KLT for spectral decorrelation, where KLT is only performed on two bands every time. First, KLT is performed on the first two adjacent bands and two principle components are obtained. Secondly, one remainning band and the principal component (PC) with the larger eigenvalue is selected to perform a KLT on this new couple. This procedure is repeated until the last band is reached. Finally, the optimal truncation technique of post-compression rate-distortion optimization is employed for the rate allocation of all the PCs, followed by embedded block coding with optimized truncation to generate the final bit-stream. Experimental results show that the proposed algorithm outperforms the algorithm based on global KLT. Moreover, the pairwise KLT structure can significantly reduce the complexity compared with a global KLT.

  5. Satellite multispectral data for improved floodplain roughness modelling

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2011-09-01

    SummaryRiparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This paper explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height ( h g) and flexural rigidity ( MEI) for herbaceous patterns and of plant density ( M), tree height ( h), stem diameter ( Ds), crown base height ( cbh) and crown diameter ( Dc) of high-forest ( hf) and coppice ( cop) consociations for arboreal and shrub patterns. The method is organized in four sequential steps: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the hydrodynamic impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived hydrodynamic parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate

  6. Multispectral imaging contributions to global land ice measurements from space

    Science.gov (United States)

    Kargel, J.S.; Abrams, M.J.; Bishop, M.P.; Bush, A.; Hamilton, G.; Jiskoot, H.; Kääb, Andreas; Kieffer, H.H.; Lee, E.M.; Paul, F.; Rau, F.; Raup, B.; Shroder, J.F.; Soltesz, D.; Stainforth, D.; Stearns, L.; Wessels, R.

    2005-01-01

    Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyse them for glacier extent and changes, and assess change data for causes and implications for people and the environment. Although GLIMS is making use of multiple remote-sensing systems, ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) is optimized for many needed observations, including mapping of glacier boundaries and material facies, and tracking of surface dynamics, such as flow vector fields and supraglacial lake development. Software development by GLIMS is geared toward mapping clean-ice and debris-covered glaciers; terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; multitemporal change analysis; visualization of images and derived data; and interpretation and archiving of derived data. A global glacier database has been designed at the National Snow and Ice Data Center (NSIDC, Boulder, Colorado); parameters are compatible with and expanded from those of the World Glacier Inventory (WGI). These technology efforts are summarized here, but will be presented in detail elsewhere. Our presentation here pertains to one broad question: How can ASTER and other satellite multispectral data be used to map, monitor, and characterize the state and dynamics of glaciers and to understand their responses to 20th and 21st century climate change? Our sampled results are not yet glaciologically or climatically representative. Our early results, while indicating complexity, are generally consistent with the glaciology community's conclusion that climate change is spurring glacier responses around the world (mainly retreat). Whether individual glaciers are advancing or retreating, the aggregate average of glacier change must be climatic in origin, as nonclimatic variations average out. We have discerned regional spatial patterns in glaciological response behavior

  7. Multispectral image compression methods for improvement of both colorimetric and spectral accuracy

    Science.gov (United States)

    Liang, Wei; Zeng, Ping; Xiao, Zhaolin; Xie, Kun

    2016-07-01

    We propose that both colorimetric and spectral distortion in compressed multispectral images can be reduced by a composite model, named OLCP(W)-X (OptimalLeaders_Color clustering-PCA-W weighted-X coding). In the model, first the spectral-colorimetric clustering is designed for sparse equivalent representation by generating spatial basis. Principal component analysis (PCA) is subsequently used in the manipulation of spatial basis for spectral redundancy removal. Then error compensation mechanism is presented to produce predicted difference image, and finally combined with visual characteristic matrix W, and the created image is compressed by traditional multispectral image coding schemes. We introduce four model-based algorithms to explain their validity. The first two algorithms are OLCPWKWS (OLC-PCA-W-KLT-WT-SPIHT) and OLCPKWS, in which Karhunen-Loeve transform, wavelet transform, and set partitioning in hierarchical trees coding are applied for the created image compression. And the latter two methods are OLCPW-JPEG2000-MCT and OLCP-JPEG2000-MCT. Experimental results show that, compared with the corresponding traditional coding, the proposed OLCPW-X schemes can significantly improve the colorimetric accuracy of rebuilding images under various illumination conditions and generally achieve satisfactory peak signal-to-noise ratio under the same compression ratio. And OLCP-X methods could always ensure superior spectrum reconstruction. Furthermore, our model has excellent performance on user interaction.

  8. Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images

    Science.gov (United States)

    Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.

    2012-12-01

    To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.

  9. High Resolution Multispectral Flow Imaging of Cells with Extended Depth of Field Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Proposed is the development the extended depth of field (EDF) or confocal like imaging capabilities of a breakthrough multispectral high resolution imaging flow...

  10. High Resolution Multispectral Flow Imaging of Cells with Extended Depth of Field Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Proposed is the development the extended depth of field (EDF) or confocal like imaging capabilities of a breakthrough multispectral high resolution imaging flow...

  11. Deepwater Horizon MC252 - Oil Spill: Ocean Imaging Corp.'s Aerial Multispectral Oil Mapping System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Ocean Imaging Corp.'s Aerial Multispectral Oil Mapping System employs a customizable 4-spectral channel system and IR imager integrated to allow simultaneous data...

  12. Research of the fuison methods of the multispectral optoelectronic systems images

    Science.gov (United States)

    Vasilev, Aleksandr S.; Korotaev, Valery V.

    2015-05-01

    This article is devoted to consideration of the issues relating to digital images fusion of the multispectral optoelectronic systems. The images fusion formation methods and methods are studied. Theoretical analysis of the methods was completed in the course of the work, mathematical simulation model of the multispectral optoelectronic systems was developed. Effect of various factors on the result of fusion was demonstrated on the basis of the said model investigation. The paper also considers and suggests the objective assessment methods of the fusion image quality. The paper describes the mostly widely used from the above: the averaging method, the masking technique fusion, the interlacing fusion, fusion of images Fourier spectrum. The quality of the resulting image was assessed on the basis of the calculation of the cross entropy, brightness dispersion and excess of the Fourier spectrum function. Based on the research findings we can state that the images obtained by the mask technique methods, by averaging and the Fourier spectrum fusion methods have the highest information entropy. The best quality feature, in terms of the brightness dispersion and excess of the Fourier spectrum function, was demonstrated by the averaging method. The method allows reducing noise components of an image on the account of smoothing of its local brightness variations smoothing thus the contrast is improved.

  13. Multispectral photoacoustic imaging of nerves with a clinical ultrasound system

    Science.gov (United States)

    Mari, Jean Martial; West, Simeon; Beard, Paul C.; Desjardins, Adrien E.

    2014-03-01

    Accurate and efficient identification of nerves is of great importance during many ultrasound-guided clinical procedures, including nerve blocks and prostate biopsies. It can be challenging to visualise nerves with conventional ultrasound imaging, however. One of the challenges is that nerves can have very similar appearances to nearby structures such as tendons. Several recent studies have highlighted the potential of near-infrared optical spectroscopy for differentiating nerves and adjacent tissues, as this modality can be sensitive to optical absorption of lipids that are present in intra- and extra-neural adipose tissue and in the myelin sheaths. These studies were limited to point measurements, however. In this pilot study, a custom photoacoustic system with a clinical ultrasound imaging probe was used to acquire multi-spectral photoacoustic images of nerves and tendons from swine ex vivo, across the wavelength range of 1100 to 1300 nm. Photoacoustic images were processed and overlaid in colour onto co-registered conventional ultrasound images that were acquired with the same imaging probe. A pronounced optical absorption peak centred at 1210 nm was observed in the photoacoustic signals obtained from nerves, and it was absent in those obtained from tendons. This absorption peak, which is consistent with the presence of lipids, provides a novel image contrast mechanism to significantly enhance the visualization of nerves. In particular, image contrast for nerves was up to 5.5 times greater with photoacoustic imaging (0.82 +/- 0.15) than with conventional ultrasound imaging (0.148 +/- 0.002), with a maximum contrast of 0.95 +/- 0.02 obtained in photoacoustic mode. This pilot study demonstrates the potential of photoacoustic imaging to improve clinical outcomes in ultrasound-guided interventions in regional anaesthesia and interventional oncology.

  14. Spatial clustering of pixels of a multispectral image

    Energy Technology Data Exchange (ETDEWEB)

    Conger, James Lynn

    2014-08-19

    A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

  15. Spatial clustering of pixels of a multispectral image

    Science.gov (United States)

    Conger, James Lynn

    2014-08-19

    A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

  16. Whole-body multispectral photoacoustic imaging of adult zebrafish

    Science.gov (United States)

    Huang, Na; Guo, Heng; Qi, Weizhi; Zhang, Zhiwei; Rong, Jian; Yuan, Zhen; Ge, Wei; Jiang, Huabei; Xi, Lei

    2016-01-01

    The zebrafish, an ideal vertebrate for studying developmental biology and genetics, is increasingly being used to understand human diseases, due to its high similarity to the human genome and its optical transparency during embryonic stages. Once the zebrafish has fully developed, especially wild-type breeds, conventional optical imaging techniques have difficulty in imaging the internal organs and structures with sufficient resolution and penetration depth. Even with established mutant lines that remain transparent throughout their life cycle, it is still challenging for purely optical imaging modalities to visualize the organs of juvenile and adult zebrafish at a micro-scale spatial resolution. In this work, we developed a non-invasive three-dimensional photoacoustic imaging platform with an optimized illumination pattern and a cylindrical-scanning-based data collection system to image entire zebrafish with micro-scale resolutions of 80 μm and 600 μm in the lateral and axial directions, respectively. In addition, we employed a multispectral strategy that utilized excitation wavelengths from 690 nm to 930 nm to statistically quantify the relative optical absorption spectrum of major organs. PMID:27699119

  17. High-contrast subcutaneous vein detection and localization using multispectral imaging

    Science.gov (United States)

    Wang, Fengtao; Behrooz, Ali; Morris, Michael; Adibi, Ali

    2013-05-01

    Multispectral imaging has shown promise in subcutaneous vein detection and localization in human subjects. While many limitations of single-wavelength methods are addressed in multispectral vein detection methods, their performance is still limited by artifacts arising from background skin reflectance and optimality of postprocessing algorithms. We propose a background removal technique that enhances the contrast and performance of multispectral vein detection. We use images acquired at visible wavelengths as reference for removing skin reflectance background from subcutaneous structures in near-infrared images. Results are validated by experiments on human subjects.

  18. Multispectral image segmentation using parallel mean shift algorithm and CUDA technology

    Science.gov (United States)

    Zghidi, Hafedh; Walczak, Maksym; Świtoński, Adam

    2016-06-01

    We present a parallel mean shift algorithm running on CUDA and its possible application in segmentation of multispectral images. The aim of this paper is to present a method of analyzing highly noised multispectral images of various objects, so that important features are enhanced and easier to identify. The algorithm finds applications in analysis of multispectral images of eyes so that certain features visible only in specific wavelengths are made clearly visible despite high level of noise, for which processing time is very long.

  19. Assigning Main Orientation to an EOH Descriptor on Multispectral Images

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-07-01

    Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

  20. Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

    Science.gov (United States)

    Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

    2015-07-01

    This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

  1. Imaging Science Panel. Multispectral Imaging Science Working Group joint meeting with Information Science Panel: Introduction

    Science.gov (United States)

    1982-01-01

    The state-of-the-art of multispectral sensing is reviewed and recommendations for future research and development are proposed. specifically, two generic sensor concepts were discussed. One is the multispectral pushbroom sensor utilizing linear array technology which operates in six spectral bands including two in the SWIR region and incorporates capabilities for stereo and crosstrack pointing. The second concept is the imaging spectrometer (IS) which incorporates a dispersive element and area arrays to provide both spectral and spatial information simultaneously. Other key technology areas included very large scale integration and the computer aided design of these devices.

  2. 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.

  3. Active multispectral imaging system for photodiagnosis and personalized phototherapies

    Science.gov (United States)

    Ugarte, M. F.; Chávarri, L.; Briz, S.; Padrón, V. M.; García-Cuesta, E.

    2014-10-01

    The proposed system has been designed to identify dermatopathologies or to apply personalized phototherapy treatments. The system emits electromagnetic waves in different spectral bands in the range of visible and near infrared to irradiate the target (skin or any other object) to be spectrally characterized. Then, an imaging sensor measures the target response to the stimulus at each spectral band and, after processing, the system displays in real time two images. In one of them the value of each pixel corresponds to the more reflected wavenumber whereas in the other image the pixel value represents the energy absorbed at each band. The diagnosis capability of this system lies in its multispectral design, and the phototherapy treatments are adapted to the patient and his lesion by measuring his absorption capability. This "in situ" absorption measurement allows us to determine the more appropriate duration of the treatment according to the wavelength and recommended dose. The main advantages of this system are its low cost, it does not have moving parts or complex mechanisms, it works in real time, and it is easy to handle. For these reasons its widespread use in dermatologist consultation would facilitate the work of the dermatologist and would improve the efficiency of diagnosis and treatment. In fact the prototype has already been successfully applied to pathologies such as carcinomas, melanomas, keratosis, and nevi.

  4. Multispectral fluorescence imaging techniques for nondestructive food safety inspection

    Science.gov (United States)

    Kim, Moon S.; Lefcourt, Alan M.; Chen, Yud-Ren

    2004-03-01

    The use of spectral sensing has gained acceptance as a rapid means for nondestructive inspection of postharvest food produce. Current technologies generally use color or a single wavelength camera technology. The applicability and sensitivity of these techniques can be expanded through the use of multiple wavelengths. Reflectance in the Vis/NIR is the prevalent spectral technique. Fluorescence, compared to reflectance, is regarded as a more sensitive technique due to its dynamic responses to subtle changes in biological entities. Our laboratory has been exploring fluorescence as a potential means for detection of quality and wholesomeness of food products. Applications of fluorescence sensing require an understanding of the spectral characteristics emanating from constituents and potential contaminants. A number of factors affecting fluorescence emission characteristics are discussed. Because of relatively low fluorescence quantum yield from biological samples, a system with a powerful pulse light source such as a laser coupled with a gated detection device is used to harvest fluorescence, in the presence of ambient light. Several fluorescence sensor platforms developed in our laboratory, including hyperspectral imaging, and laser-induced fluorescence (LIF) and steady-state fluorescence imaging systems with multispectral capabilities are presented. We demonstrate the potential uses of recently developed fluorescence imaging platforms in food safety inspection of apples contaminated with animal feces.

  5. Phase classification by mean shift clustering of multispectral materials images.

    Science.gov (United States)

    Martins, Diego Schmaedech; Josa, Victor M Galván; Castellano, Gustavo; da Costa, José A T Borges

    2013-10-01

    A mean-shift clustering (MSC) algorithm is introduced as a valuable alternative to perform materials phase classification from multispectral images. As opposed to other multivariate statistical techniques, such as factor analysis or principal component analysis (PCA), clustering techniques directly assign a class label to each pixel, so that their outputs are phase segmented images, i.e., there is no need for an additional segmentation algorithm. On the other hand, as compared to other clustering procedures and classification methods, such as segmentation by thresholding of multiple spectral components, MSC has the advantages of not requiring previous knowledge of the number of data clusters and not assuming any shape for these clusters, i.e., neither the number nor the composition of the phases must be previously known. This makes MSC a particularly useful tool for exploratory research, assisting phase identification of unknown samples. Visualization and interpretation of the results are also simplified, since the information content of the output image does not depend on the particular choice of the content of the color channels.We applied MSC to the analysis of two sets of X-ray maps acquired in scanning electron microscopes equipped with energy-dispersive detection systems. Our results indicate that MSC is capable of detecting additional phases, not clearly identified through PCA or multiple thresholding, with a very low empirical reject rate.

  6. Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing

    Directory of Open Access Journals (Sweden)

    Arko Lucieer

    2012-05-01

    Full Text Available Unmanned aerial vehicles (UAVs represent a quickly evolving technology, broadening the availability of remote sensing tools to small-scale research groups across a variety of scientific fields. Development of UAV platforms requires broad technical skills covering platform development, data post-processing, and image analysis. UAV development is constrained by a need to balance technological accessibility, flexibility in application and quality in image data. In this study, the quality of UAV imagery acquired by a miniature 6-band multispectral imaging sensor was improved through the application of practical image-based sensor correction techniques. Three major components of sensor correction were focused upon: noise reduction, sensor-based modification of incoming radiance, and lens distortion. Sensor noise was reduced through the use of dark offset imagery. Sensor modifications through the effects of filter transmission rates, the relative monochromatic efficiency of the sensor and the effects of vignetting were removed through a combination of spatially/spectrally dependent correction factors. Lens distortion was reduced through the implementation of the Brown–Conrady model. Data post-processing serves dual roles in data quality improvement, and the identification of platform limitations and sensor idiosyncrasies. The proposed corrections improve the quality of the raw multispectral imagery, facilitating subsequent quantitative image analysis.

  7. 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.

  8. Color and textural quality of packaged wild rocket measured by multispectral imaging

    DEFF Research Database (Denmark)

    Løkke, Mette Marie; Seefeldt, Helene Fast; Skov, Thomas;

    2013-01-01

    Green color and texture are important attributes for the perception of freshness of wild rocket. Packaging of green leafy vegetables can postpone senescence and yellowing, but a drawback is the risk of anaerobic respiration leading to loss of tissue integrity and development of an olive-brown color....... The hypothesis underlying this paper is that color and textural quality of packaged wild rocket leaves can be predicted by multispectral imaging for faster evaluation of visual quality of leafy green vegetables in scientific experiments. Multispectral imaging was correlated to sensory evaluation of packaged wild...... rocket quality. CIELAB values derived from the multispectral images and from a spectrophotometer changed during storage, but the data were insufficient to describe variation in sensory perceived color and texture. CIELAB values from the multispectral images allowed for a more detailed determination...

  9. Interventional multispectral photoacoustic imaging with a clinical linear array ultrasound probe for guiding nerve blocks

    Science.gov (United States)

    Xia, Wenfeng; West, Simeon J.; Nikitichev, Daniil I.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

    2016-03-01

    Accurate identification of tissue structures such as nerves and blood vessels is critically important for interventional procedures such as nerve blocks. Ultrasound imaging is widely used as a guidance modality to visualize anatomical structures in real-time. However, identification of nerves and small blood vessels can be very challenging, and accidental intra-neural or intra-vascular injections can result in significant complications. Multi-spectral photoacoustic imaging can provide high sensitivity and specificity for discriminating hemoglobin- and lipid-rich tissues. However, conventional surface-illumination-based photoacoustic systems suffer from limited sensitivity at large depths. In this study, for the first time, an interventional multispectral photoacoustic imaging (IMPA) system was used to image nerves in a swine model in vivo. Pulsed excitation light with wavelengths in the ranges of 750 - 900 nm and 1150 - 1300 nm was delivered inside the body through an optical fiber positioned within the cannula of an injection needle. Ultrasound waves were received at the tissue surface using a clinical linear array imaging probe. Co-registered B-mode ultrasound images were acquired using the same imaging probe. Nerve identification was performed using a combination of B-mode ultrasound imaging and electrical stimulation. Using a linear model, spectral-unmixing of the photoacoustic data was performed to provide image contrast for oxygenated and de-oxygenated hemoglobin, water and lipids. Good correspondence between a known nerve location and a lipid-rich region in the photoacoustic images was observed. The results indicate that IMPA is a promising modality for guiding nerve blocks and other interventional procedures. Challenges involved with clinical translation are discussed.

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

    Science.gov (United States)

    Yi, Dingrong; Kong, Linghua; Sprigle, Stephen; Wang, Fengtao; Wang, Chao; Liu, Fuhan; Adibi, Ali; Tummala, Rao

    2010-02-01

    We are developing a handheld multispectral imaging device to non-invasively inspect stage I pressure ulcers in dark pigmented skins without the need of touching the patient's skin. This paper reports some preliminary test results of using a proof-of-concept prototype. It also talks about the innovation's impact to traditional multispectral imaging technologies and the fields that will potentially benefit from it.

  11. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    Science.gov (United States)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  12. Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

    Directory of Open Access Journals (Sweden)

    Harvey Neal R

    2007-07-01

    Full Text Available Abstract Background We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis. Results For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum gave a performance increase of 0.57%, compared to performance of the single best RGB band (red. Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains. Conclusion Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.

  13. Multispectral Imager With Improved Filter Wheel and Optics

    Science.gov (United States)

    Bremer, James C.

    2007-01-01

    Figure 1 schematically depicts an improved multispectral imaging system of the type that utilizes a filter wheel that contains multiple discrete narrow-band-pass filters and that is rotated at a constant high speed to acquire images in rapid succession in the corresponding spectral bands. The improvement, relative to prior systems of this type, consists of the measures taken to prevent the exposure of a focal-plane array (FPA) of photodetectors to light in more than one spectral band at any given time and to prevent exposure of the array to any light during readout. In prior systems, these measures have included, variously the use of mechanical shutters or the incorporation of wide opaque sectors (equivalent to mechanical shutters) into filter wheels. These measures introduce substantial dead times into each operating cycle intervals during which image information cannot be collected and thus incoming light is wasted. In contrast, the present improved design does not involve shutters or wide opaque sectors, and it reduces dead times substantially. The improved multispectral imaging system is preceded by an afocal telescope and includes a filter wheel positioned so that its rotation brings each filter, in its turn, into the exit pupil of the telescope. The filter wheel contains an even number of narrow-band-pass filters separated by narrow, spoke-like opaque sectors. The geometric width of each filter exceeds the cross-sectional width of the light beam coming out of the telescope. The light transmitted by the sequence of narrow-band filters is incident on a dichroic beam splitter that reflects in a broad shorter-wavelength spectral band that contains half of the narrow bands and transmits in a broad longer-wavelength spectral band that contains the other half of the narrow spectral bands. The filters are arranged on the wheel so that if the pass band of a given filter is in the reflection band of the dichroic beam splitter, then the pass band of the adjacent filter

  14. Multi-spectral image enhancement algorithm based on keeping original gray level

    Science.gov (United States)

    Wang, Tian; Xu, Linli; Yang, Weiping

    2016-11-01

    Characteristics of multi-spectral imaging system and the image enhancement algorithm are introduced.Because histogram equalization and some other image enhancement will change the original gray level,a new image enhancement algorithm is proposed to maintain the gray level.For this paper, we have chosen 6 narrow-bands multi-spectral images to compare,the experimental results show that the proposed method is better than those histogram equalization and other algorithm to multi-spectral images.It also insures that histogram information contained in original features is preserved and guarantees to make use of data class information.What's more,on the combination of subjective and objective sharpness evaluation,details of the images are enhanced and noise is weaken.

  15. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

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

  16. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

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

  17. 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.

  18. Multispectral mm-wave imaging: materials and images

    Science.gov (United States)

    Alexander, Naomi E.; Callejero Andrés, Carlos; Gonzalo, Ramón

    2008-04-01

    It is well known that millimeter-wave technology provides an important imaging capability through clothing and adverse weather conditions, among others. Alfa Imaging has undertaken a project to study the different applications of mm-wave imaging. An important part of this project is the measurement of material properties of a number of clothing and packaging samples in the frequency range from 40 to 306GHz. This task has been undertaken by the Antenna Group at the Public University of Navarra using an ABmm Network Analyser. The resulting data has been analysed and is presented in this paper along with example images and conclusions on the ideal operating frequency for the various applications studied.

  19. Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit.

    Science.gov (United States)

    Liu, Changhong; Liu, Wei; Chen, Wei; Yang, Jianbo; Zheng, Lei

    2015-04-15

    Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (RP(2))=0.938 and 0.965, residual predictive deviation (RPD)=4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading.

  20. a Two-Step Decision Fusion Strategy: Application to Hyperspectral and Multispectral Images for Urban Classification

    Science.gov (United States)

    Ouerghemmi, W.; Le Bris, A.; Chehata, N.; Mallet, C.

    2017-05-01

    Very high spatial resolution multispectral images and lower spatial resolution hyperspectral images are complementary sources for urban object classification. The first enables a fine delineation of objects, while the second can better discriminate classes and consider richer land cover semantics. This paper presents a decision fusion scheme taking advantage of both sources classification maps, to produce a better classification map. The proposed method aims at dealing with both semantic and spatial uncertainties and consists in two steps. First, class membership maps are merged at pixel level. Several fusion rules are considered and compared in this study. Secondly, classification is obtained from a global regularization of a graphical model, involving a fit-to-data term related to class membership measures and an image based contrast sensitive regularization term. Results are presented on three datasets. The classification accuracy is improved up to 5 %, with comparison to the best single source classification accuracy.

  1. Hybrid multispectral optoacoustic and ultrasound tomography for morphological and physiological brain imaging

    Science.gov (United States)

    Olefir, Ivan; Merčep, Elena; Burton, Neal C.; Ovsepian, Saak V.; Ntziachristos, Vasilis

    2016-08-01

    Expanding usage of small animal models in biomedical research necessitates development of technologies for structural, functional, or molecular imaging that can be readily integrated in the biological laboratory. Herein, we consider dual multispectral optoacoustic (OA) and ultrasound tomography based on curved ultrasound detector arrays and describe the performance achieved for hybrid morphological and physiological brain imaging of mice in vivo. We showcase coregistered hemodynamic parameters resolved by OA tomography under baseline conditions and during alterations of blood oxygen saturation. As an internal reference, we provide imaging of abdominal organs. We illustrate the performance advantages of hybrid curved detector ultrasound and OA tomography and discuss immediate and long-term implications of our findings in the context of animal and human studies.

  2. Software defined multi-spectral imaging for Arctic sensor networks

    Science.gov (United States)

    Siewert, Sam; Angoth, Vivek; Krishnamurthy, Ramnarayan; Mani, Karthikeyan; Mock, Kenrick; Singh, Surjith B.; Srivistava, Saurav; Wagner, Chris; Claus, Ryan; Vis, Matthew Demi

    2016-05-01

    Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop

  3. Superresolution image reconstruction using panchromatic and multispectral image fusion

    Science.gov (United States)

    Elbakary, M. I.; Alam, M. S.

    2008-08-01

    Hyperspectral imagery is used for a wide variety of applications, including target detection, tacking, agricultural monitoring and natural resources exploration. The main reason for using hyperspectral imagery is that these images reveal spectral information about the scene that is not available in a single band. Unfortunately, many factors such as sensor noise and atmospheric scattering degrade the spatial quality of these images. Recently, many algorithms are introduced in the literature to improve the resolution of hyperspectral images using co-registered high special-resolution imagery such as panchromatic imagery. In this paper, we propose a new algorithm to enhance the spatial resolution of low resolution hyperspectral bands using strongly correlated and co-registered high special-resolution panchromatic imagery. The proposed algorithm constructs the superresolution bands corresponding to the low resolution bands to enhance the resolution using a global correlation enhancement technique. The global enhancement is based on the least square regression and the histogram matching to improve the estimated interpolation of the spatial resolution. The introduced algorithm is considered as an improvement for Price’s algorithm which uses the global correlation only for the spatial resolution enhancement. Numerous studies are conducted to investigate the effect of the proposed algorithm for achieving the enhancement compared to the traditional algorithm for superresolution enhancement. Experiments results obtained using hyperspectral data derived from airborne imaging sensor are presented to verify the superiority of the proposed algorithm.

  4. From multispectral imaging of autofluorescence to chemical and sensory images of lipid oxidation in cod caviar paste.

    Science.gov (United States)

    Airado-Rodríguez, Diego; Høy, Martin; Skaret, Josefine; Wold, Jens Petter

    2014-05-01

    The potential of multispectral imaging of autofluorescence to map sensory flavour properties and fluorophore concentrations in cod caviar paste has been investigated. Cod caviar paste was used as a case product and it was stored over time, under different headspace gas composition and light exposure conditions, to obtain a relevant span in lipid oxidation and sensory properties. Samples were divided in two sets, calibration and test sets, with 16 and 7 samples, respectively. A third set of samples was prepared with induced gradients in lipid oxidation and sensory properties by light exposure of certain parts of the sample surface. Front-face fluorescence emission images were obtained for excitation wavelength 382 nm at 11 different channels ranging from 400 to 700 nm. The analysis of the obtained sets of images was divided in two parts: First, in an effort to compress and extract relevant information, multivariate curve resolution was applied on the calibration set and three spectral components and their relative concentrations in each sample were obtained. The obtained profiles were employed to estimate the concentrations of each component in the images of the heterogeneous samples, giving chemical images of the distribution of fluorescent oxidation products, protoporphyrin IX and photoprotoporphyrin. Second, regression models for sensory attributes related to lipid oxidation were constructed based on the spectra of homogeneous samples from the calibration set. These models were successfully validated with the test set. The models were then applied for pixel-wise estimation of sensory flavours in the heterogeneous images, giving rise to sensory images. As far as we know this is the first time that sensory images of odour and flavour are obtained based on multispectral imaging.

  5. 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).

  6. Nightfire method to track volcanic eruptions from multispectral satellite images

    Science.gov (United States)

    Trifonov, Grigory; Zhizhin, Mikhail; Melnikov, Dmitry

    2016-04-01

    This work presents the first results of an application of the Nightfire hotspot algorithm towards volcano activity detection. Nightfire algorithm have been developed to play along with a Suomi-NPP polar satellite launched in 2011, which has a new generation multispectral VIIRS thermal sensor on board, to detect gas flares related to the upstream and downstream production of oil and natural gas. Simultaneously using of nighttime data in SWIR, MWIR, and LWIR sensor bands the algorithm is able to estimate the hotspot temperature, size and radiant heat. Four years of non-filtered observations have been accumulated in a spatio-temporal detection database, which currently totals 125 GB in size. The first part of this work presents results of retrospective cross-match of the detection database with the publicly available observed eruptions databases. The second part discusses how an approximate 3D shape of a lava lake could be modeled based on the apparent source size and satellite zenith angle. The third part presents the results of fusion Landsat-8 and Himawari-8 satellites data with the VIIRS Nightfire for several active volcanoes.

  7. Remote multispectral imaging with PRISMS and XRF analysis of Tang tomb paintings

    Science.gov (United States)

    Lange, Rebecca; Zhang, Qunxi; Liang, Haida

    2011-06-01

    PRISMS (Portable Remote Imaging System for Multispectral Scanning) is a multispectral/hyperspectral imaging system designed for flexible in situ imaging of wall paintings at high resolution (tens of microns) over a large range of distances (less than a meter to over ten meters). This paper demonstrates a trial run of the VIS/NIR (400-880nm) component of the instrument for non-invasive imaging of wall paintings in situ. Wall painting panels from excavated Tang dynasty (618- 907AD) tombs near Xi'an were examined by PRISMS. Pigment identifications were carried out using the spectral reflectance obtained from multispectral imaging coupled with non-invasive elemental analysis using a portable XRF.

  8. Quantitative imaging of tumor vasculature using multispectral optoacoustic tomography (MSOT)

    Science.gov (United States)

    Tomaszewski, Michal R.; Quiros-Gonzalez, Isabel; Joseph, James; Bohndiek, Sarah E.

    2017-03-01

    The ability to evaluate tumor oxygenation in the clinic could indicate prognosis and enable treatment monitoring, since oxygen deficient cancer cells are often more resistant to chemotherapy and radiotherapy. MultiSpectral Optoacoustic Tomography (MSOT) is a hybrid technique combining the high contrast of optical imaging with spatial resolution and penetration depth similar to ultrasound. We hypothesized that MSOT could reveal both tumor vascular density and function based on modulation of blood oxygenation. We performed MSOT on nude mice (n=8) bearing subcutaneous xenograft PC3 tumors using an inVision 256 (iThera Medical). The mice were maintained under inhalation anesthesia during imaging and respired oxygen content was modified from 21% to 100% and back. After imaging, Hoechst 33348 was injected to indicate vascular perfusion and permeability. Tumors were then extracted for histopathological analysis and fluorescence microscopy. The acquired data was analyzed to extract a bulk measurement of blood oxygenation (SO2MSOT) from the whole tumor using different approaches. The tumors were also automatically segmented into 5 regions to investigate the effect of depth on SO2MSOT. Baseline SO2MSOT values at 21% and 100% oxygen breathing showed no relationship with ex vivo measures of vascular density or function, while the change in SO2MSOT showed a strong negative correlation to Hoechst intensity (r=- 0.92, p=0.0016). Tumor voxels responding to oxygen challenge were spatially heterogeneous. We observed a significant drop in SO2 MSOT value with tumor depth following a switch of respiratory gas from air to oxygen (0.323+/-0.017 vs. 0.11+/-0.05, p=0.009 between 0 and 1.5mm depth), but no such effect for air breathing (0.265+/-0.013 vs. 0.19+/-0.04, p=0.14 between 0 and 1.5mm depth). Our results indicate that in subcutaneous prostate tumors, baseline SO2MSOT levels do not correlate to tumor vascular density or function while the magnitude of the response to oxygen

  9. Detection of Melanoma Metastases in Resected Human Lymph Nodes by Noninvasive Multispectral Photoacoustic Imaging

    Directory of Open Access Journals (Sweden)

    Gerrit Cornelis Langhout

    2014-01-01

    Full Text Available Objective. Sentinel node biopsy in patients with cutaneous melanoma improves staging, provides prognostic information, and leads to an increased survival in node-positive patients. However, frozen section analysis of the sentinel node is not reliable and definitive histopathology evaluation requires days, preventing intraoperative decision-making and immediate therapy. Photoacoustic imaging can evaluate intact lymph nodes, but specificity can be hampered by other absorbers such as hemoglobin. Near infrared multispectral photoacoustic imaging is a new approach that has the potential to selectively detect melanin. The purpose of the present study is to examine the potential of multispectral photoacoustic imaging to identify melanoma metastasis in human lymph nodes. Methods. Three metastatic and nine benign lymph nodes from eight melanoma patients were scanned ex vivo using a Vevo LAZR© multispectral photoacoustic imager and were spectrally analyzed per pixel. The results were compared to histopathology as gold standard. Results. The nodal volume could be scanned within 20 minutes. An unmixing procedure was proposed to identify melanoma metastases with multispectral photoacoustic imaging. Ultrasound overlay enabled anatomical correlation. The penetration depth of the photoacoustic signal was up to 2 cm. Conclusion. Multispectral three-dimensional photoacoustic imaging allowed for selective identification of melanoma metastases in human lymph nodes.

  10. Detection of melanoma metastases in resected human lymph nodes by noninvasive multispectral photoacoustic imaging.

    Science.gov (United States)

    Langhout, Gerrit Cornelis; Grootendorst, Diederik Johannes; Nieweg, Omgo Edo; Wouters, Michel Wilhelmus Jacobus Maria; van der Hage, Jos Alexander; Jose, Jithin; van Boven, Hester; Steenbergen, Wiendelt; Manohar, Srirang; Ruers, Theodoor Jacques Marie

    2014-01-01

    Objective. Sentinel node biopsy in patients with cutaneous melanoma improves staging, provides prognostic information, and leads to an increased survival in node-positive patients. However, frozen section analysis of the sentinel node is not reliable and definitive histopathology evaluation requires days, preventing intraoperative decision-making and immediate therapy. Photoacoustic imaging can evaluate intact lymph nodes, but specificity can be hampered by other absorbers such as hemoglobin. Near infrared multispectral photoacoustic imaging is a new approach that has the potential to selectively detect melanin. The purpose of the present study is to examine the potential of multispectral photoacoustic imaging to identify melanoma metastasis in human lymph nodes. Methods. Three metastatic and nine benign lymph nodes from eight melanoma patients were scanned ex vivo using a Vevo LAZR(©) multispectral photoacoustic imager and were spectrally analyzed per pixel. The results were compared to histopathology as gold standard. Results. The nodal volume could be scanned within 20 minutes. An unmixing procedure was proposed to identify melanoma metastases with multispectral photoacoustic imaging. Ultrasound overlay enabled anatomical correlation. The penetration depth of the photoacoustic signal was up to 2 cm. Conclusion. Multispectral three-dimensional photoacoustic imaging allowed for selective identification of melanoma metastases in human lymph nodes.

  11. Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology.

    Science.gov (United States)

    Jolivot, Romuald; Benezeth, Yannick; Marzani, Franck

    2013-01-01

    In vivo quantitative assessment of skin lesions is an important step in the evaluation of skin condition. An objective measurement device can help as a valuable tool for skin analysis. We propose an explorative new multispectral camera specifically developed for dermatology/cosmetology applications. The multispectral imaging system provides images of skin reflectance at different wavebands covering visible and near-infrared domain. It is coupled with a neural network-based algorithm for the reconstruction of reflectance cube of cutaneous data. This cube contains only skin optical reflectance spectrum in each pixel of the bidimensional spatial information. The reflectance cube is analyzed by an algorithm based on a Kubelka-Munk model combined with evolutionary algorithm. The technique allows quantitative measure of cutaneous tissue and retrieves five skin parameter maps: melanin concentration, epidermis/dermis thickness, haemoglobin concentration, and the oxygenated hemoglobin. The results retrieved on healthy participants by the algorithm are in good accordance with the data from the literature. The usefulness of the developed technique was proved during two experiments: a clinical study based on vitiligo and melasma skin lesions and a skin oxygenation experiment (induced ischemia) with healthy participant where normal tissues are recorded at normal state and when temporary ischemia is induced.

  12. Unsupervised Change Detection for Multispectral Remote Sensing Images Using Random Walks

    Directory of Open Access Journals (Sweden)

    Qingjie Liu

    2017-05-01

    Full Text Available In this paper, the change detection of Multi-Spectral (MS remote sensing images is treated as an image segmentation issue. An unsupervised method integrating histogram-based thresholding and image segmentation techniques is proposed. In order to overcome the poor performance of thresholding techniques for strongly overlapped change/non-change signals, a Gaussian Mixture Model (GMM with three components, including non-change, non-labeling and change, is adopted to model the statistical characteristics of the different images between two multi-temporal MS images. The non-labeling represents the pixels that are difficult to be classified. A random walk based segmentation method is applied to solve this problem, in which the different images are modeled as graphs and the classification results of GMM are imported as the labeling seeds. The experimental results of three remote sensing image pairs acquired by different sensors suggest a superiority of the proposed approach comparing with the existing unsupervised change detection methods.

  13. Multispectral fluorescence imaging of human ovarian and fallopian tube tissue for early-stage cancer detection

    Science.gov (United States)

    Tate, Tyler H.; Baggett, Brenda; Rice, Photini F. S.; Koevary, Jennifer Watson; Orsinger, Gabriel V.; Nymeyer, Ariel C.; Welge, Weston A.; Saboda, Kathylynn; Roe, Denise J.; Hatch, Kenneth D.; Chambers, Setsuko K.; Utzinger, Urs; Barton, Jennifer Kehlet

    2016-05-01

    With early detection, 5-year survival rates for ovarian cancer exceed 90%, yet no effective early screening method exists. Emerging consensus suggests over 50% of the most lethal form of the disease originates in the fallopian tube. Twenty-eight women undergoing oophorectomy or debulking surgery provided informed consent for the use of surgical discard tissue samples for multispectral fluorescence imaging. Using multiple ultraviolet and visible excitation wavelengths and emissions bands, 12 fluorescence and 6 reflectance images of 47 ovarian and 31 fallopian tube tissue samples were recorded. After imaging, each sample was fixed, sectioned, and stained for pathological evaluation. Univariate logistic regression showed cancerous tissue samples had significantly lower intensity than noncancerous tissue for 17 image types. The predictive power of multiple image types was evaluated using multivariate logistic regression (MLR) and quadratic discriminant analysis (QDA). Two MLR models each using two image types had receiver operating characteristic curves with area under the curve exceeding 0.9. QDA determined 56 image type combinations with perfect resubstituting using as few as five image types. Adaption of the system for future in vivo fallopian tube and ovary endoscopic imaging is possible, which may enable sensitive detection of ovarian cancer with no exogenous contrast agents.

  14. HIGH-ACCURACY BAND TO BAND REGISTRATION METHOD FOR MULTI-SPECTRAL IMAGES OF HJ-1A/B

    Institute of Scientific and Technical Information of China (English)

    Lu Hao; Liu Tuanjie; Zhao Haiqing

    2012-01-01

    Band-to-band registration accuracy is an important parameter of multispectral data.A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B.Firstly,the main causes resulted in misregistration are analyzed,and a high-order polynomial model is proposed.Secondly,a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix.Then,experiments are carried out to build nonlinear registration models,and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels,while near infrared band with an accuracy of 0.2 pixels.

  15. Vector-lifting schemes based on sorting techniques for lossless compression of multispectral images

    Science.gov (United States)

    Benazza-Benyahia, Amel; Pesquet, Jean-Christophe

    2003-01-01

    In this paper, we introduce vector-lifting schemes which allow to generate very compact multiresolution representations, suitable for lossless and progressive coding of multispectral images. These new decomposition schemes exploit simultaneously the spatial and the spectral redundancies contained in multispectral images. When the spectral bands have different dynamic ranges, we improve dramatically the performances of the proposed schemes by a reversible histogram modification based on sorting permutations. Simulation tests carried out on real images allow to evaluate the performances of this new compression method. They indicate that the achieved compression ratios are higher than those obtained with currently used lossless coders.

  16. Rapid Assessment of Tablet Film Coating Quality by Multispectral UV Imaging.

    Science.gov (United States)

    Klukkert, Marten; Wu, Jian X; Rantanen, Jukka; Rehder, Soenke; Carstensen, Jens M; Rades, Thomas; Leopold, Claudia S

    2016-08-01

    Chemical imaging techniques are beneficial for control of tablet coating layer quality as they provide spectral and spatial information and allow characterization of various types of coating defects. The purpose of this study was to assess the applicability of multispectral UV imaging for assessment of the coating layer quality of tablets. UV images were used to detect, characterize, and localize coating layer defects such as chipped parts, inhomogeneities, and cracks, as well as to evaluate the coating surface texture. Acetylsalicylic acid tablets were prepared on a rotary tablet press and coated with a polyvinyl alcohol-polyethylene glycol graft copolymer using a pan coater. It was demonstrated that the coating intactness can be assessed accurately and fast by UV imaging. The different types of coating defects could be differentiated and localized based on multivariate image analysis and Soft Independent Modeling by Class Analogy applied to the UV images. Tablets with inhomogeneous texture of the coating could be identified and distinguished from those with a homogeneous surface texture. Consequently, UV imaging was shown to be well-suited for monitoring of the tablet coating layer quality. UV imaging is a promising technique for fast quality control of the tablet coating because of the high data acquisition speed and its nondestructive analytical nature.

  17. Semi-supervised segmentation of multispectral remote sensing image based on spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Wang, Ting; Jiao, Licheng; Yang, Chun

    2009-10-01

    In this paper, a new multi-spectral remote sensing image segmentation method based on multi-parameter semi-supervised spectral clustering (STS3C) is proposed. Two types of instance-level constraints: must-link and cannot-link are incorporated into spectral cluster to construct semi-supervised spectral clustering in which the self-tuning parameter is applied to avoid the selection of the scaling parameter. Further, when STS3C is applied to multi-spectral remote sensing image segmentation, the uniform sampling technique combined with nearest neighbor rule is used to reduce the computation complexity. Segmentation results show that STS3C outperforms the semi-supervised spectral clustering with fixed parameter and the well-known clustering methods including k-means and FCM in multi-spectral remote sensing image segmentation.

  18. Research on Gaussian distribution preprocess method of infrared multispectral image background clutter

    Institute of Scientific and Technical Information of China (English)

    张伟; 武春风; 邓盼; 范宁

    2004-01-01

    This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.

  19. Detection and classification of latent defects and diseases on raw French fries with multispectral imaging

    NARCIS (Netherlands)

    Noordam, J.C.; Broek, van den W.H.A.M.; Buydens, L.M.C.

    2005-01-01

    This paper describes an application of both multispectral imaging and red/green/blue (RGB) colour imaging for the discrimination between different defect and diseases on raw French fries. Four different potato cultivars generally used for French fries production are selected from which fries are cut

  20. Multispectral imaging reveals the tissue distribution of tetraspanins in human lymphoid organs

    NARCIS (Netherlands)

    Winde, C.M. de; Zuidscherwoude, M.C.; Vasaturo, A.; Schaaf, A. van der; Figdor, C.G.; Spriel, A.B. van

    2015-01-01

    Multispectral imaging is a novel microscopy technique that combines imaging with spectroscopy to obtain both quantitative expression data and tissue distribution of different cellular markers. Tetraspanins CD37 and CD53 are four-transmembrane proteins involved in cellular and humoral immune response

  1. Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images

    Directory of Open Access Journals (Sweden)

    Sebastian Candiago

    2015-04-01

    Full Text Available Unmanned Aerial Vehicles (UAV-based remote sensing offers great possibilities to acquire in a fast and easy way field data for precision agriculture applications. This field of study is rapidly increasing due to the benefits and advantages for farm resources management, particularly for studying crop health. This paper reports some experiences related to the analysis of cultivations (vineyards and tomatoes with Tetracam multispectral data. The Tetracam camera was mounted on a multi-rotor hexacopter. The multispectral data were processed with a photogrammetric pipeline to create triband orthoimages of the surveyed sites. Those orthoimages were employed to extract some Vegetation Indices (VI such as the Normalized Difference Vegetation Index (NDVI, the Green Normalized Difference Vegetation Index (GNDVI, and the Soil Adjusted Vegetation Index (SAVI, examining the vegetation vigor for each crop. The paper demonstrates the great potential of high-resolution UAV data and photogrammetric techniques applied in the agriculture framework to collect multispectral images and evaluate different VI, suggesting that these instruments represent a fast, reliable, and cost-effective resource in crop assessment for precision farming applications.

  2. Joint Multi-Image Saliency Analysis for Region of Interest Detection in Optical Multispectral Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Jie Chen

    2016-05-01

    Full Text Available The automatic detection of regions of interest (ROI is useful for remote sensing image analysis, such as land cover classification, object recognition, image compression, and various computer vision related applications. Recently, approaches based on visual saliency have been utilized for ROI detection. However, most existing methods focus on detecting ROIs from a single image, which generally cannot precisely extract ROIs against a complicated background or exclude images with no ROIs. In this paper, we propose a joint multi-image saliency (JMS algorithm to simultaneously extract the common ROIs in a set of optical multispectral remote sensing images with the additional ability to identify images that do not contain the common ROIs. First, bisecting K-means clustering on the entire image set allows us to extract the global correspondence among multiple images in RGB and CIELab color spaces. Second, clusterwise saliency computation aggregating global color and shape contrast efficiently assigns common ROIs with high saliency, while effectively depressing interfering background that is salient only within its own image. Finally, binary ROI masks are generated by thresholding saliency maps. In addition, we construct an edge-preserving JMS model through edge-preserving mask optimization strategy, so as to facilitate the generation of a uniformly highlighted ROI mask with sharp borders. Experimental results demonstrate the advantages of our model in detection accuracy consistency and runtime efficiency.

  3. Recent development of feature extraction and classification multispectral/hyperspectral images: a systematic literature review

    Science.gov (United States)

    Setiyoko, A.; Dharma, I. G. W. S.; Haryanto, T.

    2017-01-01

    Multispectral data and hyperspectral data acquired from satellite sensor have the ability in detecting various objects on the earth ranging from low scale to high scale modeling. These data are increasingly being used to produce geospatial information for rapid analysis by running feature extraction or classification process. Applying the most suited model for this data mining is still challenging because there are issues regarding accuracy and computational cost. This research aim is to develop a better understanding regarding object feature extraction and classification applied for satellite image by systematically reviewing related recent research projects. A method used in this research is based on PRISMA statement. After deriving important points from trusted sources, pixel based and texture-based feature extraction techniques are promising technique to be analyzed more in recent development of feature extraction and classification.

  4. Retrieval of Temperature and Species Distributions from Multispectral Image Data of Surface Flame Spread in Microgravity

    Science.gov (United States)

    Annen, K. D.; Conant, John A.; Weiland, Karen J.

    2001-01-01

    Weight, size, and power constraints severely limit the ability of researchers to fully characterize temperature and species distributions in microgravity combustion experiments. A powerful diagnostic technique, infrared imaging spectrometry, has the potential to address the need for temperature and species distribution measurements in microgravity experiments. An infrared spectrum imaged along a line-of-sight contains information on the temperature and species distribution in the imaged path. With multiple lines-of-sight and approximate knowledge of the geometry of the combustion flowfield, a three-dimensional distribution of temperature and species can be obtained from one hyperspectral image of a flame. While infrared imaging spectrometers exist for collecting hyperspectral imagery, the remaining challenge is retrieving the temperature and species information from this data. An initial version of an infrared analysis software package, called CAMEO (Combustion Analysis Model et Optimizer), has been developed for retrieving temperature and species distributions from hyperspectral imaging data of combustion flowfields. CAMEO has been applied to the analysis of multispectral imaging data of flame spread over a PMMA surface in microgravity that was acquired in the DARTFire program. In the next section of this paper, a description of CAMEO and its operation is presented, followed by the results of the analysis of microgravity flame spread data.

  5. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    Science.gov (United States)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  6. Diffuse reflectance and fluorescence multispectral imaging system for assessment of skin

    Science.gov (United States)

    Saknite, Inga; Jakovels, Dainis; Spigulis, Janis

    2014-05-01

    The diffuse reflectance multispectral imaging technique has been used for distant mapping of in vivo skin chromophores (hemoglobin and melanin). The fluorescence multispectral imaging is not so common for skin applications due to complicity of data acquisition and processing, but could provide additional information about skin fluorophores. Both techniques are compatible, and could be combined into a multimodal solution. The multispectral imaging system Nuance based on liquid crystal tunable filters was adapted for diffuse reflectance and fluorescence spectral imaging of in vivo skin. Uniform illumination was achieved by LED ring light. Combination of four LEDs (warm white, 770 nm, 830 nm and 890 nm) was used to support diffuse reflectance mode in spectral range 450-950 nm. 405 nm LEDs were used for excitation of skin autofluorescence. Multispectral imaging system was adapted for spectral working range of 450-950 nm with scanning step of 10 nm and spectral resolution of 15 nm. An average field of view was 50x35 mm in size with spatial resolution 0,05 mm (the pixel size). Due to spectrally different illumination intensity and system sensitivity, various exposure times (from 7…500 ms) were used for each image acquisition. The proposed approach was tested for different skin lesions: benign nevus, hemangioma, basalioma and halo nevus. Spectral image cubes of different skin lesions were acquired and analyzed to test its diagnostic potential.

  7. MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM

    Institute of Scientific and Technical Information of China (English)

    Zhang Yifan; He Mingyi

    2007-01-01

    Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspectral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR) method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

  8. Pseudo colour visualization of fused multispectral laser scattering images for optical diagnosis of rheumatoid arthritis

    Science.gov (United States)

    Zabarylo, U.; Minet, O.

    2010-01-01

    Investigations on the application of optical procedures for the diagnosis of rheumatism using scattered light images are only at the beginning both in terms of new image-processing methods and subsequent clinical application. For semi-automatic diagnosis using laser light, the multispectral scattered light images are registered and overlapped to pseudo-coloured images, which depict diagnostically essential contents by visually highlighting pathological changes.

  9. An image compression method for space multispectral time delay and integration charge coupled device camera

    Institute of Scientific and Technical Information of China (English)

    Li Jin; Jin Long-Xu; Zhang Ran-Feng

    2013-01-01

    Multispectral time delay and integration charge coupled device (TDICCD) image compression requires a lowcomplexity encoder because it is usually completed on board where the energy and memory are limited.The Consultative Committee for Space Data Systems (CCSDS) has proposed an image data compression (CCSDS-IDC) algorithm which is so far most widely implemented in hardware.However,it cannot reduce spectral redundancy in multispectral images.In this paper,we propose a low-complexity improved CCSDS-IDC (ICCSDS-IDC)-based distributed source coding (DSC) scheme for multispectral TDICCD image consisting of a few bands.Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient.The output of bit plane extractor will be encoded by a first order entropy coder.Low-density parity-check-based Slepian-Wolf (SW) coder is adopted to implement the DSC strategy.Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.

  10. Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation

    Science.gov (United States)

    Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

    2017-01-01

    Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

  11. Spot-5 multispectral image for 60-75 days of rice mapping

    Science.gov (United States)

    Amiruddin Ramli, Mohd; Shariff, Abdul Rashid Mohamed; Khairunniza Bejo, Siti

    2014-06-01

    The objective of this study is to investigate the potential application of Spot-5 multispectral satellite data in monitoring rice cultivation areas in IADA (Integrated Agriculture Development Area) located at Kerian District, Perak Malaysia. Information of the rice cultivation areas is a global economic and environmental significance. Multi-spectral images acquired at high spatial resolution are an important tool, especially in agricultural applications. This paper addresses the relationship between normalize difference vegetation index (NDVI) and ancillary data acquired from Farmers Organization Authority (PPK) for 217 farmer's field in IADA Kerian. The results indicated that NDVI range 0.62 - 0.75 has a strong positive relationship with the ground survey area estimation with (r = 0.85; p Malaysia. The results appear promising and rice mapping operations using SPOT-5 multispectral image data can be foreseen.

  12. Multispectral imaging of organ viability during uterine transplantation surgery in rabbits and sheep

    Science.gov (United States)

    Clancy, Neil T.; Saso, Srdjan; Stoyanov, Danail; Sauvage, Vincent; Corless, David J.; Boyd, Michael; Noakes, David E.; Thum, Meen-Yau; Ghaem-Maghami, Sadaf; Smith, James Richard; Elson, Daniel S.

    2016-10-01

    Uterine transplantation surgery (UTx) has been proposed as a treatment for permanent absolute uterine factor infertility (AUFI) in the case of the congenital absence or surgical removal of the uterus. Successful surgical attachment of the organ and its associated vasculature is essential for the organ's reperfusion and long-term viability. Spectral imaging techniques have demonstrated the potential for the measurement of hemodynamics in medical applications. These involve the measurement of reflectance spectra by acquiring images of the tissue in different wavebands. Measures of tissue constituents at each pixel can then be extracted from these spectra through modeling of the light-tissue interaction. A multispectral imaging (MSI) laparoscope was used in sheep and rabbit UTx models to study short- and long-term changes in oxygen saturation following surgery. The whole organ was imaged in the donor and recipient animals in parallel with point measurements from a pulse oximeter. Imaging results confirmed the re-establishment of adequate perfusion in the transplanted organ after surgery. Cornual oxygenation trends measured with MSI are consistent with pulse oximeter readings, showing decreased StO2 immediately after anastomosis of the blood vessels. Long-term results show recovery of StO2 to preoperative levels.

  13. Multispectral UV imaging for surface analysis of MUPS tablets with special focus on the pellet distribution

    DEFF Research Database (Denmark)

    Novikova, Anna; Carstensen, Jens Michael; Rades, Thomas

    2016-01-01

    In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well as p...... image analysis is a promising approach for the automatic quality control of MUPS tablets during the manufacturing process.......In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well...... on the tablet surface allowed an estimation of the true drug content in the respective MUPS tablet. In addition, the pellet distribution in the MUPS formulations could be estimated by UV image analysis of the tablet surface. In conclusion, this study revealed that UV imaging in combination with multivariate...

  14. Inflight Radiometric Calibration of New Horizons' Multispectral Visible Imaging Camera (MVIC)

    CERN Document Server

    Howett, C J A; Olkin, C B; Reuter, D C; Ennico, K; Grundy, W M; Graps, A L; Harrison, K P; Throop, H B; Buie, M W; Lovering, J R; Porter, S B; Weaver, H A; Young, L A; Stern, S A; Beyer, R A; Binzell, R P; Buratti, B J; Cheng, A F; Cook, J C; Cruikshank, D P; Ore, C M Dalle; Earle, A M; Jennings, D E; Linscott, I R; Lunsford, A W; Parker, J Wm; Phillippe, S; Protopapa, S; Quirico, E; Schenk, P M; Schmitt, B; Singer, K N; Spencer, J R; Stansberry, J A; Tsang, C C C; Weigle, G E; Verbiscer, A J

    2016-01-01

    We discuss two semi-independent calibration techniques used to determine the in-flight radiometric calibration for the New Horizons' Multi-spectral Visible Imaging Camera (MVIC). The first calibration technique compares the observed stellar flux to modeled values. The difference between the two provides a calibration factor that allows the observed flux to be adjusted to the expected levels for all observations, for each detector. The second calibration technique is a channel-wise relative radiometric calibration for MVIC's blue, near-infrared and methane color channels using observations of Charon and scaling from the red channel stellar calibration. Both calibration techniques produce very similar results (better than 7% agreement), providing strong validation for the techniques used. Since the stellar calibration can be performed without a color target in the field of view and covers all of MVIC's detectors, this calibration was used to provide the radiometric keywords delivered by the New Horizons project...

  15. Analytical models and system topologies for remote multispectral data acquisition and classification

    Science.gov (United States)

    Huck, F. O.; Park, S. K.; Burcher, E. E.; Kelly, W. L., IV

    1978-01-01

    Simple analytical models are presented of the radiometric and statistical processes that are involved in multispectral data acquisition and classification. Also presented are basic system topologies which combine remote sensing with data classification. These models and topologies offer a preliminary but systematic step towards the use of computer simulations to analyze remote multispectral data acquisition and classification systems.

  16. Multispectral image compression based on DSC combined with CCSDS-IDC.

    Science.gov (United States)

    Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

    2014-01-01

    Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

  17. Multispectral photoacoustic imaging of tumours in mice injected with an enzyme-activatable photoacoustic probe

    Science.gov (United States)

    Hirasawa, Takeshi; Iwatate, Ryu J.; Kamiya, Mako; Okawa, Shinpei; Urano, Yasuteru; Ishihara, Miya

    2017-01-01

    Photoacoustic (PA) imaging offers depth-resolved images of optical absorbers with the spatial resolution of ultrasound imaging. To enhance tumour contrast, tumour-specific probes are used as contrast agents. We synthesised a colourless PA probe that is activated in the presence of γ-glutamyltranspeptidase, a cancer-associated enzyme, to show its original colour and fluorescence. We have acquired high specificity fluorescence images of small tumours, using a fluorescent probe based on similar enzymatic reactions. Here, we developed a PA imaging technique to detect the PA probe. In PA imaging, depending on the concentration and excitation wavelength of the probe, the intensities of the probe signals may be lower than those of the background signals produced by intrinsic optical absorbers such as haemoglobin. For probe imaging in the presence of strong background signals, multispectral photoacoustic (MS-PA) imaging was evaluated. In MS-PA imaging, the spectral fitting method, which distinguishes the probe signals from background signals using reference spectra, has been widely used. To compensate for the decrease of fluence due to optical attenuation in biological tissue, we used a simplified compensation method that calculates fluence inside biological tissues by the Monte-Carlo model using published data on optical properties of biological tissues. The validity of the method was confirmed using tissue-mimicking phantoms. Finally, MS-PA imaging of a mouse subcutaneous tumour injected with the activatable probe was demonstrated. In conclusion, our MS-PA imaging technique afforded successful detection of the activated probe in the tumour, and time-increase of PA signals were successfully observed.

  18. Multispectral integral imaging acquisition and processing using a monochrome camera and a liquid crystal tunable filter.

    Science.gov (United States)

    Latorre-Carmona, Pedro; Sánchez-Ortiga, Emilio; Xiao, Xiao; Pla, Filiberto; Martínez-Corral, Manuel; Navarro, Héctor; Saavedra, Genaro; Javidi, Bahram

    2012-11-01

    This paper presents an acquisition system and a procedure to capture 3D scenes in different spectral bands. The acquisition system is formed by a monochrome camera, and a Liquid Crystal Tunable Filter (LCTF) that allows to acquire images at different spectral bands in the [480, 680]nm wavelength interval. The Synthetic Aperture Integral Imaging acquisition technique is used to obtain the elemental images for each wavelength. These elemental images are used to computationally obtain the reconstruction planes of the 3D scene at different depth planes. The 3D profile of the acquired scene is also obtained using a minimization of the variance of the contribution of the elemental images at each image pixel. Experimental results show the viability to recover the 3D multispectral information of the scene. Integration of 3D and multispectral information could have important benefits in different areas, including skin cancer detection, remote sensing and pattern recognition, among others.

  19. Multispectral endoscopy and microscopy imaging system using a spectrally programmable light engine

    Science.gov (United States)

    MacKinnon, N.; Stange, Ulrich; Lane, Pierre M.; MacAulay, Calum E.

    2005-03-01

    We report a spectrally and temporally programmable light engine based on a spatial light modulator that can dynamically create any narrow or broadband spectral profile for hyperspectral, fluorescence, or principal component imaging. Most hyperspectral or multispectral imaging systems use wavelength selection devices such as acousto-optic tunable filters (AOTFs), tunable grating or prism-based monochromators, or filter wheels. While these devices can select wavelengths they cannot create arbitrary spectral profiles. This simple and economical system can be controlled at high speed (up to 5000 illumination profiles per second). Digitally controlled illumination is bit additive with image data providing high dynamic range imaging with monochrome or color imaging devices. This is especially advantageous for endoscopes employing small well CCD or CMOS sensors since the dynamic range now can extend beyond the limits of the sensor itself. In this report we show multispectral images of in vivo tissue and in vitro tissue samples using endoscopes, surgical microscopes and conventional microscopes.

  20. A Multispectral Photon-Counting Double Random Phase Encoding Scheme for Image Authentication

    Directory of Open Access Journals (Sweden)

    Faliu Yi

    2014-05-01

    Full Text Available In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI and double random phase encoding (DRPE schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

  1. Analysis of Multispectral Galileo SSI Images of the Conamara Chaos Region, Europa

    Science.gov (United States)

    Spaun, N. A.; Phillips, C. B.

    2003-01-01

    Multispectral imaging of Europa s surface by Galileo s Solid State Imaging (SSI) camera has revealed two major surface color units, which appear as white and red-brown regions in enhanced color images of the surface (see figure). The Galileo Near- Infrared Mapping Spectrometer (NIMS) experiment suggests that the whitish material is icy, almost pure water ice, while the spectral signatures of the reddish regions are dominated by a non-ice material. Two endmember models have been proposed for the composition of the non-ice material: magnesium sulfate hydrates [1] and sulfuric acid and its byproducts [2]. There is also debate concerning whether the origin of this non-ice material is exogenic or endogenic [3].Goals: The key questions this work addresses are: 1) Is the non-ice material exogenic or endogenic in origin? 2) Once emplaced, is this non-ice material primarily modified by exogenic or endogenic processes? 3) Is the non-ice material within ridges, bands, chaos, and lenticulae the same non-ice material across all such geological features? 4) Does the distribution of the non-ice material provide any evidence for or against any of the various models for feature formation? 5) To what extent do the effects of scattered light in SSI images change the spectral signatures of geological features?

  2. An airborne multispectral imaging system based on two consumer-grade cameras for agricultural remote sensing

    Science.gov (United States)

    This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS) sensor with 5616 × 3744 pixels. One came...

  3. The method of multispectral image processing of phytoplankton processing for environmental control of water pollution

    Science.gov (United States)

    Petruk, Vasil; Kvaternyuk, Sergii; Yasynska, Victoria; Kozachuk, Anastasia; Kotyra, Andrzej; Romaniuk, Ryszard S.; Askarova, Nursanat

    2015-12-01

    The paper presents improvement of the method of environmental monitoring of water bodies based on bioindication by phytoplankton, which identify phytoplankton particles carried out on the basis of comparison array multispectral images using Bayesian classifier of solving function based on Mahalanobis distance. It allows to evaluate objectively complex anthropogenic and technological impacts on aquatic ecosystems.

  4. 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.

  5. Multispectral remote sensing from unmanned aircraft: image processing workflows and applications for rangeland environments

    Science.gov (United States)

    Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Most image acquisitions from UAS have been in the visible bands, while multispectral remote sensing ap...

  6. A virtual seed file: the use of multispectral image analysis in the management of genebank seed accessions

    DEFF Research Database (Denmark)

    Adsetts Edberg Hansen, Michael; R. Hay, Fiona; Carstensen, Jens Michael

    2015-01-01

    We present a method for multispectral seed phenotyping as a fast and robust tool for managing genebank accessions. A multispectral vision system was used to take images of the seeds of 20 diverse varieties of rice (approximately 30 seeds for each variety). This was followed by extraction of featu...

  7. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    OpenAIRE

    Heleno, Sandra; Matias, Magda; Pina, Pedro , (O.F.M.); sousa, António Jorge

    2016-01-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area,...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    sand types were examined with 20-60 images for each type. To reduce the amount of data, features were extracted from the multi-spectral images; the features were summary statistics on single bands and pairs of bands as well as morphological summaries. The number of features (2,016) is high in relation...... reduction (forward selection and principal components) combined with ordinary least squares and one sophisticated chemometrics algorithm (genetic algorithm-partial least squares) are compared to the recently proposed least angle regression-elastic net (LARS-EN) model selection method....

  9. Improved image classification with neural networks by fusing multispectral signatures with topological data

    Science.gov (United States)

    Harston, Craig; Schumacher, Chris

    1992-01-01

    Automated schemes are needed to classify multispectral remotely sensed data. Human intelligence is often required to correctly interpret images from satellites and aircraft. Humans suceed because they use various types of cues about a scene to accurately define the contents of the image. Consequently, it follows that computer techniques that integrate and use different types of information would perform better than single source approaches. This research illustrated that multispectral signatures and topographical information could be used in concert. Significantly, this dual source tactic classified a remotely sensed image better than the multispectral classification alone. These classifications were accomplished by fusing spectral signatures with topographical information using neural network technology. A neural network was trained to classify Landsat mulitspectral signatures. A file of georeferenced ground truth classifications were used as the training criterion. The network was trained to classify urban, agriculture, range, and forest with an accuracy of 65.7 percent. Another neural network was programmed and trained to fuse these multispectral signature results with a file of georeferenced altitude data. This topological file contained 10 levels of elevations. When this nonspectral elevation information was fused with the spectral signatures, the classifications were improved to 73.7 and 75.7 percent.

  10. Transferring results from NIR-hyperspectral to NIR-multispectral imaging systems: A filter-based simulation applied to the classification of Arabica and Robusta green coffee.

    Science.gov (United States)

    Calvini, Rosalba; Amigo, Jose Manuel; Ulrici, Alessandro

    2017-05-15

    Due to the differences in terms of both price and quality, the availability of effective instrumentation to discriminate between Arabica and Robusta coffee is extremely important. To this aim, the use of multispectral imaging systems could provide reliable and accurate real-time monitoring at relatively low costs. However, in practice the implementation of multispectral imaging systems is not straightforward: the present work investigates this issue, starting from the outcome of variable selection performed using a hyperspectral system. Multispectral data were simulated considering four commercially available filters matching the selected spectral regions, and used to calculate multivariate classification models with Partial Least Squares-Discriminant Analysis (PLS-DA) and sparse PLS-DA. Proper strategies for the definition of the training set and the selection of the most effective combinations of spectral channels led to satisfactory classification performances (100% classification efficiency in prediction of the test set). Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Interventional multi-spectral photoacoustic imaging in laparoscopic surgery

    Science.gov (United States)

    Hill, Emma R.; Xia, Wenfeng; Nikitichev, Daniil I.; Gurusamy, Kurinchi; Beard, Paul C.; Hawkes, David J.; Davidson, Brian R.; Desjardins, Adrien E.

    2016-03-01

    Laparoscopic procedures can be an attractive treatment option for liver resection, with a shortened hospital stay and reduced morbidity compared to open surgery. One of the central challenges of this technique is visualisation of concealed structures within the liver, particularly the vasculature and tumourous tissue. As photoacoustic (PA) imaging can provide contrast for haemoglobin in real time, it may be well suited to guiding laparoscopic procedures in order to avoid inadvertent trauma to vascular structures. In this study, a clinical laparoscopic ultrasound probe was used to receive ultrasound for PA imaging and to obtain co-registered B-mode ultrasound (US) images. Pulsed excitation light was delivered to the tissue via a fibre bundle in dark-field mode. Monte Carlo simulations were performed to optimise the light delivery geometry for imaging targets at depths of 1 cm, 2 cm and 3 cm, and 3D-printed mounts were used to position the fibre bundle relative to the transducer according to the simulation results. The performance of the photoacoustic laparoscope system was evaluated with phantoms and tissue models. The clinical potential of hybrid PA/US imaging to improve the guidance of laparoscopic surgery is discussed.

  12. Multi-spectral image fusion method based on two channels non-separable wavelets

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; PENG JiaXiong

    2008-01-01

    A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1, -1] and its application in the fusion of multi-spectral image are presented. Many 4x4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.

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

    OpenAIRE

    Marc Wieland; Massimiliano Pittore

    2014-01-01

    In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS) and very high resolution (WorldView-2, Quickbird, Ikonos) multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognitio...

  14. Non-Contact Optical Fluorescence Tomography for Small Animal Imaging: System Development and Multispectral Applications

    OpenAIRE

    2010-01-01

    Optical Fluorescence Tomography (OFT) of live small animals can yield optimum 3-dimensional imaging performance when large amounts of tomographic boundary information are used for reconstruction. Commonly, multiple source-detector projection measurements distributed over the tissue surface of the imaging object are used to generate raw data for tomography. Recent advances in multispectral optical tomography, however, provide an attractive alternative method to harness tomographic boundary dat...

  15. Image smoothing of multispectral imagery based on the HNN and geo-statistics

    Institute of Scientific and Technical Information of China (English)

    Nguyen Quang Minh

    2011-01-01

    A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network (HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral (MS) image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.

  16. 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.

  17. Mapping lipid and collagen by multispectral photoacoustic imaging of chemical bond vibration

    Science.gov (United States)

    Wang, Pu; Wang, Ping; Wang, Han-Wei; Cheng, Ji-Xin

    2012-09-01

    Photoacoustic microscopy using vibrational overtone absorption as a contrast mechanism allows bond-selective imaging of deep tissues. Due to the spectral similarity of molecules in the region of overtone vibration, it is difficult to interrogate chemical components using photoacoustic signal at single excitation wavelength. Here we demonstrate that lipids and collagen, two critical markers for many kinds of diseases, can be distinguished by multispectral photoacoustic imaging of the first overtone of C-H bond. A phantom consisting of rat-tail tendon and fat was constructed to demonstrate this technique. Wavelengths between 1650 and 1850 nm were scanned to excite both the first overtone and combination bands of C-H bonds. B-scan multispectral photoacoustic images, in which each pixel contains a spectrum, were analyzed by a multivariate curve resolution-alternating least squares algorithm to recover the spatial distribution of collagen and lipids in the phantom.

  18. Validation of a fiber-based confocal microscope for interventional image-guided procedures: correlation with multispectral optical imaging

    Science.gov (United States)

    Herzka, Daniel; Quijano, Jade; Xie, Jianwu; Krueger, Sascha; Weiss, Steffen; Abrat, Benjamin; Osdoit, Anne; Cavé, Charlotte; Burnett, Christopher; Danthi, S. Narasimhan; Li, King

    2006-03-01

    The concept of the biopsy is ubiquitous in current medical diagnosis of cancer and other diseases. The standard biopsy consists of removing a sample of tissue for evaluation and diagnosis, primarily to ascertain the presence of cancer cells by (histo)pathological analyses. However, the advent of new optical imaging modalities and targeted or "smart" agents, that have affinity for a select target, suggests the possibility of performing in vivo tissue characterization without the need for sample removal or the wait for histopathologic processing. Here we present work testing and validating a fiber-based confocal fluorescence microscopic imaging system intended for combination with a larger scale imaging modality (i.e. MRI or CT) to be used in image-guided in vivo tissue characterization. Fiber-based confocal fluorescence microscopic imaging experiments were performed (Cellvizio, Mauna Kea Technologies, Paris, France) in vivo in two mouse models including: 1) EGFP-expressing mouse melanoma model and 2) M21 mouse melanoma model. Both models are known to express integrin α νβ 3, a cell-surface receptor protein. We also performed an experiment in ex vivo chicken muscle tissue labelled with a fluorescein isothiocyanate-lectin targeted compound. In the mouse models, contrast agents that targeted the integrin were injected and the contrast agent localization in tumor was verified by a whole-body multispectral imager. The fiber-based tool was sensitive enough to detect and image the tissue of interest in all different experiments, and was found appropriate for use in interventional catheter-based procedures.

  19. Panoramic, Macro and Micro Multispectral Imaging: An Affordable System for Mapping Pigments on Artworks

    Directory of Open Access Journals (Sweden)

    Antonino Cosentino

    2015-07-01

    Full Text Available Multispectral imaging systems are used in art examinations to map and identify pigments, binders and areas of retouching. A monochromatic camera is combined with an appropriate wavelength selection system and acquires a variable number of spectral images of a scene. These images are then stacked into a reflectance imaging cube to reconstruct reflectance spectra from each of the images’ pixels. This paper presents an affordable multispectral imaging system composed of a monochromatic CCD camera and a set of only 12 interference filters for mapping pigments on works of art and for the tentative identification of such pigments. This work demonstrates the versatility of this set-up, a versatility enabling it to be applied to different tasks, involving examination and documentation of objects of varying size. Use of this multispectral camera for both panoramic and macro photography is discussed, together with the possibilities facilitated from the coupling of the system to a stereomicroscope and a compound microscope. This system is of particular interest for the cultural heritage sector because of its hardware simplicity and acquisition speed, as well as its lightness and small dimensions.

  20. A System to Detect Residential Area in Multispectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Seyfallah Bouraoui

    2011-11-01

    Full Text Available In this paper, we propose a new solution to extract complex structures from High-Resolution (HR remote-sensing images. We propose to represent shapes and there relations by using region adjacency graphs. They are generated automatically from the segmented images. Thus, the nodes of the graph represent shape like houses, streets or trees, while arcs describe the adjacency relation between them. In order to be invariant to transformations such as rotation and scaling, the extraction of objects of interest is done by combining two techniques: one based on roof color to detect the bounding boxes of houses, and one based on mathematical morphology notions to detect streets. To recognize residential areas, a model described by a regular language is built. The detection is achieved by looking for a path in the region adjacency graph, which can be recognized as a word belonging to the description language. Our algorithm was tested with success on images from the French satellite SPOT 5 representing the urban area of Strasbourg (France at different spatial resolution.

  1. Application of multispectral animal living imaging technology in evaluating osteoarthritis model%多光谱小动物活体成像技术在骨性关节炎模型评价中的应用

    Institute of Scientific and Technical Information of China (English)

    许世兵; 单乐天; 郭燕威; 肖鲁伟; 童培建

    2014-01-01

    Objective:To observe application value of multispectral animal living imaging technology in rats model of os-teoarthritis. Methods:Fifteen male SD rats weighed (180 ±20) g (3 months old) were received intra articular injection of iodoacetic acid for establishing osteoarthritis. Articular cavity of left knee of rats were injected into 50 μl iodoacetic acid. The same volume of sterile saline was injected into right knee articular cavity as control. X ray living imaging and bone mineral density were observed at 2 and 4 weeks after establishment of model. After 4 weeks ,rats were sacrificed and their bilateral joints were collected and determined histologically based on Collins classification and Kellgren-Lawrence classification. Re-sults:Osteoarthritis model was successfully established,compared with control group, model group showed typical manifesta-tion of osteoarthritis,including irregular cartilage surface,osteophyte formation,joint deformity and cartilage defect,and com-bined with significant decrease of bone density (P<0.01),while the decrease was not obvious in proximal tibia (P<0.05). After 2 weeks,knee joints in model group was classified as Collins grade 1 and Kellgren-Lawrence grade 2 ,then classified as Collins grade 4 and Kellgren-Lawrence grade 3 after 4 weeks ,control group showed smooth articular surface ,normal joint space and intact cartilage surface ,knee joints was classified as Collins and Kellgren-Lawrence grade 0 ,and bone density of distal femur and proximal tibia were normal. Conclusion:Multispectral animal living imaging technology could be used in dy-namic observation of living imaging and detection of bone density in the animal model of osteoarthritis ,and it is significant for evaluation of osteoarthritis model,and its realted tesearch.%目的:利用多光谱小动物活体成像技术动态观察和评价大鼠骨性关节炎模型的应用价值。方法:取3月龄SD雄性大鼠15只(180±20) g,利用碘乙酸关节腔注

  2. Quantitatively differentiating microstructural variations of skeletal muscle tissues by multispectral Mueller matrix imaging

    Science.gov (United States)

    Dong, Yang; He, Honghui; He, Chao; Ma, Hui

    2016-10-01

    Polarized light is sensitive to the microstructures of biological tissues and can be used to detect physiological changes. Meanwhile, spectral features of the scattered light can also provide abundant microstructural information of tissues. In this paper, we take the backscattering polarization Mueller matrix images of bovine skeletal muscle tissues during the 24-hour experimental time, and analyze their multispectral behavior using quantitative Mueller matrix parameters. In the processes of rigor mortis and proteolysis of muscle samples, multispectral frequency distribution histograms (FDHs) of the Mueller matrix elements can reveal rich qualitative structural information. In addition, we analyze the temporal variations of the sample using the multispectral Mueller matrix transformation (MMT) parameters. The experimental results indicate that the different stages of rigor mortis and proteolysis for bovine skeletal muscle samples can be judged by these MMT parameters. The results presented in this work show that combining with the multispectral technique, the FDHs and MMT parameters can characterize the microstructural variation features of skeletal muscle tissues. The techniques have the potential to be used as tools for quantitative assessment of meat qualities in food industry.

  3. Low-complexity image processing for a high-throughput low-latency snapshot multispectral imager with integrated tiled filters

    Science.gov (United States)

    Geelen, Bert; Jayapala, Murali; Tack, Nicolaas; Lambrechts, Andy

    2013-05-01

    Traditional spectral imaging cameras typically operate as pushbroom cameras by scanning a scene. This approach makes such cameras well-suited for high spatial and spectral resolution scanning applications, such as remote sensing and machine vision, but ill-suited for 2D scenes with free movement. This limitation can be overcome by single frame, multispectral (here called snapshot) acquisition, where an entire three-dimensional multispectral data cube is sensed at one discrete point in time and multiplexed on a 2D sensor. Our snapshot multispectral imager is based on optical filters monolithically integrated on CMOS image sensors with large layout flexibility. Using this flexibility, the filters are positioned on the sensor in a tiled layout, allowing trade-offs between spatial and spectral resolution. At system-level, the filter layout is complemented by an optical sub-system which duplicates the scene onto each filter tile. This optical sub-system and the tiled filter layout lead to a simple mapping of 3D spectral cube data on the sensor, facilitating simple cube assembly. Therefore, the required image processing consists of simple and highly parallelizable algorithms for reflectance and cube assembly, enabling real-time acquisition of dynamic 2D scenes at low latencies. Moreover, through the use of monolithically integrated optical filters the multispectral imager achieves the qualities of compactness, low cost and high acquisition speed, further differentiating it from other snapshot spectral cameras. Our prototype camera can acquire multispectral image cubes of 256x256 pixels over 32 bands in the spectral range of 600-1000nm at 340 cubes per second for normal illumination levels.

  4. Two Levels Fusion Decision for Multispectral Image Pattern Recognition

    Science.gov (United States)

    Elmannai, H.; Loghmari, M. A.; Naceur, M. S.

    2015-10-01

    Major goal of multispectral data analysis is land cover classification and related applications. The dimension drawback leads to a small ratio of the remote sensing training data compared to the number of features. Therefore robust methods should be associated to overcome the dimensionality curse. The presented work proposed a pattern recognition approach. Source separation, feature extraction and decisional fusion are the main stages to establish an automatic pattern recognizer. The first stage is pre-processing and is based on non linear source separation. The mixing process is considered non linear with gaussians distributions. The second stage performs feature extraction for Gabor, Wavelet and Curvelet transform. Feature information presentation provides an efficient information description for machine vision projects. The third stage is a decisional fusion performed in two steps. The first step assign the best feature to each source/pattern using the accuracy matrix obtained from the learning data set. The second step is a source majority vote. Classification is performed by Support Vector Machine. Experimentation results show that the proposed fusion method enhances the classification accuracy and provide powerful tool for pattern recognition.

  5. 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.

  6. An improved partial SPIHT with classified weighted rate-distortion optimization for interferential multispectral image compression

    Institute of Scientific and Technical Information of China (English)

    Keyan Wang; Chengke Wu; Fanqiang Kong; Lei Zhang

    2008-01-01

    Based on the property analysis of interferential multispectral images, a novel compression algorithm of partial set partitioning in hierarchical trees (SPIHT) with classified weighted rate-distortion optimization is presented.After wavelet decomposition, partial SPIHT is applied to each zero tree independently by adaptively selecting one of three coding modes according to the probability of the significant coefficients in each bitplane.Meanwhile the interferential multispectral image is partitioned into two kinds of regions in terms of luminous intensity, and the rate-distortion slopes of zero trees are then lifted with classified weights according to their distortion contribution to the constructed spectrum.Finally a global ratedistortion optimization truncation is performed.Compared with the conventional methods, the proposed algorithm not only improves the performance in spatial domain but also reduces the distortion in spectral domain.

  7. Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Czapski Paweł

    2015-09-01

    Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

  8. Identification of tissular origin of particles based on autofluorescence multispectral image analysis at the macroscopic scale

    Science.gov (United States)

    Corcel, Mathias; Devaux, Marie-Françoise; Guillon, Fabienne; Barron, Cécile

    2017-06-01

    Powders produced from plant materials are heterogeneous in relation to native plant heterogeneity, and during grinding, dissociation often occurred at the tissue scale. The tissue composition of powdery samples could be modified through dry fractionation diagrams and impact their end-uses properties. If tissue identification is often made on native plant structure, this characterization is not straightforward in destructured samples such powders. Taking advantage of the autofluorescence properties of cell wall components, multispectral image acquisition is envisioned to identify the tissular origin of particles. Images were acquired on maize stem sections and ground tissues isolated from the same stem by hand dissection. The variability in fluorescence intensity profiles was analysed using principal component analysis. The correspondence between fluorescence profiles and the different tissues observed in maize sections was assessed based on histology or known compositional heterogeneity. Similar variability was encountered in fluorescence profiles extracted from powder leading to the potential ability to predict tissular origin based on this autofluorescence multispectral signal.

  9. Integration of SAR features into multispectral images based on the nonsubsampled contourlet and IHS transform

    Science.gov (United States)

    Yang, Zhixiang; He, Xiufeng; Xu, Jia

    2011-10-01

    As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.

  10. Demultiplexing Visible and Near-Infrared Information in Single- Sensor Multispectral Imaging

    OpenAIRE

    Sadeghipoor, Zahra; Thomas, Jean-Baptiste; Süsstrunk, Sabine

    2016-01-01

    In this paper, we study a single-sensor imaging system that uses a multispectral filter array to spectrally sample the scene. Our system captures information in both visible and near-infrared bands of the electromagnetic spectrum. Due to manufacturing limitations, the visible filters in this system also transmit the NIR radiation. Similarly, visible light is transmitted by the NIR filter, leading to inaccurate mixed spectral measurements. We present an algorithm that resolves this issue by se...

  11. Viola-Jones based hybrid framework for real-time object detection in multispectral images

    Science.gov (United States)

    Kuznetsova, E.; Shvets, E.; Nikolaev, D.

    2015-12-01

    This paper describes a method for real-time object detection based on a hybrid of a Viola-Jones cascade with a convolutional neural network. This scheme allows flexible trade-offs between detection quality and computational performance. We also propose a generalization of this method to multispectral images that effectively and efficiently utilizes information from each spectral channel. The new scheme is experimentally compared to traditional Viola-Jones, showing improved detection quality with adjustable performance.

  12. ADVANCES IN HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION AND SPECTRAL UNMIXING

    OpenAIRE

    C. Lanaras; E. Baltsavias; K. Schindler

    2015-01-01

    In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image. We assume that the two images are radiometrically corrected and geometrically co-registered. The scientific contributions of this work are (a) a simultaneous approa...

  13. Automatic recognition of abnormal cells in cytological tests using multispectral imaging

    Science.gov (United States)

    Gertych, A.; Galliano, G.; Bose, S.; Farkas, D. L.

    2010-03-01

    Cervical cancer is the leading cause of gynecologic disease-related death worldwide, but is almost completely preventable with regular screening, for which cytological testing is a method of choice. Although such testing has radically lowered the death rate from cervical cancer, it is plagued by low sensitivity and inter-observer variability. Moreover, its effectiveness is still restricted because the recognition of shape and morphology of nuclei is compromised by overlapping and clumped cells. Multispectral imaging can aid enhanced morphological characterization of cytological specimens. Features including spectral intensity and texture, reflecting relevant morphological differences between normal and abnormal cells, can be derived from cytopathology images and utilized in a detection/classification scheme. Our automated processing of multispectral image cubes yields nuclear objects which are subjected to classification facilitated by a library of spectral signatures obtained from normal and abnormal cells, as marked by experts. Clumps are processed separately with reduced set of signatures. Implementation of this method yields high rate of successful detection and classification of nuclei into predefined malignant and premalignant types and correlates well with those obtained by an expert. Our multispectral approach may have an impact on the diagnostic workflow of cytological tests. Abnormal cells can be automatically highlighted and quantified, thus objectivity and performance of the reading can be improved in a way which is currently unavailable in clinical setting.

  14. Hemodynamic and morphologic responses in mouse brain during acute head injury imaged by multispectral structured illumination

    Science.gov (United States)

    Volkov, Boris; Mathews, Marlon S.; Abookasis, David

    2015-03-01

    Multispectral imaging has received significant attention over the last decade as it integrates spectroscopy, imaging, tomography analysis concurrently to acquire both spatial and spectral information from biological tissue. In the present study, a multispectral setup based on projection of structured illumination at several near-infrared wavelengths and at different spatial frequencies is applied to quantitatively assess brain function before, during, and after the onset of traumatic brain injury in an intact mouse brain (n=5). For the production of head injury, we used the weight drop method where weight of a cylindrical metallic rod falling along a metal tube strikes the mouse's head. Structured light was projected onto the scalp surface and diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse head. Following data analysis, we were able to concurrently show a series of hemodynamic and morphologic changes over time including higher deoxyhemoglobin, reduction in oxygen saturation, cell swelling, etc., in comparison with baseline measurements. Overall, results demonstrates the capability of multispectral imaging based structured illumination to detect and map of brain tissue optical and physiological properties following brain injury in a simple noninvasive and noncontact manner.

  15. Multispectral Imaging and Analysis of the Rosette Nebula

    Science.gov (United States)

    Huber, Jeremy; Kielkopf, J. F.; Ferland, G. J.; Clark, F. O.

    2013-06-01

    With the goal of understanding the three dimensional structure and fundamental physical processes of the Rosette Nebula and its associated cluster NGC 2244, we have acquired flux-calibrated, 4-degree field, deep exposures of the Rosette region through 3 nm bandwidth Hα (656.3 nm) as well as Hβ (486.1nm), O[III] (500.7 nm) and S[II] (671.6 nm) filters with 4.5 nm bandwidth. The 4 arcsec/pixel images are supplemented with 4 degree field slit spectra and combined with archival WISE data in the 3.4, 4.6, 12, and 22 micron bands, published single dish radio data of the hydrogen continuum at 1410, 2700, and 4750 MHz, and Chandra X-ray data to form a data array allowing comparison and analysis of this important star forming region across the electromagnetic spectrum. The new observational data also allow the development of useful new image maps. The Hα to Hβ ratio yields extinction in the visible spectrum by dust across the region, and the 1410 MHz hydrogen continuum to Hα line ratio reveals structure obscured in the optical bands. A radial profile analysis of large scale Hα emission from the Rosette is found to be inconsistent with an assumption of a simple spherically symmetric region, and suggests a partially unobstructed view of the central cluster. These data are the basis for work in progress to develop a comprehensive model of the structure and radiative processes in the Rosette region with CLOUDY and CLOUDY-3D.

  16. A portable UV-fluorescence multispectral imaging system for the analysis of painted surfaces.

    Science.gov (United States)

    Comelli, Daniela; Valentini, Gianluca; Nevin, Austin; Farina, Andrea; Toniolo, Lucia; Cubeddu, Rinaldo

    2008-08-01

    A portable fluorescence multispectral imaging system was developed and has been used for the analysis of artistic surfaces. The imaging apparatus exploits two UV lamps for fluorescence excitation and a liquid crystal tunable filter coupled to a low-noise charge coupled device as the image detector. The main features of the system are critically presented, outlining the assets, drawbacks, and practical considerations of portability. A multivariate statistical treatment of spectral data is further considered. Finally, the in situ analysis with the new apparatus of recently restored Renaissance wall paintings is presented.

  17. Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging

    Science.gov (United States)

    Li, Weizhi; Mo, Weirong; Zhang, Xu; Squiers, John J.; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2015-12-01

    Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately representing the burn tissue was needed, but assigning raw MSI data to appropriate tissue classes is prone to error. We hypothesized that removing outliers from the training dataset would improve classification accuracy. A swine burn model was developed to build an MSI training database and study an algorithm's burn tissue classification abilities. After the ground-truth database was generated, we developed a multistage method based on Z-test and univariate analysis to detect and remove outliers from the training dataset. Using 10-fold cross validation, we compared the algorithm's accuracy when trained with and without the presence of outliers. The outlier detection and removal method reduced the variance of the training data. Test accuracy was improved from 63% to 76%, matching the accuracy of clinical judgment of expert burn surgeons, the current gold standard in burn injury assessment. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

  18. Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging.

    Science.gov (United States)

    Li, Weizhi; Mo, Weirong; Zhang, Xu; Squiers, John J; Lu, Yang; Sellke, Eric W; Fan, Wensheng; DiMaio, J Michael; Thatcher, Jeffrey E

    2015-12-01

    Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately representing the burn tissue was needed, but assigning raw MSI data to appropriate tissue classes is prone to error. We hypothesized that removing outliers from the training dataset would improve classification accuracy. A swine burn model was developed to build an MSI training database and study an algorithm’s burn tissue classification abilities. After the ground-truth database was generated, we developed a multistage method based on Z -test and univariate analysis to detect and remove outliers from the training dataset. Using 10-fold cross validation, we compared the algorithm’s accuracy when trained with and without the presence of outliers. The outlier detection and removal method reduced the variance of the training data. Test accuracy was improved from 63% to 76%, matching the accuracy of clinical judgment of expert burn surgeons, the current gold standard in burn injury assessment. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

  19. Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management.

    Science.gov (United States)

    Du, Qian; Chang, Ni-Bin; Yang, Chenghai; Srilakshmi, Kanth R

    2008-01-01

    The Lower Rio Grande Valley (LRGV) of south Texas is an agriculturally rich area supporting intensive production of vegetables, fruits, grain sorghum, and cotton. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yields. Intensive agricultural activities in past decades might have caused potential contamination of soil, surface water, and groundwater due to leaching of pesticides in the vadose zone. In an effort to promote precision farming in citrus production, this paper aims at developing an airborne multispectral technique for identifying tree health problems in a citrus grove that can be combined with variable rate technology (VRT) for required pesticide application and environmental modeling for assessment of pollution prevention. An unsupervised linear unmixing method was applied to classify the image for the grove and quantify the symptom severity for appropriate infection control. The PRZM-3 model was used to estimate environmental impacts that contribute to nonpoint source pollution with and without the use of multispectral remote sensing and VRT. Research findings using site-specific environmental assessment clearly indicate that combination of remote sensing and VRT may result in benefit to the environment by reducing the nonpoint source pollution by 92.15%. Overall, this study demonstrates the potential of precision farming for citrus production in the nexus of industrial ecology and agricultural sustainability.

  20. Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

    Science.gov (United States)

    Ewerlöf, Maria; Larsson, Marcus; Salerud, E. Göran

    2017-02-01

    Hyperspectral imaging (HSI) can estimate the spatial distribution of skin blood oxygenation, using visible to near-infrared light. HSI oximeters often use a liquid-crystal tunable filter, an acousto-optic tunable filter or mechanically adjustable filter wheels, which has too long response/switching times to monitor tissue hemodynamics. This work aims to evaluate a multispectral snapshot imaging system to estimate skin blood volume and oxygen saturation with high temporal and spatial resolution. We use a snapshot imager, the xiSpec camera (MQ022HG-IM-SM4X4-VIS, XIMEA), having 16 wavelength-specific Fabry-Perot filters overlaid on the custom CMOS-chip. The spectral distribution of the bands is however substantially overlapping, which needs to be taken into account for an accurate analysis. An inverse Monte Carlo analysis is performed using a two-layered skin tissue model, defined by epidermal thickness, haemoglobin concentration and oxygen saturation, melanin concentration and spectrally dependent reduced-scattering coefficient, all parameters relevant for human skin. The analysis takes into account the spectral detector response of the xiSpec camera. At each spatial location in the field-of-view, we compare the simulated output to the detected diffusively backscattered spectra to find the best fit. The imager is evaluated for spatial and temporal variations during arterial and venous occlusion protocols applied to the forearm. Estimated blood volume changes and oxygenation maps at 512x272 pixels show values that are comparable to reference measurements performed in contact with the skin tissue. We conclude that the snapshot xiSpec camera, paired with an inverse Monte Carlo algorithm, permits us to use this sensor for spatial and temporal measurement of varying physiological parameters, such as skin tissue blood volume and oxygenation.

  1. An interventional multispectral photoacoustic imaging platform for the guidance of minimally invasive procedures

    Science.gov (United States)

    Xia, Wenfeng; Nikitichev, Daniil I.; Mari, Jean Martial; West, Simeon J.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

    2015-07-01

    Precise and efficient guidance of medical devices is of paramount importance for many minimally invasive procedures. These procedures include fetal interventions, tumor biopsies and treatments, central venous catheterisations and peripheral nerve blocks. Ultrasound imaging is commonly used for guidance, but it often provides insufficient contrast with which to identify soft tissue structures such as vessels, tumors, and nerves. In this study, a hybrid interventional imaging system that combines ultrasound imaging and multispectral photoacoustic imaging for guiding minimally invasive procedures was developed and characterized. The system provides both structural information from ultrasound imaging and molecular information from multispectral photoacoustic imaging. It uses a commercial linear-array ultrasound imaging probe as the ultrasound receiver, with a multimode optical fiber embedded in a needle to deliver pulsed excitation light to tissue. Co-registration of ultrasound and photoacoustic images is achieved with the use of the same ultrasound receiver for both modalities. Using tissue ex vivo, the system successfully discriminated deep-located fat tissue from the surrounding muscle tissue. The measured photoacoustic spectrum of the fat tissue had good agreement with the lipid spectrum in literature.

  2. Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

    Science.gov (United States)

    Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

    2017-09-01

    In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

  3. EDGE DETECTION IN MULTISPECTRAL IMAGES BASED ON STRUCTURAL ELEMENTS

    Directory of Open Access Journals (Sweden)

    Mehdi Ghasemi Naraghi

    2011-02-01

    Full Text Available One of the first steps of feature extraction is edge detection. There are various methods for edge detection such as sobel operator, log method and canny operator. These methods have disadvantages such as create noise and discontinues edge and image smoothing. With the notice of the daily growth multi spectral images processing and describe of these images have become very important. Because of the existence of many details of these images, necessity to robust algorithms caused to present a method to extract feature of an object. In this article An improve method for edge detection has been purposed. In this method edge is detected by morphology’s operator and their combination and with the use of various structure elements of images in satellite and remote sensing.

  4. Edge Detection in Multispectral Images Based on Structural Elements

    Directory of Open Access Journals (Sweden)

    Mehdi Ghasemi Naraghi

    2011-02-01

    Full Text Available One of the first steps of feature extraction is edge detection. There are various methods for edge detection such as sobel operator, log method and canny operator. These methods have disadvantages such as create noise and discontinues edge and image smoothing. With the notice of the daily growth multi spectral images processing and describe of these images have become very important. Because of the existence of many details of these images, necessity to robust algorithms caused to present a method to extract featureof an object. In this article An improve method for edge detection has been purposed. In this method edge is detected by morphology’s operator and their combination and with the use of various structure elements of images in satellite and remote sensing.

  5. Compact multispectral fluorescence imaging system with spectral multiplexed volume holographic grating

    Science.gov (United States)

    Lv, Yanlu; Cai, Chuangjian; Bai, Jing; Luo, Jianwen

    2016-12-01

    Traditional spectral imaging systems mainly rely on spatial scanning or spectral scanning methods to acquire spatial and spectral features. The acquisition is time-consuming and cannot fully satisfy the need of monitoring dynamic phenomenon and observing different structures of the specimen simultaneously. To overcome these barriers, we develop a video-rate simultaneous multispectral imaging system built with a spectral multiplexed volume holographic grating (VHG) and few optical components. Four spectral multiplexed volume holograms optimized for four discrete spectral bands (centered at 488 nm, 530 nm, 590 nm and 620 nm) are recorded into an 8×12 mm photo-thermal refractive glass. The diffraction efficiencies of all the holograms within the multiplexed VHG are greater than 80%. With the high throughout multiplexed VHG, the system can work with both reflection and fluorescence modes and allow simultaneous acquisition of spectral and spatial information with a single exposure. Imaging experiments demonstrate that the multispectral images of the target illuminated with white light source can be obtained. Fluorescence images of multiple fluorescence objects (two glass beads filled with 20 uL 1.0 mg/mL quantum dots solutions that emit 530 +/- 15 nm and 620 +/- 15 nm fluorescence, respectively) buried 3 mm below the surface of a tissue mimicking phantom are acquired. The results demonstrate that the system can provide complementary information in fluorescence imaging. The design diagram of the proposed system is given to explain the advantage of compactness and flexibility in integrating with other imaging platforms.

  6. NSCT-based fusion enhancement for multispectral finger-vein images

    Science.gov (United States)

    Wu, Dongdong; Yang, Jinfeng

    2014-04-01

    Personal identification based on single-spectral finger-vein image has been widely investigated recently. However, in finger-vein imaging, finger-vein image degradation is the main factor causing lower recognition accuracy. So, to improve the finger-vein image quality, in this paper, multispectral finger-vein images (760nm and 850nm) are fused together for contrast enhancement using NSCT transformation. The proposed method can preserve the completeness and sharpness of finger-vein. Experimental results demonstrate that the proposed method is certainly powerful in enhancing finger-vein image contrast and achieves lower equal error rates in finger-vein recognition even if original images have poor contrast.

  7. Multispectral high-resolution hologram generation using orthographic projection images

    Science.gov (United States)

    Muniraj, I.; Guo, C.; Sheridan, J. T.

    2016-08-01

    We present a new method of synthesizing a digital hologram of three-dimensional (3D) real-world objects from multiple orthographic projection images (OPI). A high-resolution multiple perspectives of 3D objects (i.e., two dimensional elemental image array) are captured under incoherent white light using synthetic aperture integral imaging (SAII) technique and their OPIs are obtained respectively. The reference beam is then multiplied with the corresponding OPI and integrated to form a Fourier hologram. Eventually, a modified phase retrieval algorithm (GS/HIO) is applied to reconstruct the hologram. The principle is validated experimentally and the results support the feasibility of the proposed method.

  8. Identification Of Barley Grain Mycoflora By Next Generation Sequencing And Videometer Multispectral Imaging

    DEFF Research Database (Denmark)

    Jørgensen, Johannes Ravn; Carstensen, Jens Michael; Søren, Knudsen

    on the dorsal and ventral sides by the VideometerLab multispectral imaging system (Videometer A/S, Hørsholm, Denmark). This system is an instrument equipped with 19 different light emitting diodes at wavelengths ranging from 375 to 970nm (ultraviolet, visual and lower wavelength of the near-infrared region....... Analytical separation of the identified fungi was based on mean pixel intensity and a normalized Canonical Discriminant Analysis (nCDA) using the images of infected and healthy seeds. The potential of using spectral characteristics of the fungal species as a way to provide a fast optical screening method...

  9. Adaptive FPGA NoC-based Architecture for Multispectral Image Correlation

    CERN Document Server

    Zhang, Linlin; Fresse, Virginie; Fischer, Viktor

    2009-01-01

    An adaptive FPGA architecture based on the NoC (Network-on-Chip) approach is used for the multispectral image correlation. This architecture must contain several distance algorithms depending on the characteristics of spectral images and the precision of the authentication. The analysis of distance algorithms is required which bases on the algorithmic complexity, result precision, execution time and the adaptability of the implementation. This paper presents the comparison of these distance computation algorithms on one spectral database. The result of a RGB algorithm implementation was discussed.

  10. MULTISPECTRAL MICROSCOPY AND COMPUTERIZED IMAGE ANALYSIS: A METHOD TO OBTAIN MORE RELIABLE AND REPRODUCIBLE IMMUNOHISTOCHEMISTRY RESULTS

    Directory of Open Access Journals (Sweden)

    Giovanni Francesco Spatola

    2015-04-01

    Full Text Available The use of image analysis methods has allowed us to obtain more reliable and repro-ducible immunohistochemistry (IHC results. Wider use of such approaches and sim-plification of software allowing a colorimetric study has meant that these methods are available to everyone, and made it possible to standardize the technique by a reliable systems score. Moreover, the recent introduction of multispectral image acquisition systems methods has further refined these techniques, minimizing artefacts and eas-ing the evaluation of the data by the observer.

  11. Multispectral image feature fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Fields, D.J.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)] [and others

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  12. Black phosphorus photodetector for multispectral, high-resolution imaging.

    Science.gov (United States)

    Engel, Michael; Steiner, Mathias; Avouris, Phaedon

    2014-11-12

    Black phosphorus is a layered semiconductor that is intensely researched in view of applications in optoelectronics. In this letter, we investigate a multilayer black phosphorus photodetector that is capable of acquiring high-contrast (V > 0.9) images both in the visible (λVIS = 532 nm) as well as in the infrared (λIR = 1550 nm) spectral regime. In a first step, by using photocurrent microscopy, we map the active area of the device and we characterize responsivity and gain. In a second step, by deploying the black phosphorus device as a point-like detector in a confocal microsope setup, we acquire diffraction-limited optical images with submicron resolution. The results demonstrate the usefulness of black phosphorus as an optoelectronic material for hyperspectral imaging applications.

  13. Multispectral mid-infrared imaging using frequency upconversion

    DEFF Research Database (Denmark)

    Sanders, Nicolai Højer; Dam, Jeppe Seidelin; Jensen, Ole Bjarlin;

    2013-01-01

    It has recently been shown that it is possible to upconvert infrared images to the near infrared region with high quantum efficiency and low noise by three-wave mixing with a laser field [1]. If the mixing laser is single-frequency, the upconverted image is simply a band-pass filtered version......: Infrared imaging, nonlinear frequency conversion, diode lasers, upconversion ] of the nonlinear material. Unfortunately, temperature tuning is slow, and angle tuning typically results in alignment issues. Here we present a novel approach where the wavelength of the mixing field is used as a tuning...... feedback grating. The output from a tunable laser is used as seed for a fiber amplifier system, boosting the power to approx. 3 W over the tuning range from 1025 to 1085 nm. Using a periodically poled lithium niobate crystal, the infrared wavelength that can be phase-matched is tunable over more than 200...

  14. Multispectral mid-infrared imaging using frequency upconversion

    DEFF Research Database (Denmark)

    Sanders, Nicolai Højer; Dam, Jeppe Seidelin; Jensen, Ole Bjarlin

    2013-01-01

    of the infrared object field, with a bandwidth corresponding given by the acceptance parameter of the conversion process, and a center frequency given by the phase-match condition. Tuning of the phase-matched wavelengths has previously been demonstrated by changing the temperature [2] or angle [3 Keywords......It has recently been shown that it is possible to upconvert infrared images to the near infrared region with high quantum efficiency and low noise by three-wave mixing with a laser field [1]. If the mixing laser is single-frequency, the upconverted image is simply a band-pass filtered version......: Infrared imaging, nonlinear frequency conversion, diode lasers, upconversion ] of the nonlinear material. Unfortunately, temperature tuning is slow, and angle tuning typically results in alignment issues. Here we present a novel approach where the wavelength of the mixing field is used as a tuning...

  15. Correction of motion artefacts and pseudo colour visualization of multispectral light scattering images for optical diagnosis of rheumatoid arthritis

    Science.gov (United States)

    Minet, Olaf; Scheibe, Patrick; Beuthan, Jürgen; Zabarylo, Urszula

    2010-02-01

    State-of-the-art image processing methods offer new possibilities for diagnosing diseases using scattered light. The optical diagnosis of rheumatism is taken as an example to show that the diagnostic sensitivity can be improved using overlapped pseudo-coloured images of different wavelengths, provided that multispectral images are recorded to compensate for any motion related artefacts which occur during examination.

  16. [Comparison of performances in retrieving impervious surface between hyperspectral (Hyperion) and multispectral (TM/ETM+) images].

    Science.gov (United States)

    Tang, Fei; Xu, Han-Qiu

    2014-04-01

    The retrieval of impervious surface is a hot topic in the remote sensing field in the past decade. Nevertheless, studies on retrieving impervious surface from hyperspectral image and the comparison of the performances in retrieving impervious surface between hyperspectral and multispectral images are rarely reported. Therefore, The present paper focuses on the characteristics of hyperspectral (EO-1 Hyperion) and multispectral (Landsat TM/ETM+) images and implements a complementary study on the comparison based on the retrieved impervious surface information between Hyperion and TM/ETM+ data. For up to 242 bands of Hyperion image, a further study was carried out to select feature bands for impervious surface retrieving using stepwise discriminant analysis. As a result, 11 feature bands were selected and a new image named Hyperion' was thus composed. The new Hyperion' image was used to investigate whether this band-reduced image could obtain higher accuracy in retrieving impervious surface. The three test regions were selected from Fuzhou, Guangzhou and Hangzhou of China, with date-coincident or nearly coincident image pairs of the used sensors. The linear spectral mixture analysis (LSMA) was employed to retrieve impervious surface and the results were accessed for their accuracy. The comparison shows that the Hyperion image has higher accuracy than TM/ETM+, and the Hyperion' composed of the selected 11 feature bands has the highest accuracy. The advantages of Hyperion in spectral and radiometric resolutions over TM/ETM+ are believed to be the main factors contributing to the higher accuracy. The high spectral and radiometric resolutions of Hyperion image allow the sensor to have higher sensitivity in distinguishing subtle spectral changes of ground objects. While, the highest accuracy the 11-band Hyperion' image achieved is owing to the significant reduction of the band dimension of the image and thus the band redundancy.

  17. 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.

  18. Imaging high-intensity focused ultrasound-induced tissue denaturation by multispectral photoacoustic method: an ex vivo study.

    Science.gov (United States)

    Sun, Yao; O'Neill, Brian

    2013-03-10

    We present an ex vivo study for the first time, to the best of our knowledge, in multispectral photoacoustic imaging (PAI) of tissue denaturation induced by high-intensity focused ultrasound (HIFU) in this paper. Tissue of bovine muscle was thermally treated in a heated water bath and by HIFU, and then was imaged using a multispectral photoacoustic approach. Light at multiple optical wavelengths between 700 and 900 nm was delivered to the treated bovine muscle tissue to excite the photoacoustic signal. Apparent tissue denaturation has been observed in multispectral photoacoustic images after being treated in a water bath and by HIFU. It is interesting that the denaturation is more striking at shorter optical wavelength photoacoustic images than at longer optical wavelength photoacoustic images. Multispectral photoacoustic images of the tissue denaturation were further analyzed and the photoacoustic spectrums of the denaturized tissue were calculated in this paper. This study suggests that a multispectral PAI approach might be a promising tool to evaluate tissue denaturation induced by HIFU treatment.

  19. Nondestructive determination of transgenic Bacillus thuringiensis rice seeds (Oryza sativa L.) using multispectral imaging and chemometric methods.

    Science.gov (United States)

    Liu, Changhong; Liu, Wei; Lu, Xuzhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

    2014-06-15

    Crop-to-crop transgene flow may affect the seed purity of non-transgenic rice varieties, resulting in unwanted biosafety consequences. The feasibility of a rapid and nondestructive determination of transgenic rice seeds from its non-transgenic counterparts was examined by using multispectral imaging system combined with chemometric data analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), least squares-support vector machines (LS-SVM), and PCA-back propagation neural network (PCA-BPNN) methods were applied to classify rice seeds according to their genetic origins. The results demonstrated that clear differences between non-transgenic and transgenic rice seeds could be easily visualized with the nondestructive determination method developed through this study and an excellent classification (up to 100% with LS-SVM model) can be achieved. It is concluded that multispectral imaging together with chemometric data analysis is a promising technique to identify transgenic rice seeds with high efficiency, providing bright prospects for future applications.

  20. Chromaffin cell calcium signal and morphology study based on multispectral images

    Science.gov (United States)

    Wu, Hongxiu; Wei, Shunhui; Qu, Anlian; Zhou, Zhuan

    1998-09-01

    Increasing or decreasing the internal calcium concentration can promote or prevent programmed cell death (PCD). We therefore performed a Ca2+ imaging study using Ca2+ indicator dye fura-2 and a sensitive cooled-CCD camera with a 12 bit resolution. Monochromatic beams of light with a wavelength of 345,380 nm were isolated from light emitted by a xenon lamp using a monochromator. The concentration of free calcium can be directly calculated from the ratio of two fluorescence values taken at two appropriately selected wavelength. Fluorescent light emitted from the cells was capture using a camera system. The cell morphology study is based on multispectral scanning, with smear images provided as three monochromatic images by illumination with light of 610,535 and 470 nm wavelengths. The nuclear characteristic parameters extracted from individual nuclei by system are nuclear area, nuclear diameter, nuclear density vector. The results of the restoration of images and the performance of a primitive logic for the detection of nuclei with PCD proved the usefulness of the system and the advantages of using multispectral images in the restoration and detection procedures.

  1. A comparative performance study characterizing breast tissue microarrays using standard RGB and multispectral imaging

    Science.gov (United States)

    Qi, Xin; Cukierski, William; Foran, David J.

    2010-02-01

    The lack of clear consensus over the utility of multispectral imaging (MSI) for bright-field imaging prompted our team to investigate the benefit of using MSI on breast tissue microarrays (TMA). We have conducted performance studies to compare MSI with standard bright-field imaging in hematoxylin stained breast tissue. The methodology has three components. The first extracts a region of interest using adaptive thresholding and morphological processing. The second performs texture feature extraction from a local binary pattern within each spectral channel and compared to features of co-occurrence matrix and texture feature coding in third component. The third component performs feature selection and classification. For each spectrum, exhaustive feature selection was used to search for the combination of features that yields the best classification accuracy. AdaBoost with a linear perceptron least-square classifier was applied. The spectra carrying the greatest discriminatory power were automatically chosen and a majority vote was used to make the final classification. 92 breast TMA discs were included in the study. Sensitivity of 0.96 and specificity of 0.89 were achieved on the multispectral data, compared with sensitivity of 0.83 and specificity of 0.85 on RGB data. MSI consistently achieved better classification results than those obtained using standard RGB images. While the benefits of MSI for unmixing multi-stained specimens are well documented, this study demonstrated statistically significant improvements in the automated analysis of single stained bright-field images.

  2. Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars

    Science.gov (United States)

    Nunez, Jorge; Farmer, Jack; Sellar, R. Glenn; Swayze, Gregg A.; Blaney, Diana L.

    2014-01-01

    Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars.

  3. Science applications of a multispectral microscopic imager for the astrobiological exploration of Mars.

    Science.gov (United States)

    Núñez, Jorge I; Farmer, Jack D; Sellar, R Glenn; Swayze, Gregg A; Blaney, Diana L

    2014-02-01

    Future astrobiological missions to Mars are likely to emphasize the use of rovers with in situ petrologic capabilities for selecting the best samples at a site for in situ analysis with onboard lab instruments or for caching for potential return to Earth. Such observations are central to an understanding of the potential for past habitable conditions at a site and for identifying samples most likely to harbor fossil biosignatures. The Multispectral Microscopic Imager (MMI) provides multispectral reflectance images of geological samples at the microscale, where each image pixel is composed of a visible/shortwave infrared spectrum ranging from 0.46 to 1.73 μm. This spectral range enables the discrimination of a wide variety of rock-forming minerals, especially Fe-bearing phases, and the detection of hydrated minerals. The MMI advances beyond the capabilities of current microimagers on Mars by extending the spectral range into the infrared and increasing the number of spectral bands. The design employs multispectral light-emitting diodes and an uncooled indium gallium arsenide focal plane array to achieve a very low mass and high reliability. To better understand and demonstrate the capabilities of the MMI for future surface missions to Mars, we analyzed samples from Mars-relevant analog environments with the MMI. Results indicate that the MMI images faithfully resolve the fine-scale microtextural features of samples and provide important information to help constrain mineral composition. The use of spectral endmember mapping reveals the distribution of Fe-bearing minerals (including silicates and oxides) with high fidelity, along with the presence of hydrated minerals. MMI-based petrogenetic interpretations compare favorably with laboratory-based analyses, revealing the value of the MMI for future in situ rover-mediated astrobiological exploration of Mars.

  4. The Effect of Multispectral Image Fusion Enhancement on Human Efficiency

    Science.gov (United States)

    2017-03-20

    Additionally, we test this on a simple stimulus and task experimental struc- ture to understand the basic impacts of fusion on the visual system. Ideal observer...information heatmap help us tackle the problem space of image fusion in relation to human testing ? As we have seen even within our own basic experiment ...strengthen visual perception. We employ ideal observer analysis over a series of experimental conditions to (1) establish a framework for testing

  5. Spectral ladar: towards active 3D multispectral imaging

    Science.gov (United States)

    Powers, Michael A.; Davis, Christopher C.

    2010-04-01

    In this paper we present our Spectral LADAR concept, an augmented implementation of traditional LADAR. This sensor uses a polychromatic source to obtain range-resolved 3D spectral images which are used to identify objects based on combined spatial and spectral features, resolving positions in three dimensions and up to hundreds of meters in distance. We report on a proof-of-concept Spectral LADAR demonstrator that generates spectral point clouds from static scenes. The demonstrator transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Currently we use a rapidly tuned receiver with a high-speed InGaAs APD for 25 spectral bands with the future expectation of implementing a linear APD array spectrograph. Each spectral band is independently range resolved with multiple return pulse recognition. This is a critical feature, enabling simultaneous spectral and spatial unmixing of partially obscured objects when not achievable using image fusion of monochromatic LADAR and passive spectral imagers. This enables higher identification confidence in highly cluttered environments such as forested or urban areas (e.g. vehicles behind camouflage or foliage). These environments present challenges for situational awareness and robotic perception which can benefit from the unique attributes of Spectral LADAR. Results from this demonstrator unit are presented for scenes typical of military operations and characterize the operation of the device. The results are discussed here in the context of autonomous vehicle navigation and target recognition.

  6. Multispectral imaging approach for simplified non-invasive in-vivo evaluation of gingival erythema

    Science.gov (United States)

    Eckhard, Timo; Valero, Eva M.; Nieves, Juan L.; Gallegos-Rueda, José M.; Mesa, Francisco

    2012-03-01

    Erythema is a common visual sign of gingivitis. In this work, a new and simple low-cost image capture and analysis method for erythema assessment is proposed. The method is based on digital still images of gingivae and applied on a pixel-by-pixel basis. Multispectral images are acquired with a conventional digital camera and multiplexed LED illumination panels at 460nm and 630nm peak wavelength. An automatic work-flow segments teeth from gingiva regions in the images and creates a map of local blood oxygenation levels, which relates to the presence of erythema. The map is computed from the ratio of the two spectral images. An advantage of the proposed approach is that the whole process is easy to manage by dental health care professionals in clinical environment.

  7. Discrimination of haploid and diploid maize kernels via multispectral imaging

    DEFF Research Database (Denmark)

    De La Fuente, Gerald N.; Carstensen, Jens Michael; Adsetts Edberg Hansen, Michael

    2017-01-01

    and (ii) doubling of the haploid genome to produce fertile inbred lines. This study is focused on the first step. Currently, identification of maize haploid progeny is performed manually using the R1-nj seed colour marker. This is a labour-intensive and time-consuming process; a method for automated...... sorting of haploids would increase the efficiency of DH line development. In this study, six inbred lines were crossed with the maternal haploid inducer ‘RWS/RWK-76’ and a sample of seed was sorted manually for each line. Using the VideometerLab 3 system, spectral imaging techniques were applied...

  8. Developing handheld real time multispectral imager to clinically detect erythema in darkly pigmented skin

    Science.gov (United States)

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

    2010-02-01

    Pressure ulcers have been identified as a public health concern by the US government through the Healthy People 2010 initiative and the National Quality Forum (NQF). Currently, no tools are available to assist clinicians in erythema, i.e. the early stage pressure ulcer detection. The results from our previous research (supported by NIH grant) indicate that erythema in different skin tones can be identified using a set of wavelengths 540, 577, 650 and 970nm. This paper will report our recent work which is developing a handheld, point-of-care, clinicallyviable and affordable, real time multispectral imager to detect erythema in persons with darkly pigmented skin. Instead of using traditional filters, e.g. filter wheels, generalized Lyot filter, electrical tunable filter or the methods of dispersing light, e.g. optic-acoustic crystal, a novel custom filter mosaic has been successfully designed and fabricated using lithography and vacuum multi layer film technologies. The filter has been integrated with CMOS and CCD sensors. The filter incorporates four or more different wavelengths within the visual to nearinfrared range each having a narrow bandwidth of 30nm or less. Single wavelength area is chosen as 20.8μx 20.8μ. The filter can be deposited on regular optical glass as substrate or directly on a CMOS and CCD imaging sensor. This design permits a multi-spectral image to be acquired in a single exposure, thereby providing overwhelming convenience in multi spectral imaging acquisition.

  9. Multi-Spectral imaging of vegetation for detecting CO2 leaking from underground

    Energy Technology Data Exchange (ETDEWEB)

    Rouse, J.H.; Shaw, J.A.; Lawrence, R.L.; Lewicki, J.L.; Dobeck, L.M.; Repasky, K.S.; Spangler, L.H.

    2010-06-01

    Practical geologic CO{sub 2} sequestration will require long-term monitoring for detection of possible leakage back into the atmosphere. One potential monitoring method is multi-spectral imaging of vegetation reflectance to detect leakage through CO{sub 2}-induced plant stress. A multi-spectral imaging system was used to simultaneously record green, red, and near-infrared (NIR) images with a real-time reflectance calibration from a 3-m tall platform, viewing vegetation near shallow subsurface CO{sub 2} releases during summers 2007 and 2008 at the Zero Emissions Research and Technology field site in Bozeman, Montana. Regression analysis of the band reflectances and the Normalized Difference Vegetation Index with time shows significant correlation with distance from the CO{sub 2} well, indicating the viability of this method to monitor for CO{sub 2} leakage. The 2007 data show rapid plant vigor degradation at high CO{sub 2} levels next to the well and slight nourishment at lower, but above-background CO{sub 2} concentrations. Results from the second year also show that the stress response of vegetation is strongly linked to the CO{sub 2} sink-source relationship and vegetation density. The data also show short-term effects of rain and hail. The real-time calibrated imaging system successfully obtained data in an autonomous mode during all sky and daytime illumination conditions.

  10. Portable multispectral fluorescence imaging system for food safety applications

    Science.gov (United States)

    Lefcourt, Alan M.; Kim, Moon S.; Chen, Yud-Ren

    2004-03-01

    Fluorescence can be a sensitive method for detecting food contaminants. Of particular interest is detection of fecal contamination as feces is the source of many pathogenic organisms. Feces generally contain chlorophyll a and related compounds due to ingestion of plant materials, and these compounds can readily be detected using fluorescence techniques. Described is a fluorescence-imaging system consisting primarily of a UV light source, an intensified camera with a six-position filter wheel, and software for controlling the system and automatically analyzing the resulting images. To validate the system, orchard apples artificially contaminated with dairy feces were used in a "hands-on" public demonstration. The contamination sites were easily identified using automated edge detection and threshold detection algorithms. In addition, by applying feces to apples and then washing sets of apples at hourly intervals, it was determined that five h was the minimum contact time that allowed identification of the contamination site after the apples were washed. There are many potential uses for this system, including studying the efficacy of apple washing systems.

  11. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    Science.gov (United States)

    Heleno, Sandra; Matias, Magda; Pina, Pedro; Sousa, António Jorge

    2016-04-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

  12. Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

    Science.gov (United States)

    Heleno, S.; Matias, M.; Pina, P.; Sousa, A. J.

    2015-09-01

    A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

  13. Optical design of an optical coherence tomography and multispectral fluorescence imaging endoscope to detect early stage ovarian cancer

    Science.gov (United States)

    Tate, Tyler; Keenan, Molly; Swan, Elizabeth; Black, John; Utzinger, Urs; Barton, Jennifer

    2014-12-01

    The five year survival rate for ovarian cancer is over 90% if early detection occurs, yet no effective early screening method exists. We have designed and are constructing a dual modality Optical Coherence Tomography (OCT) and Multispectral Fluorescence Imaging (MFI) endoscope to optically screen the Fallopian tube and ovary for early stage cancer. The endoscope reaches the ovary via the natural pathway of the vagina, cervix, uterus and Fallopian tube. In order to navigate the Fallopian tube the endoscope must have an outer diameter of 600 μm, be highly flexible, steerable, tracking and nonperforating. The imaging systems consists of six optical subsystems, two from OCT and four from MFI. The optical subsystems have independent and interrelated design criteria. The endoscope will be tested on realistic tissue models and ex vivo tissue to prove feasibility of future human trials. Ultimately the project aims to provide women the first effective ovarian cancer screening technique.

  14. Design and evaluation of a device for fast multispectral time-resolved fluorescence spectroscopy and imaging

    Energy Technology Data Exchange (ETDEWEB)

    Yankelevich, Diego R. [Department of Electrical and Computer Engineering, University of California, 3101 Kemper Hall, Davis, California 95616 (United States); Department of Biomedical Engineering, University of California, 451 Health Sciences Drive, Davis, California 95616 (United States); Ma, Dinglong; Liu, Jing; Sun, Yang; Sun, Yinghua; Bec, Julien; Marcu, Laura, E-mail: lmarcu@ucdavis.edu [Department of Biomedical Engineering, University of California, 451 Health Sciences Drive, Davis, California 95616 (United States); Elson, Daniel S. [Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ (United Kingdom)

    2014-03-15

    The application of time-resolved fluorescence spectroscopy (TRFS) to in vivo tissue diagnosis requires a method for fast acquisition of fluorescence decay profiles in multiple spectral bands. This study focusses on development of a clinically compatible fiber-optic based multispectral TRFS (ms-TRFS) system together with validation of its accuracy and precision for fluorescence lifetime measurements. It also presents the expansion of this technique into an imaging spectroscopy method. A tandem array of dichroic beamsplitters and filters was used to record TRFS decay profiles at four distinct spectral bands where biological tissue typically presents fluorescence emission maxima, namely, 390, 452, 542, and 629 nm. Each emission channel was temporally separated by using transmission delays through 200 μm diameter multimode optical fibers of 1, 10, 19, and 28 m lengths. A Laguerre-expansion deconvolution algorithm was used to compensate for modal dispersion inherent to large diameter optical fibers and the finite bandwidth of detectors and digitizers. The system was found to be highly efficient and fast requiring a few nano-Joule of laser pulse energy and <1 ms per point measurement, respectively, for the detection of tissue autofluorescent components. Organic and biological chromophores with lifetimes that spanned a 0.8–7 ns range were used for system validation, and the measured lifetimes from the organic fluorophores deviated by less than 10% from values reported in the literature. Multi-spectral lifetime images of organic dye solutions contained in glass capillary tubes were recorded by raster scanning the single fiber probe in a 2D plane to validate the system as an imaging tool. The lifetime measurement variability was measured indicating that the system provides reproducible results with a standard deviation smaller than 50 ps. The ms-TRFS is a compact apparatus that makes possible the fast, accurate, and precise multispectral time-resolved fluorescence

  15. CMOS time-resolved, contact, and multispectral fluorescence imaging for DNA molecular diagnostics.

    Science.gov (United States)

    Guo, Nan; Cheung, Kawai; Wong, Hiu Tong; Ho, Derek

    2014-10-31

    Instrumental limitations such as bulkiness and high cost prevent the fluorescence technique from becoming ubiquitous for point-of-care deoxyribonucleic acid (DNA) detection and other in-field molecular diagnostics applications. The complimentary metal-oxide-semiconductor (CMOS) technology, as benefited from process scaling, provides several advanced capabilities such as high integration density, high-resolution signal processing, and low power consumption, enabling sensitive, integrated, and low-cost fluorescence analytical platforms. In this paper, CMOS time-resolved, contact, and multispectral imaging are reviewed. Recently reported CMOS fluorescence analysis microsystem prototypes are surveyed to highlight the present state of the art.

  16. CMOS Time-Resolved, Contact, and Multispectral Fluorescence Imaging for DNA Molecular Diagnostics

    Directory of Open Access Journals (Sweden)

    Nan Guo

    2014-10-01

    Full Text Available Instrumental limitations such as bulkiness and high cost prevent the fluorescence technique from becoming ubiquitous for point-of-care deoxyribonucleic acid (DNA detection and other in-field molecular diagnostics applications. The complimentary metal-oxide-semiconductor (CMOS technology, as benefited from process scaling, provides several advanced capabilities such as high integration density, high-resolution signal processing, and low power consumption, enabling sensitive, integrated, and low-cost fluorescence analytical platforms. In this paper, CMOS time-resolved, contact, and multispectral imaging are reviewed. Recently reported CMOS fluorescence analysis microsystem prototypes are surveyed to highlight the present state of the art.

  17. Pollution detection by digital correlation of multispectral, stero-image pairs.

    Science.gov (United States)

    Krause, F. R.; Betz, H. T.; Lysobey, D. H.

    1971-01-01

    Remote detection of air pollution circulation patterns is proposed to eventually predict the accumulation of hazardous surface concentrations in time for preventive emission control operations. Earth observations from space platforms will contain information on the height, mean velocity and lateral mixing scales of inversion layers and pollution plumes. Although this information is often not visible on photographs, it could conceivably be retrieved through a digital cross-correlation of multispectral stereo image pairs. Laboratory and field test results are used to illustrate the detection of non-visual inversion layers, the reduction of dominant signal interference, and the spectroscopic identification of combustion products.

  18. Multispectral image classification of MRI data using an empirically-derived clustering algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Horn, K.M.; Osbourn, G.C.; Bouchard, A.M. [Sandia National Labs., Albuquerque, NM (United States); Sanders, J.A. [Univ. of New Mexico, Albuquerque, NM (United States)]|[VA Hospital, Albuquerque, NM (United States)

    1998-08-01

    Multispectral image analysis of magnetic resonance imaging (MRI) data has been performed using an empirically-derived clustering algorithm. This algorithm groups image pixels into distinct classes which exhibit similar response in the T{sub 2} 1st and 2nd-echo, and T{sub 1} (with ad without gadolinium) MRI images. The grouping is performed in an n-dimensional mathematical space; the n-dimensional volumes bounding each class define each specific tissue type. The classification results are rendered again in real-space by colored-coding each grouped class of pixels (associated with differing tissue types). This classification method is especially well suited for class volumes with complex boundary shapes, and is also expected to robustly detect abnormal tissue classes. The classification process is demonstrated using a three dimensional data set of MRI scans of a human brain tumor.

  19. Rapid mapping of digital integrated circuit logic gates via multi-spectral backside imaging

    CERN Document Server

    Adato, Ronen; Zangeneh, Mahmoud; Zhou, Boyou; Joshi, Ajay; Goldberg, Bennett; Unlu, M Selim

    2016-01-01

    Modern semiconductor integrated circuits are increasingly fabricated at untrusted third party foundries. There now exist myriad security threats of malicious tampering at the hardware level and hence a clear and pressing need for new tools that enable rapid, robust and low-cost validation of circuit layouts. Optical backside imaging offers an attractive platform, but its limited resolution and throughput cannot cope with the nanoscale sizes of modern circuitry and the need to image over a large area. We propose and demonstrate a multi-spectral imaging approach to overcome these obstacles by identifying key circuit elements on the basis of their spectral response. This obviates the need to directly image the nanoscale components that define them, thereby relaxing resolution and spatial sampling requirements by 1 and 2 - 4 orders of magnitude respectively. Our results directly address critical security needs in the integrated circuit supply chain and highlight the potential of spectroscopic techniques to addres...

  20. An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chenghai Yang

    2014-06-01

    Full Text Available This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

  1. Simulation of multispectral x-ray imaging scenarios by Wien shift optical spectroscopy

    Science.gov (United States)

    Brydegaard, M.; Svanberg, S.

    2010-02-01

    The acquisition of multispectral x-ray images and the treatment of such data are essential for understanding many devices that we encounter in everyday life. Examples include computerized tomography in hospitals and scanners at airports. X-ray devices remain impractical for undergraduate laboratories because of their considerable cost and the risk of exposure to ionizing radiation. One way to acquire spectral information and thus constituent-discriminating data in x-ray imaging is to alter the spectral contents of the illuminating x-ray source, which can be achieved by changing the x-ray tube voltage and thus energetically displacing the bremsstrahlung. A similar effect occurs in the emission from a black-body radiator in the optical and infrared regions when altering the temperature. We illustrate how to simulate the x-ray scenario with a webcam and an ordinary light bulb. Insight into how chemical and physical information regarding objects can be obtained in multispectral imaging supported by multivariate analysis is gained.

  2. A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, Michael Adsetts Edberg; Frisvad, Jens Christian

    2007-01-01

    We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we pr...... to macro-morphological features. The species have been classified using only 3–4 of the spectral bands with a 100% correct classification rate using both leave-one-out cross-validation and test set validation....... propose the use of multi-spectral imaging as a means of objective identification. Three species of the fungal genus Penicillium are subject to classification. To obtain an objective classification we use multi-spectral images. Previously, RGB images have proven useful for the purpose. We use multi-spectral...

  3. Assessment of the fused image of multispectral and panchromatic images of SPOT5 in the investigation of geological hazards

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The investigated area in this paper is located on the northern mountain in Guangzhou City.It is characterized by high relief and inaccessibility.Multispectral and pan Images of SPOT5 were used as the remote sensing data source,and high-pass filtering(HPF),Brovery transform(BT),intensity-hue-saturation(IHS),principal component analysis(PCA) and the modified IHS(MIHS) methods were adopted for image fusion.Here,a comparison has been made between the entire fused images and the original multispectral images.Subjective evaluation and objective evaluation(entropy,average gradient,correlation coefficient,distribution of gray) have been adopted to assess the quality of the fused images.Also regional geological survey has been taken to find the interpretation veracity.Results show that the MIHS is the best image fusion method for geological hazards interpretation,and the fused image can provide abundant textural and spectral information for easy interpretation of such geological hazards as collapse,landslip,and debris flow.

  4. Investigation of Image Fusion Between High-Resolution Image and Multi-spectral Image

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; WANG Zhijun

    2003-01-01

    On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China. The experimental results show that a perfect image fusion can be built up by using the image analytical solution and re-construction in the image frequency domain based on the physical characteristics of the image formation. The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.

  5. Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

    Science.gov (United States)

    Nag, Sreeja; Hewagama, Tilak; Georgiev, Georgi; Pasquale, Bert; Aslam, Shahid; Gatebe, Charles K.

    2017-01-01

    Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

  6. Interest Point Detection for Multispectral Remote Sensing Image Using Phase Congruency in Illumination Space

    Directory of Open Access Journals (Sweden)

    CHEN Min

    2016-02-01

    Full Text Available A robust interest point detection algorithm based on illumination space and phase congruency is proposed in this paper. Firstly, image illumination space is constructed by using a parameters adaptive method. Secondly, a phase congruency based interest point detection algorithm is adopted to compute candidate points in illumination space. Then, all interest point candidates are mapped back to the original image and a non-maximum suppression step is added to find final interest points. Finally, the feature scale values of all interest points are calculated based on the Laplacian function. The proposed algorithm combines the advantages of illumination space and phase congruency, which makes the proposed method robust to the radiation variation of multispectral images. The experimental results show that the proposed method performs better than other traditional methods in feature repeatability rate and repeated features number.

  7. An approach to optimal hyperspectral and multispectral signature and image fusion for detecting hidden targets on shorelines

    Science.gov (United States)

    Bostater, Charles R.

    2015-10-01

    Hyperspectral and multispectral imagery of shorelines collected from airborne and shipborne platforms are used following pushbroom imagery corrections using inertial motion motions units and augmented global positioning data and Kalman filtering. Corrected radiance or reflectance images are then used to optimize synthetic high spatial resolution spectral signatures resulting from an optimized data fusion process. The process demonstrated utilizes littoral zone features from imagery acquired in the Gulf of Mexico region. Shoreline imagery along the Banana River, Florida, is presented that utilizes a technique that makes use of numerically embedded targets in both higher spatial resolution multispectral images and lower spatial resolution hyperspectral imagery. The fusion process developed utilizes optimization procedures that include random selection of regions and pixels in the imagery, and minimizing the difference between the synthetic signatures and observed signatures. The optimized data fusion approach allows detection of spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using numerically embedded line targets within actual imagery. The approach allows one to test spectral signature anomaly detection and to identify features and targets. The optimized data fusion techniques and software allows one to perform sensitivity analysis and optimization in the singular value decomposition model building process and the 2-D Butterworth cutoff frequency and order numerical selection process. The data fusion "synthetic imagery" forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within "spectral anomaly areas". Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K

  8. Multivariate alteration detection (MAD) in multispectral, bi-temporal image data: A new approach to change detction studies

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut

    for the definition of the MAD transformation is proven. As opposed to traditional univariate change detection schemes our scheme transforms two sets of multivariate observations (e.g. two multispectral satellite images covering the same geographical area acquired at different points in time) into a difference......-processing introduces a new spatial element into our change detection scheme which is highly relevant for image data. Two case studies using multispectral SPOT HRV data from 5 February 1987 and 12 February 1989 covering coffee and pineapple plantations in central Kenya, and Landsat TM data from 6 June 1986 and 27 June...

  9. Multispectral imaging of the ocular fundus using light emitting diode illumination.

    Science.gov (United States)

    Everdell, N L; Styles, I B; Calcagni, A; Gibson, J; Hebden, J; Claridge, E

    2010-09-01

    We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.

  10. Multispectral texture characterization: application to computer aided diagnosis on prostatic tissue images

    Science.gov (United States)

    Khelifi, Riad; Adel, Mouloud; Bourennane, Salah

    2012-12-01

    Various approaches have been proposed in the literature for texture characterization of images. Some of them are based on statistical properties, others on fractal measures and some more on multi-resolution analysis. Basically, these approaches have been applied on mono-band images. However, most of them have been extended by including the additional information between spectral bands to deal with multi-band texture images. In this article, we investigate the problem of texture characterization for multi-band images. Therefore, we aim to add spectral information to classical texture analysis methods that only treat gray-level spatial variations. To achieve this goal, we propose a spatial and spectral gray level dependence method (SSGLDM) in order to extend the concept of gray level co-occurrence matrix (GLCM) by assuming the presence of texture joint information between spectral bands. Thus, we propose new multi-dimensional functions for estimating the second-order joint conditional probability density of spectral vectors. Theses functions can be represented in structure form which can help us to compute the occurrences while keeping the corresponding components of spectral vectors. In addition, new texture features measurements related to (SSGLDM) which define the multi-spectral image properties are proposed. Extensive experiments have been carried out on 624 textured multi-spectral images for use in prostate cancer diagnosis and quantitative results showed the efficiency of this method compared to the GLCM. The results indicate a significant improvement in terms of global accuracy rate. Thus, the proposed approach can provide clinically useful information for discriminating pathological tissue from healthy tissue.

  11. Building keypoint mappings on multispectral images by a cascade of classifiers with a resurrection mechanism.

    Science.gov (United States)

    Li, Yong; Jing, Jing; Jin, Hongbin; Qiao, Wei

    2015-05-21

    Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF), color and intensity distribution of segment (CIDS), global information and the RANSAC process to remove outlier keypoint matchings. Initial keypoint mappings are built with the descriptors associated with keypoints; then, at each step, only a small number of keypoint mappings of a high confidence are classified to be incorrect. The unclassified keypoint mappings will be passed on to subsequent steps for determining whether they are correct. Due to the drawback of a classification rule, some correct keypoint mappings may be misclassified as incorrect at a step. Observing this, we design a resurrection mechanism, so that they will be reconsidered and evaluated by the rules utilized in subsequent steps. Experimental results show that the proposed cascade structure combined with the resurrection mechanism can effectively build more reliable keypoint mappings on multispectral images than existing methods.

  12. Galileo multispectral imaging of the north polar and eastern limb regions of the moon

    Science.gov (United States)

    Belton, M.J.S.; Greeley, R.; Greenberg, R.; McEwen, A.; Klaasen, K.P.; Head, J. W.; Pieters, C.; Neukum, G.; Chapman, C.R.; Geissler, P.; Heffernan, C.; Breneman, H.; Anger, C.; Carr, M.H.; Davies, M.E.; Fanale, F.P.; Gierasch, P.J.; Ingersoll, A.P.; Johnson, T.V.; Pilcher, C.B.; Thompson, W.R.; Veverka, J.; Sagan, C.

    1994-01-01

    Multispectral images obtained during the Galileo probe's second encounter with the moon reveal the compositional nature of the north polar regions and the northeastern limb. Mare deposits in these regions are found to be primarily low to medium titanium lavas and, as on the western limb, show only slight spectral heterogeneity. The northern light plains are found to have the spectral characteristics of highlands materials, show little evidence for the presence of cryptomaria, and were most likely emplaced by impact processes regardless of their age.Multispectral images obtained during the Galileo probe's second encounter with the moon reveal the compositional nature of the north polar regions and the northeastern limb. Mare deposits in these regions are found to be primarily low to medium titanium lavas and, as on the western limb, show only slight spectral heterogeneity. The northern light plains are found to have the spectral characteristics of highlands materials, show little evidence for the presence of cryptomaria, and were most likely emplaced by impact processes regardless of their age.

  13. Building Keypoint Mappings on Multispectral Images by a Cascade of Classifiers with a Resurrection Mechanism

    Directory of Open Access Journals (Sweden)

    Yong Li

    2015-05-01

    Full Text Available Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF, color and intensity distribution of segment (CIDS, global information and the RANSAC process to remove outlier keypoint matchings. Initial keypoint mappings are built with the descriptors associated with keypoints; then, at each step, only a small number of keypoint mappings of a high confidence are classified to be incorrect. The unclassified keypoint mappings will be passed on to subsequent steps for determining whether they are correct. Due to the drawback of a classification rule, some correct keypoint mappings may be misclassified as incorrect at a step. Observing this, we design a resurrection mechanism, so that they will be reconsidered and evaluated by the rules utilized in subsequent steps. Experimental results show that the proposed cascade structure combined with the resurrection mechanism can effectively build more reliable keypoint mappings on multispectral images than existing methods.

  14. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  15. Aerosol optical thickness of Mt. Etna volcanic plume retrieved by means of the Airborne Multispectral Imaging Spectrometer (MIVIS

    Directory of Open Access Journals (Sweden)

    L. Merucci

    2003-06-01

    Full Text Available Within the framework of the European MVRRS project (Mitigation of Volcanic Risk by Remote Sensing Techniques, in June 1997 an airborne campaign was organised on Mt. Etna to study different characteristics of the volcanic plume emitted by the summit craters in quiescent conditions. Digital images were collected with the Airborne Multispectral Imaging Spectrometer (MIVIS, together with ground-based measurements. MIVIS images were used to calculate the aerosol optical thickness of the volcanic plume. For this purpose, an inversion algorithm was developed based on radiative transfer equations and applied to the upwelling radiance data measured by the sensor. This article presents the preliminary results from this inversion method. One image was selected following the criteria of concomitant atmospheric ground-based measurements necessary to model the atmosphere, plume centrality in the scene to analyse the largest plume area and cloudless conditions. The selected image was calibrated in radiance and geometrically corrected. The 6S (Second Simulation of the Satellite Signal in the Solar Spectrum radiative transfer model was used to invert the radiative transfer equation and derive the aerosol optical thickness. The inversion procedure takes into account both the spectral albedo of the surface under the plume and the topographic effects on the refl ected radiance, due to the surface orientation and elevation. The result of the inversion procedure is the spatial distribution of the plume optical depth. An average value of 0.1 in the wavelength range 454-474 nm was found for the selected measurement day.

  16. Multispectral Thermal Imager Optical Assembly Performance and Intergration of the Flight Focal Plane Assembly

    Energy Technology Data Exchange (ETDEWEB)

    Blake, Dick; Byrd, Don; Christensen, Wynn; Henson, Tammy; Krumel, Les; Rappoport, William; Shen, Gon-Yen

    1999-06-08

    The Multispectral Thermal Imager Optical Assembly (OA) has been fabricated, assembled, successfully performance tested, and integrated into the flight payload structure with the flight Focal Plane Assembly (FPA) integrated and aligned to it. This represents a major milestone achieved towards completion of this earth observing E-O imaging sensor that is to be operated in low earth orbit. The OA consists of an off-axis three mirror anastigmatic (TMA) telescope with a 36 cm unobscured clear aperture, a wide-field-of-view (WFOV) of 1.82° along the direction of spacecraft motion and 1.38° across the direction of spacecraft motion. It also contains a comprehensive on-board radiometric calibration system. The OA is part of a multispectral pushbroom imaging sensor which employs a single mechanically cooled focal plane with 15 spectral bands covering a wavelength range from 0.45 to 10.7 µm. The OA achieves near diffraction-limited performance from visible to the long-wave infrared (LWIR) wavelengths. The two major design drivers for the OA are 80% enpixeled energy in the visible bands and radiometric stability. Enpixeled energy in the visible bands also drove the alignment of the FPA detectors to the OA image plane to a requirement of less than ± 20 µm over the entire visible detector field of view (FOV). Radiometric stability requirements mandated a cold Lyot stop for stray light rejection and thermal background reduction. The Lyot stop is part of the FPA assembly and acts as the aperture stop for the imaging system. The alignment of the Lyot stop to the OA drove the centering and to some extent the tilt alignment requirements of the FPA to the OA.

  17. Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

    Science.gov (United States)

    Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

    2017-01-01

    The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

  18. Potential of multispectral imaging for real-time determination of colour change and moisture distribution in carrot slices during hot air dehydration.

    Science.gov (United States)

    Liu, Changhong; Liu, Wei; Lu, Xuzhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

    2016-03-15

    Colour and moisture content are important indices in quality monitoring of dehydrating carrot slices during dehydration process. This study investigated the potential of using multispectral imaging for real-time and non-destructive determination of colour change and moisture distribution during the hot air dehydration of carrot slices. Multispectral reflectance images, ranging from 405 to 970 nm, were acquired and then calibrated based on three chemometrics models of partial least squares (PLS), least squares-support vector machines (LS-SVM), and back propagation neural network (BPNN), respectively. Compared with PLS and LS-SVM, BPNN considerably improved the prediction performance with coefficient of determination in prediction (RP(2))=0.991, root-mean-square error of prediction (RMSEP)=1.482% and residual predictive deviation (RPD)=11.378 for moisture content. It was concluded that multispectral imaging has an excellent potential for rapid, non-destructive and simultaneous determination of colour change and moisture distribution of carrot slices during dehydration.

  19. Development of a mobile multispectral imaging platform for precise field phenotyping

    DEFF Research Database (Denmark)

    Svensgaard, Jesper; Roitsch, Thomas Georg; Christensen, Svend

    2014-01-01

    Abstract: Phenotyping in field experiments is challenging due to interactions between plants and effects from biotic and abiotic factors which increase complexity in plant development. In such environments, visual or destructive measurements are considered the limiting factor and novel approaches...... are necessary. Remote multispectral imaging is a powerful method that has shown significant potential to estimate crop physiology. However, precise measurements of phenotypic differences between crop varieties in field experiments require exclusion of the disturbances caused by wind and varying sunlight...... potentials for differentiating between the varieties using both vegetation coverage and NDVI, especially at the early growth stages. The perspectives of high-precision and high-throughput imaging for field phenotyping are discussed including the potentials of measuring varietal differences via spectral...

  20. A Combined Texture-principal Component Image Classification Technique For Landslide Identification Using Airborne Multispectral Imagery

    Science.gov (United States)

    Whitworth, M.; Giles, D.; Murphy, W.

    The Jurassic strata of the Cotswolds escarpment of southern central United Kingdom are associated with extensive mass movement activity, including mudslide systems, rotational and translational landslides. These mass movements can pose a significant engineering risk and have been the focus of research into the use of remote sensing techniques as a tool for landslide identification and delineation on clay slopes. The study has utilised a field site on the Cotswold escarpment above the village of Broad- way, Worcestershire, UK. Geomorphological investigation was initially undertaken at the site in order to establish ground control on landslides and other landforms present at the site. Subsequent to this, Airborne Thematic Mapper (ATM) imagery and colour stereo photography were acquired by the UK Natural Environment Research Coun- cil (NERC) for further analysis and interpretation. This paper describes the textu- ral enhancement of the airborne imagery undertaken using both mean euclidean dis- tance (MEUC) and grey level co-occurrence matrix entropy (GLCM) together with a combined texture-principal component based supervised image classification that was adopted as the method for landslide identification. The study highlights the importance of image texture for discriminating mass movements within multispectral imagery and demonstrates that by adopting a combined texture-principal component image classi- fication we have been able to achieve classification accuracy of 84 % with a Kappa statistic of 0.838 for landslide classes. This paper also highlights the potential prob- lems that can be encountered when using high-resolution multispectral imagery, such as the presence of dense variable woodland present within the image, and presents a solution using principal component analysis.

  1. Blind source separation of ex-vivo aorta tissue multispectral images.

    Science.gov (United States)

    Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

    2015-05-01

    Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method's performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue.

  2. 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.

  3. A novel method for non-destructive determination of hair photo-induced damage based on multispectral imaging technology.

    Science.gov (United States)

    Cao, Yue; Qu, Hao; Xiong, Can; Liu, Changhong; Zheng, Lei

    2017-03-31

    Extended exposure to sunlight may give rise to chemical and physical damages of human hairs. In this work, we report a novel method for non-destructive quantification of hair photodamage via multispectral imaging (MSI) technology. We show that the multispectral reflectance value in near-infrared region has a strong correlation with hair photodamage. More specifically, the hair segments with longer growing time and the same hair root segment after continuous ultraviolet (UV) irradiation displaying more severe photodamage observed via scanning electron microscopy (SEM) micrographs showed significantly higher multispectral reflectance value. Besides, the multispectral reflectance value of hair segments with different growing time was precisely reproduced by exposing the same hair root segment to specific durations of UV irradiation, suggesting that MSI can be adequately applied to determine the sunlight exposure time of the hair. The loss of cystine content of photodamaged hairs was identified to be the main factor that physiologically contributed to the morphological changes of hair surface fibers and hence the variation of their multispectral reflectance spectra. Considering the environmental information recording nature of hairs, we believe that MSI for non-destructive evaluation of hair photodamage would prove valuable for assessing sunlight exposure time of a subject in the biomedical fields.

  4. Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory

    Science.gov (United States)

    Anderson, Ryan B.; Bell, James F.

    2013-01-01

    In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red–blue ratio (673 nm/434 nm) and Fe3+-bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400–1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes. This work shows

  5. Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour

    Directory of Open Access Journals (Sweden)

    Puneet Mishra

    2015-06-01

    Full Text Available In current industrial environments there is an increasing need for practical and inexpensive quality control systems to detect the foreign food materials in powder food processing lines. This demand is especially important for the detection of product adulteration with traces of highly allergenic products, such as peanuts and tree nuts. Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with traces of tree nuts and other adulterants, which might result in unintentional ingestion of nuts by the sensitised population. Hence, the need for an in-line system to detect nut traces at the early stages of food manufacturing is of crucial importance. In this present work, a feasibility study of a spectral index for revealing adulteration of tree nut and peanut traces in wheat flour samples with hyperspectral images is reported. The main nuts responsible for allergenic reactions considered in this work were peanut, hazelnut and walnut. Enhanced contrast between nuts and wheat flour was obtained after the application of the index. Furthermore, the segmentation of these images by selecting different thresholds for different nut and flour mixtures allowed the identification of nut traces in the samples. Pixels identified as nuts were counted and compared with the actual percentage of peanut adulteration. As a result, the multispectral system was able to detect and provide good visualisation of tree nut and peanut trace levels down to 0.01% by weight. In this context, multispectral imaging could operate in conjuction with chemical procedures, such as Real Time Polymerase Chain Reaction and Enzyme-Linked Immunosorbent Assay to save time, money and skilled labour on product quality control. This approach could enable not only a few selected samples to be assessed but also to extensively incorporate quality control surveyance on product processing lines.

  6. Multispectral imaging reveals the tissue distribution of tetraspanins in human lymphoid organs.

    Science.gov (United States)

    de Winde, Charlotte M; Zuidscherwoude, Malou; Vasaturo, Angela; van der Schaaf, Alie; Figdor, Carl G; van Spriel, Annemiek B

    2015-08-01

    Multispectral imaging is a novel microscopy technique that combines imaging with spectroscopy to obtain both quantitative expression data and tissue distribution of different cellular markers. Tetraspanins CD37 and CD53 are four-transmembrane proteins involved in cellular and humoral immune responses. However, comprehensive immunohistochemical analyses of CD37 and CD53 in human lymphoid organs have not been performed so far. We investigated CD37 and CD53 protein expression on primary human immune cell subsets in blood and in primary and secondary lymphoid organs. Both tetraspanins were prominently expressed on antigen-presenting cells, with highest expression of CD37 on B lymphocytes. Analysis of subcellular distribution showed presence of both tetraspanins on the plasma membrane and on endosomes. In addition, CD53 was also present on lysosomes. Quantitative analysis of expression and localization of CD37 and CD53 on lymphocytes within lymphoid tissues by multispectral imaging revealed high expression of both tetraspanins on CD20(+) cells in B cell follicles in human spleen and appendix. CD3(+) T cells within splenic T cell zones expressed lower levels of CD37 and CD53 compared to T cells in the red pulp of human spleen. B cells in human bone marrow highly expressed CD37, whereas the expression of CD53 was low. In conclusion, we demonstrate differential expression of CD37 and CD53 on primary human immune cells, their subcellular localization and their quantitative distribution in human lymphoid organs. This study provides a solid basis for better insight into the function of tetraspanins in the human immune response.

  7. Evaluation of port-wine stain treatment outcomes using multispectral imaging

    Science.gov (United States)

    Samatham, Ravikant; Choudhury, Niloy; Krol, Alfons L.; Jacques, Steven L.

    2012-02-01

    Port-wine Stain (PWS) is a vascular malformation characterized by ectasia of superficial dermal capillaries. The flash-lamp pumped pulsed dye laser (PDL) treatment has been the mainstay of PWS for the last decade. Despite the success of the PDL in significantly fading the PWS, the overall cure rate is less than 10%. The precise efficacy of an individual PDL treatment is hard to evaluate and the treatment outcome is measured by visual observation of clinical fading. A hand-held multi-spectral imaging system was developed to image PWS before and after PDL treatment. In an NIH-funded pilot study multi-spectral camera was used to image PWS in children (2- 17 years). Oxygen saturation (S) and blood content (B) of PWS before and after the treatment was determined by analysis of the reflectance spectra. The outcome of the treatment was evaluated during follow up visits of the patients. One of the major causes of failure of laser therapy of port-wine stains (PWS) is reperfusion of the lesion after laser treatment. Oxygen saturation and blood content maps of PWS before and after treatment can predict regions of reperfusion and subsequent failure of the treatment. The ability to measure reperfusion and to predict lesions or areas susceptible to reperfusion, will help in selection of patients/lesions for laser treatment and help to optimize laser dosimetry for maximum effect. The current studies also should provide a basis for monitoring of future alternative therapies or enhancers of laser treatment in resistant cases.

  8. Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

    Science.gov (United States)

    Liebel, L.; Körner, M.

    2016-06-01

    In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

  9. A contiguity-enhanced k-means clustering algorithm for unsupervised multispectral image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Theiler, J.; Gisler, G.

    1997-07-01

    The recent and continuing construction of multi and hyper spectral imagers will provide detailed data cubes with information in both the spatial and spectral domain. This data shows great promise for remote sensing applications ranging from environmental and agricultural to national security interests. The reduction of this voluminous data to useful intermediate forms is necessary both for downlinking all those bits and for interpreting them. Smart onboard hardware is required, as well as sophisticated earth bound processing. A segmented image (in which the multispectral data in each pixel is classified into one of a small number of categories) is one kind of intermediate form which provides some measure of data compression. Traditional image segmentation algorithms treat pixels independently and cluster the pixels according only to their spectral information. This neglects the implicit spatial information that is available in the image. We will suggest a simple approach; a variant of the standard k-means algorithm which uses both spatial and spectral properties of the image. The segmented image has the property that pixels which are spatially contiguous are more likely to be in the same class than are random pairs of pixels. This property naturally comes at some cost in terms of the compactness of the clusters in the spectral domain, but we have found that the spatial contiguity and spectral compactness properties are nearly orthogonal, which means that we can make considerable improvements in the one with minimal loss in the other.

  10. Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

    Science.gov (United States)

    Park, Chulhee; Kang, Moon Gi

    2016-05-18

    A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

  11. Noninvasive in vivo multispectral optoacoustic imaging of apoptosis in triple negative breast cancer using indocyanine green conjugated phosphatidylserine monoclonal antibody

    Science.gov (United States)

    Kannadorai, Ravi Kumar; Udumala, Sunil Kumar; Sidney, Yu Wing Kwong

    2016-12-01

    Noninvasive and nonradioactive imaging modality to track and image apoptosis during chemotherapy of triple negative breast cancer is much needed for an effective treatment plan. Phosphatidylserine (PS) is a biomarker transiently exposed on the outer surface of the cells during apoptosis. Its externalization occurs within a few hours of an apoptotic stimulus by a chemotherapy drug and leads to presentation of millions of phospholipid molecules per apoptotic cell on the cell surface. This makes PS an abundant and accessible target for apoptosis imaging. In the current work, we show that PS monoclonal antibody tagged with indocyanine green (ICG) can help to track and image apoptosis using multispectral optoacoustic tomography in vivo. When compared to saline control, the doxorubicin treated group showed a significant increase in uptake of ICG-PS monoclonal antibody in triple negative breast tumor xenografted in NCr nude female mice. Day 5 posttreatment had the highest optoacoustic signal in the tumor region, indicating maximum apoptosis and the tumor subsequently shrank. Since multispectral optoacoustic imaging does not involve the use of radioactivity, the longer the circulatory time of the PS antibody can be exploited to monitor apoptosis over a period of time without multiple injections of commonly used imaging probes such as Tc-99m Annexin V or F-18 ML10. The proposed apoptosis imaging technique involving multispectral optoacoustic tomography, monoclonal antibody, and near-infrared absorbing fluorescent marker can be an effective tool for imaging apoptosis and treatment planning.

  12. Noninvasive in vivo multispectral optoacoustic imaging of apoptosis in triple negative breast cancer using indocyanine green conjugated phosphatidylserine monoclonal antibody.

    Science.gov (United States)

    Kannadorai, Ravi Kumar; Udumala, Sunil Kumar; Sidney, Yu Wing Kwong

    2016-12-01

    Noninvasive and nonradioactive imaging modality to track and image apoptosis during chemotherapy of triple negative breast cancer is much needed for an effective treatment plan. Phosphatidylserine (PS) is a biomarker transiently exposed on the outer surface of the cells during apoptosis. Its externalization occurs within a few hours of an apoptotic stimulus by a chemotherapy drug and leads to presentation of millions of phospholipid molecules per apoptotic cell on the cell surface. This makes PS an abundant and accessible target for apoptosis imaging. In the current work, we show that PS monoclonal antibody tagged with indocyanine green (ICG) can help to track and image apoptosis using multispectral optoacoustic tomography triple negative breast tumor xenografted in NCr nude female mice. Day 5 posttreatment had the highest optoacoustic signal in the tumor region, indicating maximum apoptosis and the tumor subsequently shrank. Since multispectral optoacoustic imaging does not involve the use of radioactivity, the longer the circulatory time of the PS antibody can be exploited to monitor apoptosis over a period of time without multiple injections of commonly used imaging probes such as Tc-99m Annexin V or F-18 ML10. The proposed apoptosis imaging technique involving multispectral optoacoustic tomography, monoclonal antibody, and near-infrared absorbing fluorescent marker can be an effective tool for imaging apoptosis and treatment planning.

  13. MONSTIR II: A 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, Robert J., E-mail: robert.cooper@ucl.ac.uk; Magee, Elliott; Everdell, Nick; Magazov, Salavat; Varela, Marta; Airantzis, Dimitrios; Gibson, Adam P.; Hebden, Jeremy C. [Biomedical Optics Research Laboratory, Department of Medical Physics and Bioengineering, University College London, London WC1E 6BT (United Kingdom)

    2014-05-15

    We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

  14. MONSTIR II: A 32-channel, multispectral, time-resolved optical tomography system for neonatal brain imaging

    Science.gov (United States)

    Cooper, Robert J.; Magee, Elliott; Everdell, Nick; Magazov, Salavat; Varela, Marta; Airantzis, Dimitrios; Gibson, Adam P.; Hebden, Jeremy C.

    2014-05-01

    We detail the design, construction and performance of the second generation UCL time-resolved optical tomography system, known as MONSTIR II. Intended primarily for the study of the newborn brain, the system employs 32 source fibres that sequentially transmit picosecond pulses of light at any four wavelengths between 650 and 900 nm. The 32 detector channels each contain an independent photo-multiplier tube and temporally correlated photon-counting electronics that allow the photon transit time between each source and each detector position to be measured with high temporal resolution. The system's response time, temporal stability, cross-talk, and spectral characteristics are reported. The efficacy of MONSTIR II is demonstrated by performing multi-spectral imaging of a simple phantom.

  15. Inferential multi-spectral image compression based on distributed source coding

    Science.gov (United States)

    Wu, Xian-yun; Li, Yun-song; Wu, Cheng-ke; Kong, Fan-qiang

    2008-08-01

    Based on the analyses of the interferential multispectral imagery(IMI), a new compression algorithm based on distributed source coding is proposed. There are apparent push motions between the IMI sequences, the relative shift between two images is detected by the block match algorithm at the encoder. Our algorithm estimates the rate of each bitplane with the estimated side information frame. then our algorithm adopts a ROI coding algorithm, in which the rate-distortion lifting procedure is carried out in rate allocation stage. Using our algorithm, the FBC can be removed from the traditional scheme. The compression algorithm developed in the paper can obtain up to 3dB's gain comparing with JPEG2000 and significantly reduce the complexity and storage consumption comparing with 3D-SPIHT at the cost of slight degrade in PSNR.

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

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

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

  17. Detection of skin erythema in darkly pigmented skin using multispectral images.

    Science.gov (United States)

    Sprigle, Stephen; Zhang, Liwei; Duckworth, Mark

    2009-04-01

    To develop a technique using a fixed, discrete set of wavelengths that can detect erythema in persons with darkly pigmented skin. The resulting erythema detection approach will then be incorporated into a handheld, point-of-care device that is clinically viable and affordable. A multispectral imaging system was used to acquire spectral images of induced erythema. Individual images were combined into a single image using different fusion algorithms. Image fusion algorithms based on published literature and using linear and nonlinear color space transformation were tested to optimize the contrast between erythematic and uninvolved skin. A research laboratory at Georgia Institute of Technology, Atlanta, Georgia. Fifty-six subjects, of whom 28 had darkly pigmented skin, were recruited from a pool of students, faculty, and staff. The ability of detection algorithms to detect erythema was measured using Weber contrast. A simple threshold classifier determined accuracy, sensitivity, and specificity for each algorithm. Four algorithms enhanced contrast of erythema by an order of magnitude over that of a digital photograph. The accuracy of the detection algorithms ranged from 66% to 95%. Sensitivity and specificity ranged from 0% to 100%. One fusion algorithm exhibited an accuracy of more than 90% and sensitivity and specificity of more than 90%. The results indicate that erythema in different skin tones can be identified using 2 to 3 filters. Increasing accuracy and discrimination will be targeted via use of filters with narrower half-wave bandwidths, more consistent camera lighting, and improved machine vision techniques.

  18. Comparative study of sampling strategies for sparse photon multispectral lidar imaging: towards mosaic filter arrays

    Science.gov (United States)

    Tobin, Rachael; Altmann, Yoann; Ren, Ximing; McCarthy, Aongus; Lamb, Robert A.; McLaughlin, Stephen; Buller, Gerald S.

    2017-09-01

    In this paper, we investigate the recovery of range and spectral profiles associated with remote three-dimensional scenes sensed via single-photon multispectral lidar (MSL). We consider two different spatial/spectral sampling strategies and compare their performance for a similar overall number of detected photons. For a regular spatial grid of pixels, the first strategy consists of sampling all the spatial locations of the grid for each of the L wavelengths. The second strategy is consistent with the use of mosaic filter-based arrays and consists of acquiring only one wavelength (out of L) per spatial location. Despite the reduction of spectral content observed in each location, the second strategy has clear potential advantages for fast multispectral imaging using only a single frame read out. We propose a fully automated computational method, adapted for each of the two sampling strategies in order to recover the target range profile, as well as the reflectivity profiles associated with the different wavelengths. These strategies were also assessed with high ambient background. The performance of the two sampling strategies is illustrated using a single-photon MSL system with L = 4 wavelengths (473, 532, 589 and 640 nm). The results presented demonstrate that although the first strategy usually provides more accurate results, the second strategy does not exhibit a significant performance degradation, particularly for sparse photon data (down to 1 photon per pixel on average). These results suggest a way forward for the integration of single-photon detector arrays with mosaic filters for use in a range of emerging photon-starved two-dimensional and three-dimensional imaging applications.

  19. Design, fabrication and characterization of resonant metamaterial filters for infrared multispectral imaging

    Energy Technology Data Exchange (ETDEWEB)

    Commandré, Mireille, E-mail: mireille.commandre@fresnel.fr [Centrale Marseille, Aix Marseille Université, CNRS, Institut Fresnel, UMR 7249, 13013 Marseille (France); Vial, Benjamin [Centrale Marseille, Aix Marseille Université, CNRS, Institut Fresnel, UMR 7249, 13013 Marseille (France); Silios Technologies, ZI Peynier-Rousset, rue Gaston Imbert Prolongée, 13790 Peynier (France); Tisserand, Stéphane; Roux, Laurent [Silios Technologies, ZI Peynier-Rousset, rue Gaston Imbert Prolongée, 13790 Peynier (France); Dallaporta, Hervé; Bedu, Frédéric [Aix Marseille Université, CNRS, CiNaM, UMR 7325, Campus de Luminy, Case 913, 13288 Marseille Cedex 9 (France); Demésy, Guillaume; Nicolet, André; Zolla, Frédéric [Centrale Marseille, Aix Marseille Université, CNRS, Institut Fresnel, UMR 7249, 13013 Marseille (France)

    2015-10-01

    We present the design of infrared filters for multispectral imaging applications, based on square annular aperture arrays in a thin gold film. These structures function as band pass filters with large bandwidth and high transmission at resonance. A modal analysis based on the Finite Element Method (FEM) is performed to obtain quickly the features of this resonance. The center wavelength can be tuned in the 7–12 μm range while keeping constant the quality factor and maximum transmission by scaling all transverse dimensions of the apertures, which allows to obtain filters with different centering on the same substrate in a single fabrication step. Large area samples have been fabricated on a silicon wafer by electronic lithography. Spectrophotometric measurements are in rather good agreement with numerical predictions. In addition, angle resolved measurements show that the filters are quite tolerant to the incidence angle up to 30° for both polarizations which is consistent with our FEM simulations. Finally, a complete sensitivity analysis allows us to evaluate acceptable opto-geometric tolerances of fabrication and thus to improve reproducibility on large areas. The impact of fabrication defaults (rounded corners, aperture anisotropy, aperture edge roughness, sloping aperture edges) on the filtering performances is analyzed. The simulations of realistic structures allow to explain and reduce the differences between measured and simulated spectra. - Highlights: • A theoretical and experimental study of resonant transmission of aperture arrays • Transmission filters in the infrared range are developed for multispectral imaging. • Impact of fabrication defaults, rounded corners, and aperture anisotropy is analyzed. • The simulations of realistic structures increase agreement measurement/simulation.

  20. Computationally efficient target classification in multispectral image data with Deep Neural Networks

    Science.gov (United States)

    Cavigelli, Lukas; Bernath, Dominic; Magno, Michele; Benini, Luca

    2016-10-01

    Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or transmitted to a central storage site for post-incident examination. The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats. An effective way to overcome these limitations is to build a smart camera that analyzes the data on-site, close to the sensor, and transmits alerts when relevant video sequences are detected. Deep neural networks (DNNs) have come to outperform humans in visual classifications tasks and are also performing exceptionally well on other computer vision tasks. The concept of DNNs and Convolutional Networks (ConvNets) can easily be extended to make use of higher-dimensional input data such as multispectral data. We explore this opportunity in terms of achievable accuracy and required computational effort. To analyze the precision of DNNs for scene labeling in an urban surveillance scenario we have created a dataset with 8 classes obtained in a field experiment. We combine an RGB camera with a 25-channel VIS-NIR snapshot sensor to assess the potential of multispectral image data for target classification. We evaluate several new DNNs, showing that the spectral information fused together with the RGB frames can be used to improve the accuracy of the system or to achieve similar accuracy with a 3x smaller computation effort. We achieve a very high per-pixel accuracy of 99.1%. Even for scarcely occurring, but particularly interesting classes, such as cars, 75% of the pixels are labeled correctly with errors occurring only around the border of the objects. This high accuracy was obtained with a training set of only 30 labeled images, paving the way for fast adaptation to various application scenarios.

  1. Theoretical and Monte Carlo optimization of a stacked three-layer flat-panel x-ray imager for applications in multi-spectral diagnostic medical imaging

    Science.gov (United States)

    Lopez Maurino, Sebastian; Badano, Aldo; Cunningham, Ian A.; Karim, Karim S.

    2016-03-01

    We propose a new design of a stacked three-layer flat-panel x-ray detector for dual-energy (DE) imaging. Each layer consists of its own scintillator of individual thickness and an underlying thin-film-transistor-based flat-panel. Three images are obtained simultaneously in the detector during the same x-ray exposure, thereby eliminating any motion artifacts. The detector operation is two-fold: a conventional radiography image can be obtained by combining all three layers' images, while a DE subtraction image can be obtained from the front and back layers' images, where the middle layer acts as a mid-filter that helps achieve spectral separation. We proceed to optimize the detector parameters for two sample imaging tasks that could particularly benefit from this new detector by obtaining the best possible signal to noise ratio per root entrance exposure using well-established theoretical models adapted to fit our new design. These results are compared to a conventional DE temporal subtraction detector and a single-shot DE subtraction detector with a copper mid-filter, both of which underwent the same theoretical optimization. The findings are then validated using advanced Monte Carlo simulations for all optimized detector setups. Given the performance expected from initial results and the recent decrease in price for digital x-ray detectors, the simplicity of the three-layer stacked imager approach appears promising to usher in a new generation of multi-spectral digital x-ray diagnostics.

  2. Multispectral Mueller polarimetric imaging detecting residual cancer and cancer regression after neoadjuvant treatment for colorectal carcinomas

    Science.gov (United States)

    Pierangelo, Angelo; Manhas, Sandeep; Benali, Abdelali; Fallet, Clément; Totobenazara, Jean-Laurent; Antonelli, Maria-Rosaria; Novikova, Tatiana; Gayet, Brice; De Martino, Antonello; Validire, Pierre

    2013-04-01

    This work is devoted to a first exploration of Mueller polarimetric imaging for the detection of residual cancer after neoadjuvant treatment for the rectum. Three samples of colorectal carcinomas treated by radiochemotherapy together with one untreated sample are analyzed ex vivo before fixation in formalin by using a multispectral Mueller polarimetric imaging system operated from 500 to 700 nm. The Mueller images, analyzed using the Lu-Chipmann decomposition, show negligible diattenuation and retardation. The nonirradiated rectum exhibits a variation of depolarization with cancer evolution stage. At all wavelengths on irradiated samples, the contrast between the footprint of the initial tumor and surrounding healthy tissue is found to be much smaller for complete tumor regression than when a residual tumor is present, even at volume fractions of the order of 5%. This high sensitivity is attributed to the modification of stromal collagen induced by the cancer. The depolarization contrast between treated cancer and healthy tissue is found to increase monotonously with the volume fraction of residual cancer in the red part of the spectrum. Polarimetric imaging is a promising technique for detecting short-time small residual cancers, which is valuable information for pathological diagnosis and patient management by clinicians.

  3. Using Multispectral Analysis in GIS to Model the Potential for Urban Agriculture in Philadelphia

    Science.gov (United States)

    Dmochowski, J. E.; Cooper, W. P.

    2010-12-01

    In the context of growing concerns about the international food system’s dependence on fossil fuels, soil degradation, climate change, and other diverse issues, a number of initiatives have arisen to develop and implement sustainable agricultural practices. Many seeking to reform the food system look to urban agriculture as a means to create localized, sustainable agricultural production, while simultaneously providing a locus for community building, encouraging better nutrition, and promoting the rebirth of depressed urban areas. The actual impact of such system, however, is not well understood, and many critics of urban agriculture regard its implementation as impractical and unrealistic. This project uses multispectral imagery from United States Department of Agriculture’s National Agricultural Imagery Program with a one-meter resolution to quantify the potential for increasing urban agriculture in an effort to create a sustainable food system in Philadelphia. Color infrared images are classified with a minimum distance algorithm in ArcGIS to generate baseline data on vegetative cover in Philadelphia. These data, in addition to mapping on the ground, form the basis of a model of land suitable for conversion to agriculture in Philadelphia, which will help address questions related to potential yields, workforce, and energy requirements. This research will help city planners, entrepreneurs, community leaders, and citizens understand how urban agriculture can contribute to creating a sustainable food system in a major North American city.

  4. 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

  5. Optical assembly of a visible through thermal infrared multispectral imaging system

    Energy Technology Data Exchange (ETDEWEB)

    Henson, T. [Sandia National Labs., Albuquerque, NM (United States); Bender, S.; Byrd, D. [Los Alamos National Labs., NM (United States). NIS Div.; Rappoport, W.; Shen, G.Y. [Raytheon Optical Systems, Inc., Danbury, CT (United States)

    1998-06-01

    The Optical Assembly (OA) for the Multispectral Thermal Imager (MTI) program has been fabricated, assembled, and successfully tested for its performance. It represents a major milestone achieved towards completion of this earth observing E-O imaging sensor that is to be operated in low earth orbit. Along with its wide-field-of-view (WFOV), 1.82{degree} along-track and 1.38{degree} cross-track, and comprehensive on-board calibration system, the pushbroom imaging sensor employs a single mechanically cooled focal plane with 15 spectral bands covering a wavelength range from 0.45 to 10.7 {micro}m. The OA has an off-axis three-mirror anastigmatic (TMA) telescope with a 36-cm unobscured clear aperture. The two key performance criteria, 80% enpixeled energy in the visible and radiometric stability of 1% 1{sigma} in the visible/near-infrared (VNIR) and short wavelength infrared (SWIR), of 1.45% 1{sigma} in the medium wavelength infrared (MWIR), and of 0.53% 1{sigma} long wavelength infrared (LWIR), as well as its low weight (less than 49 kg) and volume constraint (89 cm x 44 cm x 127 cm) drive the overall design configuration of the OA and fabrication requirements.

  6. Assessment of advanced glycated end product accumulation in skin using auto fluorescence multispectral imaging.

    Science.gov (United States)

    Larsson, Marcus; Favilla, Riccardo; Strömberg, Tomas

    2016-04-12

    Several studies have shown that advanced glycation end products (AGE) play a role in both the microvascular and macrovascular complications of diabetes and are closely linked to inflammation and atherosclerosis. AGEs accumulate in skin and can be detected using their auto fluorescence (AF). A significant correlation exists between AGE AF and the levels of AGEs as obtained from skin biopsies. A commercial device, the AGE Reader, has become available to assess skin AF for clinical purposes but, while displaying promising results, it is limited to single-point measurements performed in contact to skin tissue. Furthermore, in vivo imaging of AGE accumulation is virtually unexplored. We proposed a non-invasive, contact-less novel technique for quantifying fluorescent AGE deposits in skin tissue using a multispectral imaging camera setup (MSI) during ultraviolet (UV) exposure. Imaging involved applying a region-of-interest mask, avoiding specular reflections and a simple calibration. Results of a study conducted on 16 subjects with skin types ranging from fair to deeply pigmented skin, showed that AGE measured with MSI in forearm skin was significantly correlated with the AGE reference method (AGE Reader on forearm skin, R=0.68, p=0.005). AGE measured in facial skin was borderline significantly related to AGE Reader on forearm skin (R=0.47, p=0.078). These results support the use of the technique in devices for non-touch measurement of AGE content in either facial or forearm skin tissue over time.

  7. Evaluation of non-invasive multispectral imaging as a tool for measuring the effect of systemic therapy in Kaposi sarcoma.

    Directory of Open Access Journals (Sweden)

    Jana M Kainerstorfer

    Full Text Available Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect.

  8. Charon’s Color: A view from New Horizon Ralph/Multispectral Visible Imaging Camer

    Science.gov (United States)

    Howett, Carly Jacqueline Amy; Olkin, Cathy B.; Grundy, William M.; Parker, Alex H.; Ennico, Kimberly; Stern, Sol Alan; Binzel, Richard P.; Cook, Jason C.; Cruikshank, Dale P.; Dalle Ore, Cristina M.; Earle, Alissa; Jennings, Don E.; Linscott, Ivan; Lunsford, Allen W.; Parker, Joel Wm; Protopapa, Silvia; Reuter, Dennis C.; Singer, Kelsi N.; Spencer, John R.; Tsang, Con C. C.; Verbiscer, Anne J.; Weaver, Hal A.; Young, Leslie A.

    2015-11-01

    The Multispectral Visible Imaging Camera (MVIC; Reuter et al., 2008) is part of Ralph, an instrument on NASA’s New Horizons spacecraft. MVIC is the color ‘eyes’ of New Horizons, observing objects using four bands from blue to infrared wavelengths. MVIC’s images of Charon show it to be an intriguing place, a far cry from the grey heavily cratered world once postulated. Rather Charon is observed to have large surface areas free of craters, and a northern polar region that is much redder than its surroundings. This talk will describe these initial results in more detail, for example is Charon’s redder pole caused by molecules that have escaped Pluto’s atmosphere only to be captured and frozen onto the surface of Charon’s cold polar region, where they have undergone photolysis? Charon’s global geological color variations will also be discussed, to put these results into their wider context. This work was supported by NASA’s New Horizons project.

  9. Wide-field multispectral super-resolution imaging using spin-dependent fluorescence in nanodiamonds.

    Science.gov (United States)

    Chen, Edward H; Gaathon, Ophir; Trusheim, Matthew E; Englund, Dirk

    2013-05-08

    Recent advances in fluorescence microscopy have enabled spatial resolution below the diffraction limit by localizing multiple temporally or spectrally distinguishable fluorophores. Here, we introduce a super-resolution technique that deterministically controls the brightness of uniquely addressable, photostable emitters. We modulate the fluorescence brightness of negatively charged nitrogen-vacancy (NV(-)) centers in nanodiamonds through magnetic resonance techniques. Using a CCD camera, this "deterministic emitter switch microscopy" (DESM) technique enables super-resolution imaging with localization down to 12 nm across a 35 × 35 μm(2) area. DESM is particularly well suited for biological applications such as multispectral particle tracking since fluorescent nanodiamonds are not only cytocompatible but also nonbleaching and bright. We observe fluorescence count rates exceeding 1.5 × 10(6) photons per second from single NV(-) centers at saturation. When combined with emerging NV(-)-based techniques for sensing magnetic and electric fields, DESM opens the door to rapid, super-resolution imaging for tracking and sensing applications in the life and physical sciences.

  10. An object based approach for coastline extraction from Quickbird multispectral images

    Directory of Open Access Journals (Sweden)

    Massimiliano Basile Giannini

    2014-12-01

    Full Text Available Because of the reduced dimensions of pixels, in the last years high resolution satellite images (Quickbird, IKONOS, GeoEye, ….. are considered very important data to extract information for coastline monitoring and engineering opera planning. They can integrate detail topographic maps and aerial photos so to contribute to modifications recognition and coastal dynamics reconstruction. Many studies have been carried out on coastline detection from high resolution satellite images: unsupervised and supervised classification, segmentation, NDVI (Normalized Difference Vegetation Index and NDWI (Normalized Difference Water Index are only some of the methodological aspects that have been already considered and experimented. This paper is aimed to implement an object based approach to extract coastline from Quickbird multispectral imagery. Domitian area near Volturno River mouth in Campania Region (Italy, an interesting zone for its dynamics and evolution, is considered. Object based approach is developed for automatic detection of coastline from Quickbird imagery using the Feature Extraction Workflow implemented in ENVI Zoom software. The resulting vector polyline is performed using the smoothing algorithm named PAEK (Polynomial Approximation with Exponential Kernel.

  11. Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

    Science.gov (United States)

    Krohn, M. Dennis

    1986-01-01

    The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

  12. Target-to-background enhancement in multispectral endoscopy with background autofluorescence mitigation for quantitative molecular imaging

    Science.gov (United States)

    Yang, Chenying; Hou, Vivian W.; Girard, Emily J.; Nelson, Leonard Y.; Seibel, Eric J.

    2014-07-01

    Fluorescence molecular imaging with exogenous probes improves specificity for the detection of diseased tissues by targeting unambiguous molecular signatures. Additionally, increased diagnostic sensitivity is expected with the application of multiple molecular probes. We developed a real-time multispectral fluorescence-reflectance scanning fiber endoscope (SFE) for wide-field molecular imaging of fluorescent dye-labeled molecular probes at nanomolar detection levels. Concurrent multichannel imaging with the wide-field SFE also allows for real-time mitigation of the background autofluorescence (AF) signal, especially when fluorescein, a U.S. Food and Drug Administration approved dye, is used as the target fluorophore. Quantitative tissue AF was measured for the ex vivo porcine esophagus and murine brain tissues across the visible and near-infrared spectra. AF signals were then transferred to the unit of targeted fluorophore concentration to evaluate the SFE detection sensitivity for sodium fluorescein and cyanine. Next, we demonstrated a real-time AF mitigation algorithm on a tissue phantom, which featured molecular probe targeted cells of high-grade dysplasia on a substrate containing AF species. The target-to-background ratio was enhanced by more than one order of magnitude when applying the real-time AF mitigation algorithm. Furthermore, a quantitative estimate of the fluorescein photodegradation (photobleaching) rate was evaluated and shown to be insignificant under the illumination conditions of SFE. In summary, the multichannel laser-based flexible SFE has demonstrated the capability to provide sufficient detection sensitivity, image contrast, and quantitative target intensity information for detecting small precancerous lesions in vivo.

  13. 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.

  14. Introducing a Low-Cost Mini-Uav for - and Multispectral-Imaging

    Science.gov (United States)

    Bendig, J.; Bolten, A.; Bareth, G.

    2012-07-01

    's image covers an area of approx. 50 by 40 m. The sensor's resolution is 160 x 120 pixel and the field of view is 28° (H) x 21° (V). According to the producer, absolute accuracy for temperature is ±1 °C and the thermal sensitivity is >0.1 K. Additionally, the MK-Okto is equipped with Tetracam's Mini MCA. The Mini MCA in our study is a four band multispectral imaging system. Total weight is 700 g and spectral characteristics can be modified by filters between 400 and 1000 nm. In this study, three bands with a width of 10 nm (green: 550 nm, red: 671 nm, NIR1: 800 nm) and one band of 20 nm width (NIR2: 950 nm) have been used. Even so the MK-Okto is able to carry both sensors at the same time, the imaging systems were used separately for this contribution. First results of a combined thermal- and multispectral MK-Okto campaign in 2011 are presented and evaluated for a sugarbeet field experiment examining pathogens and drought stress.

  15. Multispectral Airborne Laser Scanning for Automated Map Updating

    Science.gov (United States)

    Matikainen, Leena; Hyyppä, Juha; Litkey, Paula

    2016-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.

  16. Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission

    Science.gov (United States)

    Mariotto, Isabella; Thenkabail, Prasad S.; Huete, Alfredo; Slonecker, E. Terrence; Platonov, Alexander

    2013-01-01

    Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of λ1 (400–2500 nm) versus λ2 (400–2500 nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742 nm and 1175 nm (HVI742-1175), (ii) 1296 nm and 1054 nm (HVI1296-1054), (iii) 1225 nm and 697 nm (HVI1225-697), and (iv) 702 nm and 1104 nm (HVI702-1104). Among the most frequently occurring HNBs in various crop biophysical models, 74% were located in the 1051–2331 nm spectral range, followed by 10% in the moisture sensitive 970 nm, 6% in the red and red-edge (630–752 nm), and the remaining 10% distributed between blue (400–500 nm), green (501–600 nm), and NIR (760–900 nm). Discriminant models, used for discriminating 3 or 4 or 5 crop types, showed significantly higher accuracies

  17. High Fidelity Multi-Mode Hyperspectral Multispectral Imager with Programmable Spectral Resolution Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase II proposal introduces a fast multi-mode hyperspectral-multispectral (MM-HS-MS) sensor with programmable spectral resolution. The sensor brings the...

  18. An investigation of multispectral imaging for the mapping of pigments in paintings

    Science.gov (United States)

    Zhao, Yonghui; Berns, Roy S.; Taplin, Lawrence A.; Coddington, James

    2008-02-01

    Compared with colorimetric imaging, multispectral imaging has the advantage of retrieving spectral reflectance factor of each pixel of a painting. Using this spectral information, pigment mapping is concerned with decomposing the spectrum into its constituent pigments and their relative contributions. The output of pigment mapping is a series of spatial concentration maps of the pigments comprising the painting. This approach was used to study Vincent van Gogh's The Starry Night. The artist's palette was approximated using ten oil pigments, selected from a large database of pigments used in oil paintings and a priori analytical research on one of his self portraits, executed during the same time period. The pigment mapping was based on single-constant Kubelka-Munk theory. It was found that the region of blue sky where the stars were located contained, predominantly, ultramarine blue while the swirling sky and region surrounding the moon contained, predominantly, cobalt blue. Emerald green, used in light bluish-green brushstrokes surrounding the moon, was not used to create the dark green in the cypresses. A measurement of lead white from Georges Seurat's La Grande Jatte was used as the white when mapping The Starry Night. The absorption and scattering properties of this white were replaced with a modern dispersion of lead white in linseed oil and used to simulate the painting's appearance before the natural darkening and yellowing of lead white oil paint. Pigment mapping based on spectral imaging was found to be a viable and practical approach for analyzing pigment composition, providing new insight into an artist's working method, the possibility for aiding in restorative inpainting, and lighting design.

  19. Non-invasive detection of aflatoxin-contaminated figs using fluorescence and multispectral imaging.

    Science.gov (United States)

    Kalkan, Habil; Güneş, Ali; Durmuş, Efkan; Kuşçu, Alper

    2014-01-01

    Agricultural products are prone to aflatoxin (AF)-producing moulds (Aspergillus flavus, A. parasiticus) during harvesting, drying, processing and also storage. AF is a mycotoxin that may cause liver cancer when consumed in amounts higher than allowed limits. Figs, like other agricultural products, are mostly affected by AF-producing moulds and these moulds usually produce kojic acid together with AF. Kojic acid is a fluorescent compound and exhibiting bright greenish yellow fluorescence (BGYF) under ultraviolet (UV) light. Using this fluorescence property, fig-processing plants manually select and remove the BGYF+ figs to reduce the AF level of the processed figs. Although manual selection is based on subjective criteria and strongly depends on the expertise level of the workers, it is known as the most effective way of removing AF-contaminated samples. However, during manual selection, workers are exposed to UV radiation and this brings skin health problems. In this study, we individually investigated the figs to measure their fluorescence level, surface mould concentration and AF levels and noted a strong correlation between mould concentration and BGYF and AF, and BGYF and surface. In addition to a pairwise correlation, we proposed a machine-vision and machine-learning approach to detect the AF-contaminated figs using their multispectral images under UV light. The figs were classified in two different approaches considering their surface mould and AF level with error rates of 9.38% and 11.98%, respectively.

  20. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.

    2000-01-03

    Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

  1. Multispectral Enhancement Method to Increase the Visual Differences of Tissue Structures in Stained Histopathology Images

    Directory of Open Access Journals (Sweden)

    Pinky A. Bautista

    2012-01-01

    Full Text Available In this paper we proposed a multispectral enhancement scheme in which the spectral colors of the stained tissue-structure of interest and its background can be independently modified by the user to further improve their visualization and color discrimination. The colors of the background objects are modified by transforming their N-band spectra through an NxN transformation matrix, which is derived by mapping the representative samples of their original spectra to the spectra of their target colors using least mean square method. On the other hand, the color of the tissue structure of interest is modified by modulating the transformed spectra with the sum of the pixel’s spectral residual-errors at specific bands weighted through an NxN weighting matrix; the spectral error is derived by taking the difference between the pixel’s original spectrum and its reconstructed spectrum using the first M dominant principal component vectors in principal component analysis. Promising results were obtained on the visualization of the collagen fiber and the non-collagen tissue structures, e.g., nuclei, cytoplasm and red blood cells (RBC, in a hematoxylin and eosin (H&E stained image.

  2. Design and evaluation of a device for fast multispectral time-resolved fluorescence spectroscopy and imaging.

    Science.gov (United States)

    Yankelevich, Diego R; Ma, Dinglong; Liu, Jing; Sun, Yang; Sun, Yinghua; Bec, Julien; Elson, Daniel S; Marcu, Laura

    2014-03-01

    The application of time-resolved fluorescence spectroscopy (TRFS) to in vivo tissue diagnosis requires a method for fast acquisition of fluorescence decay profiles in multiple spectral bands. This study focusses on development of a clinically compatible fiber-optic based multispectral TRFS (ms-TRFS) system together with validation of its accuracy and precision for fluorescence lifetime measurements. It also presents the expansion of this technique into an imaging spectroscopy method. A tandem array of dichroic beamsplitters and filters was used to record TRFS decay profiles at four distinct spectral bands where biological tissue typically presents fluorescence emission maxima, namely, 390, 452, 542, and 629 nm. Each emission channel was temporally separated by using transmission delays through 200 μm diameter multimode optical fibers of 1, 10, 19, and 28 m lengths. A Laguerre-expansion deconvolution algorithm was used to compensate for modal dispersion inherent to large diameter optical fibers and the finite bandwidth of detectors and digitizers. The system was found to be highly efficient and fast requiring a few nano-Joule of laser pulse energy and time-resolved fluorescence lifetime measurements of low quantum efficiency sub-nanosecond fluorophores.

  3. Self-Trained Supervised Segmentation of Subcortical Brain Structures Using Multispectral Magnetic Resonance Images

    Directory of Open Access Journals (Sweden)

    Michele Larobina

    2015-01-01

    Full Text Available The aim of this paper is investigate the feasibility of automatically training supervised methods, such as k-nearest neighbor (kNN and principal component discriminant analysis (PCDA, and to segment the four subcortical brain structures: caudate, thalamus, pallidum, and putamen. The adoption of supervised classification methods so far has been limited by the need to define a representative training dataset, operation that usually requires the intervention of an operator. In this work the selection of the training data was performed on the subject to be segmented in a fully automated manner by registering probabilistic atlases. Evaluation of automatically trained kNN and PCDA classifiers that combine voxel intensities and spatial coordinates was performed on 20 real datasets selected from two publicly available sources of multispectral magnetic resonance studies. The results demonstrate that atlas-guided training is an effective way to automatically define a representative and reliable training dataset, thus giving supervised methods the chance to successfully segment magnetic resonance brain images without the need for user interaction.

  4. Self-Trained Supervised Segmentation of Subcortical Brain Structures Using Multispectral Magnetic Resonance Images

    Science.gov (United States)

    Larobina, Michele; Murino, Loredana; Cervo, Amedeo; Alfano, Bruno

    2015-01-01

    The aim of this paper is investigate the feasibility of automatically training supervised methods, such as k-nearest neighbor (kNN) and principal component discriminant analysis (PCDA), and to segment the four subcortical brain structures: caudate, thalamus, pallidum, and putamen. The adoption of supervised classification methods so far has been limited by the need to define a representative training dataset, operation that usually requires the intervention of an operator. In this work the selection of the training data was performed on the subject to be segmented in a fully automated manner by registering probabilistic atlases. Evaluation of automatically trained kNN and PCDA classifiers that combine voxel intensities and spatial coordinates was performed on 20 real datasets selected from two publicly available sources of multispectral magnetic resonance studies. The results demonstrate that atlas-guided training is an effective way to automatically define a representative and reliable training dataset, thus giving supervised methods the chance to successfully segment magnetic resonance brain images without the need for user interaction. PMID:26583131

  5. Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging.

    Science.gov (United States)

    Bauman, Tyler M; Ricke, Emily A; Drew, Sally A; Huang, Wei; Ricke, William A

    2016-04-08

    Immunohistochemistry is a commonly used clinical and research lab detection technique for investigating protein expression and localization within tissues. Many semi-quantitative systems have been developed for scoring expression using immunohistochemistry, but inherent subjectivity limits reproducibility and accuracy of results. Furthermore, the investigation of spatially overlapping biomarkers such as nuclear transcription factors is difficult with current immunohistochemistry techniques. We have developed and optimized a system for simultaneous investigation of multiple proteins using high throughput methods of multiplexed immunohistochemistry and multispectral imaging. Multiplexed immunohistochemistry is performed by sequential application of primary antibodies with secondary antibodies conjugated to horseradish peroxidase or alkaline phosphatase. Different chromogens are used to detect each protein of interest. Stained slides are loaded into an automated slide scanner and a protocol is created for automated image acquisition. A spectral library is created by staining a set of slides with a single chromogen on each. A subset of representative stained images are imported into multispectral imaging software and an algorithm for distinguishing tissue type is created by defining tissue compartments on images. Subcellular compartments are segmented by using hematoxylin counterstain and adjusting the intrinsic algorithm. Thresholding is applied to determine positivity and protein co-localization. The final algorithm is then applied to the entire set of tissues. Resulting data allows the user to evaluate protein expression based on tissue type (ex. epithelia vs. stroma) and subcellular compartment (nucleus vs. cytoplasm vs. plasma membrane). Co-localization analysis allows for investigation of double-positive, double-negative, and single-positive cell types. Combining multispectral imaging with multiplexed immunohistochemistry and automated image acquisition is an

  6. SPLASSH: Open source software for camera-based high-speed, multispectral in-vivo optical image acquisition.

    Science.gov (United States)

    Sun, Ryan; Bouchard, Matthew B; Hillman, Elizabeth M C

    2010-08-02

    Camera-based in-vivo optical imaging can provide detailed images of living tissue that reveal structure, function, and disease. High-speed, high resolution imaging can reveal dynamic events such as changes in blood flow and responses to stimulation. Despite these benefits, commercially available scientific cameras rarely include software that is suitable for in-vivo imaging applications, making this highly versatile form of optical imaging challenging and time-consuming to implement. To address this issue, we have developed a novel, open-source software package to control high-speed, multispectral optical imaging systems. The software integrates a number of modular functions through a custom graphical user interface (GUI) and provides extensive control over a wide range of inexpensive IEEE 1394 Firewire cameras. Multispectral illumination can be incorporated through the use of off-the-shelf light emitting diodes which the software synchronizes to image acquisition via a programmed microcontroller, allowing arbitrary high-speed illumination sequences. The complete software suite is available for free download. Here we describe the software's framework and provide details to guide users with development of this and similar software.

  7. Multispectral imaging system based on laser-induced fluorescence for security applications

    Science.gov (United States)

    Caneve, L.; Colao, F.; Del Franco, M.; Palucci, A.; Pistilli, M.; Spizzichino, V.

    2016-10-01

    The development of portable sensors for fast screening of crime scenes is required to reduce the number of evidences useful to be collected, optimizing time and resources. Laser based spectroscopic techniques are good candidates to this scope due to their capability to operate in field, in remote and rapid way. In this work, the prototype of a multispectral imaging LIF (Laser Induced Fluorescence) system able to detect evidence of different materials on large very crowded and confusing areas at distances up to some tens of meters will be presented. Data collected as both 2D fluorescence images and LIF spectra are suitable to the identification and the localization of the materials of interest. A reduced scan time, preserving at the same time the accuracy of the results, has been taken into account as a main requirement in the system design. An excimer laser with high energy and repetition rate coupled to a gated high sensitivity ICCD assures very good performances for this purpose. Effort has been devoted to speed up the data processing. The system has been tested in outdoor and indoor real scenarios and some results will be reported. Evidence of the plastics polypropylene (PP) and polyethilene (PE) and polyester have been identified and their localization on the examined scenes has been highlighted through the data processing. By suitable emission bands, the instrument can be used for the rapid detection of other material classes (i.e. textiles, woods, varnishes). The activities of this work have been supported by the EU-FP7 FORLAB project (Forensic Laboratory for in-situ evidence analysis in a post blast scenario).

  8. Estimation of leaf nitrogen concentration on winter wheat by multispectral imaging

    Science.gov (United States)

    Leemans, Vincent; Marlier, Guillaume; Destain, Marie-France; Dumont, Benjamin; Mercatoris, Benoit

    2017-04-01

    Precision agriculture can be considered as one of the solutions to optimize agricultural practice such as nitrogen fertilization. Nitrogen deficiency is a major limitation to crop production worldwide whereas excess leads to environmental pollution. In this context, some devices were developed as reflectance spot sensors for on-the-go applications to detect leaves nitrogen concentration deduced from chlorophyll concentration. However, such measurements suffer from interferences with the crop growth stage and the water content of plants. The aim of this contribution is to evaluate the nitrogen status in winter wheat by using multispectral imaging. The proposed system is composed of a CMOS camera and a set of filters ranged from 450 nm to 950 nm and mounted on a wheel which moves due to a stepper motor. To avoid the natural irradiance variability, a white reference is used to adjust the integration time. The segmentation of Photosynthetically Active Leaves is performed by using Bayes theorem to extract their mean reflectance. In order to introduce information related to the canopy architecture, i.e. the crop growth stage, textural attributes are also extracted from raw images at different wavelength ranges. Nc was estimated by partial least squares regression (R² = 0.94). The best attribute was homogeneity extracted from the gray level co-occurrence matrix (R² = 0.91). In order to select in limited number of filters, best subset selection was performed. Nc could be estimated by four filters (450 +/- 40 nm, 500 +/- 20 nm, 650 +/- 40 nm, 800 +/- 50 nm) (R² = 0.91).

  9. For geological investigations with airborne thermal infrared multispectral images: Transfer of calibration from laboratory spectrometer to TIMS as alternative for removing atmospheric effects

    Science.gov (United States)

    Edgett, Kenneth S.; Anderson, Donald L.

    1995-01-01

    This paper describes an empirical method to correct TIMS (Thermal Infrared Multispectral Scanner) data for atmospheric effects by transferring calibration from a laboratory thermal emission spectrometer to the TIMS multispectral image. The method does so by comparing the laboratory spectra of samples gathered in the field with TIMS 6-point spectra for pixels at the location of field sampling sites. The transference of calibration also makes it possible to use spectra from the laboratory as endmembers in unmixing studies of TIMS data.

  10. High contrast imaging of reversibly switchable fluorescent proteins via temporally unmixed Multispectral Optoacoustic Tomography (tuMSOT)

    CERN Document Server

    Stiel, Andre C; Jiang, Yuanyuan; Ntziachristos, Vasilis; Razansky, Daniel; Westmeyer, Gil G

    2014-01-01

    Photocontrol of reversibly switchable fluorescent proteins (RSFPs) was used to program optoacoustic signal time courses that were temporally unmixed to increase the proteins contrast-to-noise-ratios (CNRs) in optoacoustic imaging. In this way, two variants of the RSFP Dronpa with very similar optoacoustic spectra could be readily discriminated in the presence of highly absorbing blood. Addition of temporal unmixing to multispectral optoacoustic tomography (tuMSOT) in conjunction with synthetic or genetically controlled photochromic contrast agents and customized photoswitching schedules can increase the performance of multiplexed and high contrast molecular optoacoustic imaging.

  11. Improved tunable filter-based multispectral imaging system for detection of blood stains on construction material substrates

    Science.gov (United States)

    Janchaysang, Suwatwong; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

    2013-06-01

    We present the improved tunable filter based multispectral imaging system for detecting blood stains on construction materials. Based upon the reflectance and Kubelka Munk absorbance spectra stocked from our previous work, we modify the blood discrimination criteria to make the system more efficient by replacing the old criteria which make use of polynomial fitting with new criteria associated with a few wavelengths images. The newly established criteria are tested to be able to detect blood against other stains almost as efficient as the old criteria, while the number of spectral images required for detecting blood stains are reduced significantly from 64 to 9 spectral images. The reduction of required spectral images will reduce the time needed for image capturing and blood detection criteria application with little sacrificing of the specificity and sensitivity of the system.

  12. [Multispectral Radiation Algorithm Based on Emissivity Model Constraints for True Temperature Measurement].

    Science.gov (United States)

    Liang, Mei; Sun, Xiao-gang; Luan, Mei-sheng

    2015-10-01

    Temperature measurement is one of the important factors for ensuring product quality, reducing production cost and ensuring experiment safety in industrial manufacture and scientific experiment. Radiation thermometry is the main method for non-contact temperature measurement. The second measurement (SM) method is one of the common methods in the multispectral radiation thermometry. However, the SM method cannot be applied to on-line data processing. To solve the problems, a rapid inversion method for multispectral radiation true temperature measurement is proposed and constraint conditions of emissivity model are introduced based on the multispectral brightness temperature model. For non-blackbody, it can be drawn that emissivity is an increasing function in the interval if the brightness temperature is an increasing function or a constant function in a range and emissivity satisfies an inequality of emissivity and wavelength in that interval if the brightness temperature is a decreasing function in a range, according to the relationship of brightness temperatures at different wavelengths. The construction of emissivity assumption values is reduced from multiclass to one class and avoiding the unnecessary emissivity construction with emissivity model constraint conditions on the basis of brightness temperature information. Simulation experiments and comparisons for two different temperature points are carried out based on five measured targets with five representative variation trends of real emissivity. decreasing monotonically, increasing monotonically, first decreasing with wavelength and then increasing, first increasing and then decreasing and fluctuating with wavelength randomly. The simulation results show that compared with the SM method, for the same target under the same initial temperature and emissivity search range, the processing speed of the proposed algorithm is increased by 19.16%-43.45% with the same precision and the same calculation results.

  13. Woody-to-total area ratio determination with a multispectral canopy imager.

    Science.gov (United States)

    Zou, Jie; Yan, Guangjian; Zhu, Ling; Zhang, Wuming

    2009-08-01

    Leaf area index (LAI) - defined as one half of the total green leaf area per unit ground surface area - can be determined by direct or indirect methods. Three major sources of errors exist in indirect LAI measurements: within-shoot clumping, beyond-shoot clumping and non-photosynthetic components. The effect of non-photosynthetic components on LAI measurements can be described by the woody-to-total area ratio, alpha; however, no convenient and efficient indirect methods have been developed to estimate alpha, especially the variations in alpha with zenith angle , alpha(theta). We describe the development and use of a multispectral canopy imager (MCI) to estimate alpha and alpha(theta) by considering the effects of non-random distributions of canopy elements and woody components and the overestimation of needle-to-shoot area ratio on woody components. The MCI, which mainly comprises a near-infrared band camera (Fujifilm IS-1), two visible band cameras (Canon 40D), filters and a pan tilt, was developed to measure clumping index, woody-to-total area ratio and geometric parameters of isolated trees. Two typical sampling plots (Plots 1 and 5) chosen from among 16 permanent forest experiment plots were selected for the estimation of alpha and alpha(theta). The non-random distributions of canopy elements and woody components were estimated separately at eight zenith angles (from 0 degrees to 70 degrees in increments of 10 degrees) using MCI images based on the gap size distribution theory. The visible/near-infrared image pairs captured by the MCI were able to discriminate among sky, leaves, cloud and woody components. Based on three methods of estimation, we obtained woody-to-total area ratios of 0.24, 0.19, 0.19 for Plot 1 and 0.23, 0.18, 0.17 for Plot 5. If clumping effects were ignored, alpha values were overestimated by as much as 21% and 24% at Plots 1 and 5, respectively. We demonstrated that alpha(theta) varied with the zenith angle, with variations in the range of

  14. A neural network approach for enhancing information extraction from multispectral image data

    Science.gov (United States)

    Liu, J.; Shao, G.; Zhu, H.; Liu, S.

    2005-01-01

    A back-propagation artificial neural network (ANN) was applied to classify multispectral remote sensing imagery data. The classification procedure included four steps: (i) noisy training that adds minor random variations to the sampling data to make the data more representative and to reduce the training sample size; (ii) iterative or multi-tier classification that reclassifies the unclassified pixels by making a subset of training samples from the original training set, which means the neural model can focus on fewer classes; (iii) spectral channel selection based on neural network weights that can distinguish the relative importance of each channel in the classification process to simplify the ANN model; and (iv) voting rules that adjust the accuracy of classification and produce outputs of different confidence levels. The Purdue Forest, located west of Purdue University, West Lafayette, Indiana, was chosen as the test site. The 1992 Landsat thematic mapper imagery was used as the input data. High-quality airborne photographs of the same Lime period were used for the ground truth. A total of 11 land use and land cover classes were defined, including water, broadleaved forest, coniferous forest, young forest, urban and road, and six types of cropland-grassland. The experiment, indicated that the back-propagation neural network application was satisfactory in distinguishing different land cover types at US Geological Survey levels II-III. The single-tier classification reached an overall accuracy of 85%. and the multi-tier classification an overall accuracy of 95%. For the whole test, region, the final output of this study reached an overall accuracy of 87%. ?? 2005 CASI.

  15. Non-destructive determination of total polyphenols content and classification of storage periods of Iron Buddha tea using multispectral imaging system.

    Science.gov (United States)

    Xiong, Chuanwu; Liu, Changhong; Pan, Wenjuan; Ma, Fei; Xiong, Can; Qi, Li; Chen, Feng; Lu, Xuzhong; Yang, Jianbo; Zheng, Lei

    2015-06-01

    Total polyphenols is a primary quality indicator in tea which is consumed worldwide. The feasibility of using near infrared reflectance (NIR) spectroscopy (800-2500nm) and multispectral imaging (MSI) system (405-970nm) for prediction of total polyphenols contents (TPC) of Iron Buddha tea was investigated in this study. The results revealed that the predictive model by MSI using partial least squares (PLS) analysis for tea leaves was considered to be the best in non-destructive and rapid determination of TPC. Besides, the ability of MSI to classify tea leaves based on storage period (year of 2004, 2007, 2011, 2012 and 2013) was tested and the classification accuracies of 95.0% and 97.5% were achieved using LS-SVM and BPNN models, respectively. These overall results suggested that MSI together with suitable analysis model is a promising technology for rapid and non-destructive determination of TPC and classification of storage periods in tea leaves.

  16. Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes

    DEFF Research Database (Denmark)

    Klukkert, Marten; Wu, Jian X; Rantanen, Jukka

    2016-01-01

    in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process......Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging...... the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using...

  17. Ziyuan-3 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng

    2014-11-01

    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), àtrous Wavelet Transformation (AWT), NonsubSampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human- being subjective interpretation.

  18. Ziyuan-2 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng

    2014-11-01

    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), à trous Wavelet Transformation (AWT), Nonsub Sampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human-being subjective interpretation.

  19. Image multispectral sensing: a new and innovative instrument for hyperspectral imaging using dispersive techniques

    Science.gov (United States)

    Hinnrichs, Michele; Massie, Mark A.

    1995-06-01

    IMSS utilizes a very simple optical design that enables a robust and low cost hyperspectral imaging instrument. This technology was developed under a phase II SBIR with the Air Force Philips Lab. (Dr. Paul LeVan), for the midwave IR to perform clutter rejection and target identification based upon IR spectral signatures. The prototype instrument has been field tested on numerous occasions and successfully measured background, aircraft, and misile plume spectra. PAT currently has several contracts to commercialize this technology both for the DoD and the commercial market. Under contract to the BMDO, (Paul McCarley), with matching funds from Amber Engineering, we are developing an F/2.3 system that will be sold by Amber Engineering as an accessory to the Radiance 1 camera. PAT is also under contract with ONR (Mr. Jim Buss), to develop a longwave IR version of IMSS as well as an MWIR version tuned to operate as a 'little sister sensor for target identification' for the Navy's IRST's. The purpose of this paper is to briefly describe the hyperspectral image data that was collected in the field at Long Jump '94, and Santa Ynez Peak using IMSS prototype hyperspectral imager. Examples of spectral images, as well as spectra of different aircraft at various ranges, power settings, and aspect angles, an Atlas liquid hydrocarbon burning missile, and a solid beester. All data presented in this paper are a result of a single spectral scan. The limitation in digital storage of the prototype system do not allow multiple scans in order to improve signal to noise. In spite of this limitation, the performance of the prototype system has proven to be excellent.

  20. A new prostate segmentation approach using multispectral magnetic resonance imaging and a statistical pattern classifier

    NARCIS (Netherlands)

    Maan, Bianca; van der Heijden, Ferdinand; Fütterer, Jurgen J.

    2012-01-01

    Prostate segmentation is essential for calculating prostate volume, creating patient-specific prostate anatomical models and image fusion. Automatic segmentation methods are preferable because manual segmentation is timeconsuming and highly subjective. Most of the currently available segmentation

  1. Dialectical multispectral classification of diffusion-weighted magnetic resonance images as an alternative to apparent diffusion coefficients maps to perform anatomical analysis.

    Science.gov (United States)

    Santos, W P; Assis, F M; Souza, R E; Santos Filho, P B; Lima Neto, F B

    2009-09-01

    Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, multispectral images are composed of diffusion-weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.

  2. Development of a technique based on multi-spectral imaging for monitoring the conservation of cultural heritage objects.

    Science.gov (United States)

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-11-14

    A new approach for monitoring the state of conservation of cultural heritage objects surfaces is being developed. The technique utilizes multi-spectral imaging, multivariate analysis and statistical process control theory for the automatic detection of a possible deterioration process, its localization and identification, and the wavelengths most sensitive to detecting this before the human eye can detect the damage or potential degradation changes occur. A series of virtual degradation analyses were performed on images of parchment in order to test the proposed algorithm in controlled conditions. The spectral image of a Dead Sea Scroll (DSS) parchment, IAA (Israel Antiquities Authority) inventory plate # 279, 4Q501 Apocryphal Lamentations B, taken during the 2008 Pilot of the DSS Digitization Project, was chosen for the simulation.

  3. The role of multispectral scanners as data sources for EPA hydrologic models

    Science.gov (United States)

    Slack, R.; Hill, D.

    1982-01-01

    An estimated cost savings of 30% to 50% was realized from using LANDSAT-derived data as input into a program which simulates hydrologic and water quality processes in natural and man-made water systems. Data from the satellite were used in conjunction with EPA's 11-channel multispectral scanner to obtain maps for characterizing the distribution of turbidity plumes in Flathead Lake and to predict the effect of increasing urbanization in Montana's Flathead River Basin on the lake's trophic state. Multispectral data are also being studied as a possible source of the parameters needed to model the buffering capability of lakes in an effort to evaluate the effect of acid rain in the Adirondacks. Water quality in Lake Champlain, Vermont is being classified using data from the LANDSAT and the EPA MSS. Both contact-sensed and MSS data are being used with multivariate statistical analysis to classify the trophic status of 145 lakes in Illinois and to identify water sampling sites in Appalachicola Bay where contaminants threaten Florida's shellfish.

  4. Automated registration of multispectral MR vessel wall images of the carotid artery

    Energy Technology Data Exchange (ETDEWEB)

    Klooster, R. van ' t; Staring, M.; Reiber, J. H. C.; Lelieveldt, B. P. F.; Geest, R. J. van der, E-mail: rvdgeest@lumc.nl [Department of Radiology, Division of Image Processing, Leiden University Medical Center, 2300 RC Leiden (Netherlands); Klein, S. [Department of Radiology and Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam 3015 GE (Netherlands); Kwee, R. M.; Kooi, M. E. [Department of Radiology, Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, Maastricht 6202 AZ (Netherlands)

    2013-12-15

    Purpose: Atherosclerosis is the primary cause of heart disease and stroke. The detailed assessment of atherosclerosis of the carotid artery requires high resolution imaging of the vessel wall using multiple MR sequences with different contrast weightings. These images allow manual or automated classification of plaque components inside the vessel wall. Automated classification requires all sequences to be in alignment, which is hampered by patient motion. In clinical practice, correction of this motion is performed manually. Previous studies applied automated image registration to correct for motion using only nondeformable transformation models and did not perform a detailed quantitative validation. The purpose of this study is to develop an automated accurate 3D registration method, and to extensively validate this method on a large set of patient data. In addition, the authors quantified patient motion during scanning to investigate the need for correction. Methods: MR imaging studies (1.5T, dedicated carotid surface coil, Philips) from 55 TIA/stroke patients with ipsilateral <70% carotid artery stenosis were randomly selected from a larger cohort. Five MR pulse sequences were acquired around the carotid bifurcation, each containing nine transverse slices: T1-weighted turbo field echo, time of flight, T2-weighted turbo spin-echo, and pre- and postcontrast T1-weighted turbo spin-echo images (T1W TSE). The images were manually segmented by delineating the lumen contour in each vessel wall sequence and were manually aligned by applying throughplane and inplane translations to the images. To find the optimal automatic image registration method, different masks, choice of the fixed image, different types of the mutual information image similarity metric, and transformation models including 3D deformable transformation models, were evaluated. Evaluation of the automatic registration results was performed by comparing the lumen segmentations of the fixed image and

  5. Mapping within-field variations of soil organic carbon content using UAV multispectral visible near-infrared images

    Science.gov (United States)

    Gilliot, Jean-Marc; Vaudour, Emmanuelle; Michelin, Joël

    2016-04-01

    This study was carried out in the framework of the PROSTOCK-Gessol3 project supported by the French Environment and Energy Management Agency (ADEME), the TOSCA-PLEIADES-CO project of the French Space Agency (CNES) and the SOERE PRO network working on environmental impacts of Organic Waste Products recycling on field crops at long time scale. The organic matter is an important soil fertility parameter and previous studies have shown the potential of spectral information measured in the laboratory or directly in the field using field spectro-radiometer or satellite imagery to predict the soil organic carbon (SOC) content. This work proposes a method for a spatial prediction of bare cultivated topsoil SOC content, from Unmanned Aerial Vehicle (UAV) multispectral imagery. An agricultural plot of 13 ha, located in the western region of Paris France, was analysed in April 2013, shortly before sowing while it was still bare soil. Soils comprised haplic luvisols, rendzic cambisols and calcaric or colluvic cambisols. The UAV platform used was a fixed wing provided by Airinov® flying at an altitude of 150m and was equipped with a four channels multispectral visible near-infrared camera MultiSPEC 4C® (550nm, 660nm, 735 nm and 790 nm). Twenty three ground control points (GCP) were sampled within the plot according to soils descriptions. GCP positions were determined with a centimetric DGPS. Different observations and measurements were made synchronously with the drone flight: soil surface description, spectral measurements (with ASD FieldSpec 3® spectroradiometer), roughness measurements by a photogrammetric method. Each of these locations was sampled for both soil standard physico-chemical analysis and soil water content. A Structure From Motion (SFM) processing was done from the UAV imagery to produce a 15 cm resolution multispectral mosaic using the Agisoft Photoscan® software. The SOC content was modelled by partial least squares regression (PLSR) between the

  6. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  7. Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

    Science.gov (United States)

    Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2016-03-01

    The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care

  8. Potential of multispectral imaging technology for rapid and non-destructive determination of the microbiological quality of beef filets during aerobic storage.

    Science.gov (United States)

    Panagou, Efstathios Z; Papadopoulou, Olga; Carstensen, Jens Michael; Nychas, George-John E

    2014-03-17

    The performance of a multispectral imaging system has been evaluated in monitoring aerobically packaged beef filet spoilage at different storage temperatures (0, 4, 8, 12, and 16°C). Spectral data in the visible and short wave near infrared area (405-970nm) were collected from the surface of meat samples and correlated with microbiological data (log counts), for total viable counts (TVCs), Pseudomonas spp., and Brochothrix thermosphacta. Qualitative analysis (PLS-DA) was employed for the discrimination of meat samples in three microbiological quality classes based on the values of total viable counts, namely Class 1 (TVC7.0log10CFU/g). Furthermore, PLS regression models were developed to provide quantitative estimations of microbial counts during meat storage. In both cases model validation was implemented with independent experiments at intermediate storage temperatures (2 and 10°C) using different batches of meat. Results demonstrated good performance in classifying meat samples with overall correct classification rate for the three quality classes ranging from 91.8% to 80.0% for model calibration and validation, respectively. For quantitative estimation, the calculated regression coefficients between observed and estimated counts ranged within 0.90-0.93 and 0.78-0.86 for model development and validation, respectively, depending on the microorganism. Moreover, the calculated average deviation between observations and estimations was 11.6%, 13.6%, and 16.7% for Pseudomonas spp., B. thermosphacta, and TVC, respectively. The results indicated that multispectral vision technology has significant potential as a rapid and non-destructive technique in assessing the microbiological quality of beef fillets.

  9. Use of partial least squares discriminant analysis on visible-near infrared multispectral image data to examine germination ability and germ length in spinach seeds

    DEFF Research Database (Denmark)

    Shetty, Nisha; Olesen, Merete Halkjær; Gislum, René;

    2012-01-01

    Because of the difficulties in obtaining homogenous germination of spinach seeds for baby leaf production, the possibility of using partial least squares discriminant analysis (PLS-DA) on features extracted from multispectral images of spinach seeds was investigated. The objective has been...

  10. Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)

    DEFF Research Database (Denmark)

    Olesen, M. Halkjaer; Carstensen, Jens Michael; Boelt, B.

    2011-01-01

    Seed health tests are time consuming and require substantial training for characterization of pathogenic fungi on seed. A new approach to use a multispectral vision system for identifying surface properties of different fungal infections has been tested in spinach (Spinacia oleracea L.) at Aarhus...... based on mean pixel intensity, Canonical Discriminant Analysis (CDA) and classification by Jeffries-Matusita (JM) distance illustrates that a combination of Near Infrared spectra (NIR) and Visual spectra (VIS) is able to identify uninfected seeds from infected seeds ranging from 80-100%. Classification....... and Stemphylium spp. needs further development before practical application....

  11. ORTHO-RECTIFICATION OF HJ-1A/1B MULTI-SPECTRAL IMAGE BASED ON THE GCP IMAGE DATABASE

    Directory of Open Access Journals (Sweden)

    G. Li

    2012-07-01

    Full Text Available HJ satellite is the abbreviation of the Small Satellite Constellation of Environment and Disaster Monitoring and Forecasting in China, which plays a very important role in forecasting and monitoring the environment problems and natural disasters. The ortho-rectification of HJ images aided by GCP (Ground Control Point image database is presented in this paper. The GCP image database is constructed from historical LandSat-TM images and the GCP chip consists of image and geographic attribute information. Then auto-searching and matching algorithm is introduced and mis-matching elimination method is presented. The imaging model based on collinearity equation and the polynomial description of the attitude and position of scanning line is utilized for ortho-rectification. Four scene images are experimented and compared, and the result demonstrated the feasibility and high efficiency of the whole work flow.

  12. Mapping paddy biomass with multiple vegetation indexes by using multispectral remotely sensed image

    Science.gov (United States)

    Gu, Xiaohe; Wang, Yancang; Song, Xiaoyu; Xu, Xingang

    2016-10-01

    Monitoring dry biomass of crop timely and accurately by remote sensing is crucial to assess crop growth, manage field water-fertilizer and predict yield. The Huaihe River Basin in China was chose as study area to map the spatial distribution of paddy biomass. The study derived 12 vegetation indexes from HJ-CCD image, which were closely related to crop growth. After screening sensitive vegetation index with in-situ samples by correlation analysis, the study developed the inversion model by single variable and multiple variables. The determination coefficient (R2) and root mean square error (RMSE) was used to evaluate the accuracy of models. Results showed that the accuracies of multivariable models were better than these of single-variable models, of which the average R2 reached 0.647 and the average RMSE was 0.059. It indicated that the multi-variable models were input in more information than those of single-variable models, which improved the accuracies of estimating paddy biomass in to a certain degree. The average overall accuracies of multi-variable models were 92.7%, while that of singe-variable models were 87.8%. The model with multiple linear regressions could be used to map the paddy biomass in the study area by using HJ-CCD image.

  13. Determination of astaxanthin concentration in Rainbow trout (Oncorhynchus mykiss) by multispectral image analysis

    DEFF Research Database (Denmark)

    Frosch, Stina; Dissing, Bjørn Skovlund; Ersbøll, Bjarne Kjær

    extraction of astaxanthin from the minced sample into a suitable solvent such as acetone or hexane before further analysis. The existing methods have several drawbacks including being destructive and labour consuming. Current state-of-the art vision systems for quality and process control in the fish.......27 ppm and a goodness of fit of 0.86. The PLSR model made it possible to predict the astaxanthin concentration in each pixel of the image – surface chemistry map - and thereby show the astaxanthin distribution in the fillet. The projected images clearly show a difference in astaxanthin distribution...

  14. Estimation of urban surface water at subpixel level from neighborhood pixels using multispectral remote sensing image (Conference Presentation)

    Science.gov (United States)

    Xie, Huan; Luo, Xin; Xu, Xiong; Wang, Chen; Pan, Haiyan; Tong, Xiaohua; Liu, Shijie

    2016-10-01

    Water body is a fundamental element in urban ecosystems and water mapping is critical for urban and landscape planning and management. As remote sensing has increasingly been used for water mapping in rural areas, this spatially explicit approach applied in urban area is also a challenging work due to the water bodies mainly distributed in a small size and the spectral confusion widely exists between water and complex features in the urban environment. Water index is the most common method for water extraction at pixel level, and spectral mixture analysis (SMA) has been widely employed in analyzing urban environment at subpixel level recently. In this paper, we introduce an automatic subpixel water mapping method in urban areas using multispectral remote sensing data. The objectives of this research consist of: (1) developing an automatic land-water mixed pixels extraction technique by water index; (2) deriving the most representative endmembers of water and land by utilizing neighboring water pixels and adaptive iterative optimal neighboring land pixel for respectively; (3) applying a linear unmixing model for subpixel water fraction estimation. Specifically, to automatically extract land-water pixels, the locally weighted scatter plot smoothing is firstly used to the original histogram curve of WI image . And then the Ostu threshold is derived as the start point to select land-water pixels based on histogram of the WI image with the land threshold and water threshold determination through the slopes of histogram curve . Based on the previous process at pixel level, the image is divided into three parts: water pixels, land pixels, and mixed land-water pixels. Then the spectral mixture analysis (SMA) is applied to land-water mixed pixels for water fraction estimation at subpixel level. With the assumption that the endmember signature of a target pixel should be more similar to adjacent pixels due to spatial dependence, the endmember of water and land are determined

  15. Retinal and choroidal oxygen saturation of the optic nerve head in open-angle glaucoma subjects by multispectral imaging.

    Science.gov (United States)

    Li, Gai-Yun; Al-Wesabi, Samer Abdo; Zhang, Hong

    2016-12-01

    The aim of this study was to determine whether differences exist in oxygen supply to the optic nerve head (ONH) from the retinal and choroidal vascular layers in patients with primary open angle glaucoma (POAG) using multispectral imaging (MSI).This ia an observational, cross-sectional study.Multispectral images were acquired from 38 eyes of 19 patients with POAG, and 42 healthy eyes from 21 matched volunteers with Annidis' RHA multispectral digital ophthalmoscopy. Superficial and deeper oxygen saturation of the optic disc was represented by the mean gray scale values on the retinal and choroidal oxy-deoxy maps, respectively. Statistical analysis was performed to detect differences in ONH oxygen saturation between the 2 groups. Oxygen saturation levels in the eyes of POAG patients with severe glaucoma were compared to those of fellow eyes from the same subjects. Linear correlation analysis was performed to assess the association between ONH oxygen saturation and systemic and ocular parameters.No statistical difference was found in retinal and choroidal oxygen saturation between the POAG and control groups. In the glaucoma patients, retinal oxygen saturation was lower for eyes with worse visual fields than in those with good visual fields (t = 4.009, P = 0.001). In POAG patients, retinal oxygen saturation was dependent on mean defect of visual field and retinal nerve fiber layer thickness (RNFLT) (r = 0.511, 0.504, P = 0.001, 0.001, respectively), whereas the choroid vasculature oxygen saturation was inversely related to RNFLT (r = -0.391, P = 0.015). An age-dependent increase in retinal oxygen saturation was found for both the POAG and control groups (r = 0.473, 0.410, P = 0.007, 0.003, respectively).MSI revealed a significant correlation between functional and structural impairments in glaucoma and retinal oxygen saturation. MSI could provide objective assessments of perfusion impairments of the glaucomatous ONH. This is a

  16. Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes.

    Science.gov (United States)

    Klukkert, Marten; Wu, Jian X; Rantanen, Jukka; Carstensen, Jens M; Rades, Thomas; Leopold, Claudia S

    2016-07-30

    Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using an eccentric as well as a rotary tablet press at compression pressures from 20MPa up to 410MPa. It was found, that UV imaging can provide both, relevant information on chemical and physical tablet attributes. The tablet API content and radial tensile strength could be estimated by UV imaging combined with partial least squares analysis. Furthermore, an image analysis routine was developed and successfully applied to the UV images that provided qualitative information on physical tablet surface properties such as intactness and surface density profiles, as well as quantitative information on variations in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process and formulation optimization purposes.

  17. Online Multi-Spectral Meat Inspection

    DEFF Research Database (Denmark)

    Nielsen, Jannik Boll; Larsen, Anders Boesen Lindbo

    2013-01-01

    We perform an explorative study on multi-spectral image data from a prototype device developed for fast online quality inspection of meat products. Because the camera setup is built for speed, we sacrifice exact pixel correspondences between the different bands of the multi-spectral images. Our...... work is threefold as we 1) investigate the color distributions and construct a model to describe pork loins, 2) classify the different components in pork loins (meat, fat, membrane), and 3) detect foreign objects on the surface of pork loins. Our investigation shows that the color distributions can...... effectively be modeled using the Gaussian mixture model (GMM). For the classification task we build a classifier using a GMM. For detecting foreign objects, we construct a novelty detector using a GMM. We evaluate our method on a small dataset with mixed results. While we are able to provide reasonable...

  18. Computationally efficient perturbative forward modeling for 3D multispectral bioluminescence and fluorescence tomography

    Science.gov (United States)

    Dutta, Joyita; Ahn, Sangtae; Li, Changqing; Chaudhari, Abhijit J.; Cherry, Simon R.; Leahy, Richard M.

    2008-03-01

    The forward problem of optical bioluminescence and fluorescence tomography seeks to determine, for a given 3D source distribution, the photon density on the surface of an animal. Photon transport through tissues is commonly modeled by the diffusion equation. The challenge, then, is to accurately and efficiently solve the diffusion equation for a realistic animal geometry and heterogeneous tissue types. Fast analytical solvers are available that can be applied to arbitrary geometries but assume homogeneity of tissue optical properties and hence have limited accuracy. The finite element method (FEM) with volume tessellation allows reasonably accurate modeling of both animal geometry and tissue heterogeneity, but this approach is computationally intensive. The computational challenge is heightened when one is working with multispectral data to improve source localization and conditioning of the inverse problem. Here we present a fast forward model based on the Born approximation that falls in between these two approaches. Our model introduces tissue heterogeneity as perturbations in diffusion and absorption coefficients at rectangular grid points inside a mouse atlas. These reflect as a correction term added to the homogeneous forward model. We have tested our model by performing source localization studies first with a biolumnescence simulation setup and then with an experimental setup using a fluorescent source embedded in an inhomogeneous phantom that mimicks tissue optical properties.

  19. Spectral Separation of Quantum Dots within Tissue Equivalent Phantom Using Linear Unmixing Methods in Multispectral Fluorescence Reflectance Imaging

    Directory of Open Access Journals (Sweden)

    Ebrahim Najafzadeh

    2012-09-01

    Full Text Available Introduction Non-invasive Fluorescent Reflectance Imaging (FRI is used for accessing physiological and molecular processes in biological media. The aim of this article is to separate the overlapping emission spectra of quantum dots within tissue-equivalent phantom using SVD, Jacobi SVD, and NMF methods in the FRI mode. Materials and Methods In this article, a tissue-like phantom and an optical setup in reflectance mode were developed. The algorithm of multispectral imaging method was then written in Matlab environment. The setup included the diode-pumped solid-state lasers at 479 nm, 533 nm, and 798 nm, achromatic telescopic, mirror, high pass and low pass filters, and EMCCD camera. The FRI images were acquired by a CCD camera using band pass filter centered at 600 nm and high pass max at 615 nm for the first region and high pass filter max at 810 nm for the second region. The SVD and Jacobi SVD algorithms were written in Matlab environment and compared with a Non-negative Matrix Factorization (NMF and applied to the obtained images. Results PSNR, SNR, CNR of SVD, and NMF methods were obtained as 39 dB, 30.1 dB, and 0.7 dB, respectively. The results showed that the difference of Jacobi SVD PSNR with PSNR of NMF and modified NMF algorithm was significant (p

  20. Multi-spectral synthetic image generation for ground vehicle identification training

    Science.gov (United States)

    May, Christopher M.; Pinto, Neil A.; Sanders, Jeffrey S.

    2016-05-01

    There is a ubiquitous and never ending need in the US armed forces for training materials that provide the warfighter with the skills needed to differentiate between friendly and enemy forces on the battlefield. The current state of the art in battlefield identification training is the Recognition of Combat Vehicles (ROC-V) tool created and maintained by the Communications - Electronics Research, Development and Engineering Center Night Vision and Electronic Sensors Directorate (CERDEC NVESD). The ROC-V training package utilizes measured visual and thermal imagery to train soldiers about the critical visual and thermal cues needed to accurately identify modern military vehicles and combatants. This paper presents an approach to augment the existing ROC-V imagery database with synthetically generated multi-spectral imagery that will allow NVESD to provide improved training imagery at significantly lower costs.

  1. SPECIES-SPECIFIC FOREST VARIABLE ESTIMATION USING NON-PARAMETRIC MODELING OF MULTI-SPECTRAL PHOTOGRAMMETRIC POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    J. Bohlin

    2012-07-01

    Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.

  2. Predicting forest structural parameters using the image texture derived from WorldView-2 multispectral imagery in a dryland forest, Israel

    Science.gov (United States)

    Ozdemir, Ibrahim; Karnieli, Arnon

    2011-10-01

    Estimation of forest structural parameters by field-based data collection methods is both expensive and time consuming. Satellite remote sensing is a low-cost alternative in modeling and mapping structural parameters in large forest areas. The current study investigates the potential of using WordView-2 multispectral satellite imagery for predicting forest structural parameters in a dryland plantation forest in Israel. The relationships between image texture features and the several structural parameters such as Number of Trees (NT), Basal Area (BA), Stem Volume (SV), Clark-Evans Index (CEI), Diameter Differentiation Index (DDI), Contagion Index (CI), Gini Coefficient (GC), and Standard Deviation of Diameters at Breast Heights (SDDBH) were examined using correlation analyses. These variables were obtained from 30 m × 30 m square-shaped plots. The Standard Deviation of Gray Levels (SDGL) as a first order texture feature and the second order texture variables based on Gray Level Co-occurrence Matrix (GLCM) were calculated for the pixels that corresponds to field plots. The results of the correlation analysis indicate that the forest structural parameters are significantly correlated with the image texture features. The highest correlation coefficients were calculated for the relationships between the SDDBH and the contrast of red band ( r = 0.75, p 0.50). In conclusion, cross-validated statistics confirmed that the structural parameters including the BA, SDDBH, and GC can be predicted and mapped with a reasonable accuracy using the texture features extracted from the spectral bands of WorldView-2 image.

  3. Material Characterization using Passive Multispectral Polarimetric Imagery

    Science.gov (United States)

    2013-03-01

    least intuitive RS technique is undoubtedly polarimetry . Polarization is a property of all TEM waves, so its applications are not limited to any...Shaw. “Review of passive imaging polarimetry for remote sensing applications”. Applied Optics, 45(22):5453–5469, 2006. [48] Vanderbilt, V.C. and...refractive index; polarimetry ; multispectral; polarization; polarisation; polarimetric imagery; dispersion; Drude model; Cauchy equation; remote

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

    Science.gov (United States)

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

    2016-09-01

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

  5. Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the Dead Sea Scrolls.

    Science.gov (United States)

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-09-01

    The aim of this project is the development of a noninvasive technique based on LED multispectral imaging (MSI) for monitoring the conservation state of the Dead Sea Scrolls (DSS) collection. It is well-known that changes in the parchment reflectance drive the transition of the scrolls from legible to illegible. Capitalizing on this fact, we will use spectral imaging to detect changes in the reflectance before they become visible to the human eye. The technique uses multivariate analysis and statistical process control theory. The present study was carried out on a "sample" parchment of calfskin. The monitoring of the surface of a commercial modern parchment aged consecutively for 2 h and 6 h at 80 °C and 50% relative humidity (ASTM) was performed at the Imaging Lab of the Library of Congress (Washington, DC, U.S.A.). MSI is here carried out in the vis-NIR range limited to 1 μm, with a number of bands of 13 and bandwidths that range from about 10 nm in UV to 40 nm in IR. Results showed that we could detect and locate changing pixels, on the basis of reflectance changes, after only a few "hours" of aging.

  6. Persistent observations of the Arctic from highly elliptical orbits using multispectral, wide field of view day-night imagers

    Science.gov (United States)

    Puschell, Jeffery J.; Johnson, David; Miller, Steven

    2014-09-01

    Persistent satellite observations are essential for monitoring and understanding Earth's environmentally sensitive and rapidly changing Arctic region. Compact wide-field-of-view imagers aboard satellites in Highly Elliptical Orbit (HEO) could stare at the Arctic and collect multispectral, high dynamic range visible and near-infrared imagery with sensitivity similar to that of the Joint Polar Satellite System (JPSS) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) in sun synchronous polar orbit. These HEO Day/Night Imagers (HDNIs) provide high contrast visible wavelength imagery through the long polar night. Their dynamic range -- extending from the brightest sunlit clouds, ice and snow to reflected moonlight from open water -- enables cloud, ice and sea surface discrimination even under very low light and low thermal contrast conditions. Rapidly refreshed HDNI data results in frequent updates to key environmental products such as cloud imagery and microphysical properties, ice and open water distribution (including real-time maps of where leads are opening and new ice is forming), vector ice motion and vector polar winds from cloud motion. The relatively small size of HDNIs makes them ideal for deployment as a hosted payload or as the primary payload onboard a small satellite.

  7. Estimation of floodplain aboveground biomass using multispectral remote sensing and nonparametric modeling

    Science.gov (United States)

    Güneralp, İnci; Filippi, Anthony M.; Randall, Jarom

    2014-12-01

    Floodplain forests serve a critical function in the global carbon cycle because floodplains constitute an important carbon sink compared with other terrestrial ecosystems. Forests on dynamic floodplain landscapes, such as those created by river meandering processes, are characterized by uneven-aged trees and exhibit high spatial variability, reflecting the influence of interacting fluvial, hydrological, and ecological processes. Detailed and accurate mapping of aboveground biomass (AGB) on floodplain landscapes characterized by uneven-aged forests is critical for improving estimates of floodplain-forest carbon pools, which is useful for greenhouse gas (GHG) life cycle assessment. It would also help improve our process understanding of biomorphodynamics of river-floodplain systems, as well as planning and monitoring of conservation, restoration, and management of riverine ecosystems. Using stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), and Cubist, we remotely estimate AGB of a bottomland hardwood forest on a meander bend of a dynamic lowland river. As predictors, we use 30-m and 10-m multispectral image bands (Landsat 7 ETM+ and SPOT 5, respectively) and ancillary data. Our findings show that SGB and MARS significantly outperform Cubist, which is used for U.S. national-scale forest biomass mapping. Across all data-experiments and algorithms, at 10-m spatial resolution, SGB yields the best estimates (RMSE = 22.49 tonnes/ha; coefficient of determination (R2) = 0.96) when geomorphometric data are also included. On the other hand, at 30-m spatial resolution, MARS yields the best estimates (RMSE = 29.2 tonnes/ha; R2 = 0.94) when image-derived data are also included. By enabling more accurate AGB mapping of floodplains characterized by uneven-aged forests, SGB and MARS provide an avenue for improving operational estimates of AGB and carbon at local, regional/continental, and global scales.

  8. Low-cost multispectral imaging for remote sensing of lettuce health

    Science.gov (United States)

    Ren, David D. W.; Tripathi, Siddhant; Li, Larry K. B.

    2017-01-01

    In agricultural remote sensing, unmanned aerial vehicle (UAV) platforms offer many advantages over conventional satellite and full-scale airborne platforms. One of the most important advantages is their ability to capture high spatial resolution images (1-10 cm) on-demand and at different viewing angles. However, UAV platforms typically rely on the use of multiple cameras, which can be costly and difficult to operate. We present the development of a simple low-cost imaging system for remote sensing of crop health and demonstrate it on lettuce (Lactuca sativa) grown in Hong Kong. To identify the optimal vegetation index, we recorded images of both healthy and unhealthy lettuce, and used them as input in an expectation maximization cluster analysis with a Gaussian mixture model. Results from unsupervised and supervised clustering show that, among four widely used vegetation indices, the blue wide-dynamic range vegetation index is the most accurate. This study shows that it is readily possible to design and build a remote sensing system capable of determining the health status of lettuce at a reasonably low cost (

  9. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

    Science.gov (United States)

    Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John

    2016-01-01

    Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

  10. [Hard and soft classification method of multi-spectral remote sensing image based on adaptive thresholds].

    Science.gov (United States)

    Hu, Tan-Gao; Xu, Jun-Feng; Zhang, Deng-Rong; Wang, Jie; Zhang, Yu-Zhou

    2013-04-01

    Hard and soft classification techniques are the conventional methods of image classification for satellite data, but they have their own advantages and drawbacks. In order to obtain accurate classification results, we took advantages of both traditional hard classification methods (HCM) and soft classification models (SCM), and developed a new method called the hard and soft classification model (HSCM) based on adaptive threshold calculation. The authors tested the new method in land cover mapping applications. According to the results of confusion matrix, the overall accuracy of HCM, SCM, and HSCM is 71.06%, 67.86%, and 71.10%, respectively. And the kappa coefficient is 60.03%, 56.12%, and 60.07%, respectively. Therefore, the HSCM is better than HCM and SCM. Experimental results proved that the new method can obviously improve the land cover and land use classification accuracy.

  11. Mapping shrublands and forests with multispectral satellite images based on spectral unmixing of scene components

    Science.gov (United States)

    Caetano, Mario R.; Oliveira, Tiago; Paul, Jose U.; Vasconcelos, Maria J.; Cardoso Pereira, Jose M.

    1997-12-01

    Linear spectral mixture models (SMM) with image endmembers (IEM) and with reference endmembers (REM) were tested for discriminating maritime pine stands and shrublands in a Landsat-TM image of Central Portugal. For both types of EM, IEM and REM, two types of SMM were tried: SMM with three EM (SMM-3), i.e., green vegetation, soil and shade, and SMM with five EM (SMM-5), where the EM were the components of the landscapes that we were interested on, i.e., pine canopy, shrub, soil, forest litter and shade. Results showed that in the SMM-5, REM need to be used, since IEM were not pure enough. We verified that in the SMM-5, there was not a single set of EM that could be applied to the whole study area, because the shrubs that exist underneath the pine canopy and in the shrublands could not be modeled just by using a shrub EM. Therefore, SMM-5 require a multi-endmember approach, where the set of EM may change from pixel to pixel. In the SMM-3, an accurate discrimination of shrublands and pine stands (90% accuracy) was achieved by thresholding the shade fraction. In these simpler SMM, IEM and REM produced similar results.

  12. Quality assessment of ZiYuan-3 multispectral and panchromatic images fusion: applied in Jiangsu coastal wetland area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng; Wang, Jing

    2015-01-01

    The new launched ZiYuan-3 (ZY-3) satellite with multispectral (MS) bands and a panchromatic (PAN) band has presented a new opportunity to assess image fusion methods for coastal wetland mapping. This study focuses on image fusion quality assessment through both quantitative spectral and spatial quality analysis and object-oriented classification comparison. Various methods for pan-sharpening ZY-3 MS and PAN bands are tested, including generalized intensity-hue-saturation transform (GIHS), à trous wavelet transform (AWT), nonsubsampled contourlet transform (NSCT), and a combination of NSCT with GIHS (NSCT_GIHS). Spectral fidelity and spatial preservation of fused bands are compared with the original MS bands as reference, and spatial information injections of fused bands are compared with the resampled PAN band as reference. The fusion results demonstrate that, on average, the NSCT_GIHS method has the best performance on spectral fidelity and spatial preservation as well as spatial information injection. The near-infrared (NIR) band has the best spatial information injection in terms of entropy and cross-entropy indices, whereas the NIR band has the best spatial preservation in terms of entropy and structure similarity indices. The classification results show that NSCT_GIHS method also obtains the highest overall accuracy (96%) and Kappa coefficient (0.9425); this is in agreement with the quantitative analysis.

  13. 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.

  14. Dual-Modality Imaging of the Human Finger Joint Systems by Using Combined Multispectral Photoacoustic Computed Tomography and Ultrasound Computed Tomography

    Science.gov (United States)

    Liu, Yubin; Wang, Yating

    2016-01-01

    We developed a homemade dual-modality imaging system that combines multispectral photoacoustic computed tomography and ultrasound computed tomography for reconstructing the structural and functional information of human finger joint systems. The fused multispectral photoacoustic-ultrasound computed tomography (MPAUCT) system was examined by the phantom and in vivo experimental tests. The imaging results indicate that the hard tissues such as the bones and the soft tissues including the blood vessels, the tendon, the skins, and the subcutaneous tissues in the finger joints systems can be effectively recovered by using our multimodality MPAUCT system. The developed MPAUCT system is able to provide us with more comprehensive information of the human finger joints, which shows its potential for characterization and diagnosis of bone or joint diseases. PMID:27774453

  15. UAS-based soil carbon mapping using VIS-NIR (480–1000 nm) multi-spectral imaging: Potential and limitations

    DEFF Research Database (Denmark)

    Aldana Jague, Emilien; Heckrath, Goswin; Macdonald, Andy

    2016-01-01

    Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi-spectral i......Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi...... practices, provide a valuable resource to evaluate this approach. We acquired images (wavelength: 480–550–670–780–880–1000 nm) at an altitude of 120 m over an area of 2 ha using a multi-spectral camera mounted on an UAS. The high-resolution images captured smallscale variations at the soil surface (e...

  16. Dual-Modality Imaging of the Human Finger Joint Systems by Using Combined Multispectral Photoacoustic Computed Tomography and Ultrasound Computed Tomography

    Directory of Open Access Journals (Sweden)

    Yubin Liu

    2016-01-01

    Full Text Available We developed a homemade dual-modality imaging system that combines multispectral photoacoustic computed tomography and ultrasound computed tomography for reconstructing the structural and functional information of human finger joint systems. The fused multispectral photoacoustic-ultrasound computed tomography (MPAUCT system was examined by the phantom and in vivo experimental tests. The imaging results indicate that the hard tissues such as the bones and the soft tissues including the blood vessels, the tendon, the skins, and the subcutaneous tissues in the finger joints systems can be effectively recovered by using our multimodality MPAUCT system. The developed MPAUCT system is able to provide us with more comprehensive information of the human finger joints, which shows its potential for characterization and diagnosis of bone or joint diseases.

  17. Monitoring the Water Quality of Lake Koronia Using Long Time-Series of Multispectral Satellite Images

    Science.gov (United States)

    Perivolioti, Triantafyllia-Maria; Mouratidis, Antonios; Doxani, Georgia; Bobori, Dimitra

    2016-08-01

    In this study, a comprehensive 30-year (1984-2016) water quality parameter database for lake Koronia - one of the most important Ramsar wetlands of Greece - was compiled from Landsat imagery. The reliability of the data was evaluated by comparing water Quality Element (QE) values computed from Landsat data against in-situ data. Water quality algorithms developed from previous studies, specifically for the determination of Water Temperature, pH, Transparency/Secchi Disk Depth (SDD), Chlorophyll a and Conductivity, were applied to Landsat images. In addition, Water Depth, as well as the distribution of floating vegetation and cyanobacterial blooms were mapped. The performed comprehensive analysis posed certain questions, regarding the applicability of single empirical models across multi- temporal, multi-sensor datasets, towards the accurate prediction of key water quality indicators for shallow inland systems. This assessment demonstrates that satellite imagery can provide an accurate method for obtaining comprehensive spatial and temporal coverage of key water quality characteristics.

  18. Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

    Science.gov (United States)

    Lemeshewsky, George P.; Schowengerdt, Robert A.

    2000-01-01

    Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

  19. 基于小波分解的油菜多光谱图像与深度图像数据融合方法%Data fusion of multispectral and depth image for rape plant based on wavelet decomposition

    Institute of Scientific and Technical Information of China (English)

    张艳超; 肖宇钊; 庄载椿; 许凯雯; 何勇

    2016-01-01

    Multi-source image fusion can reduce the miscalculation caused by using single source image. Using the complement and redundancies between multi-source data fusion between complete data can improve the reliability of data. This research was done based on the wavelet decomposition reconstruction method on near ground unmanned aerial vehicle (UAV) simulation platform. Two source image, respectively multispectral image and depth image of rapeseed were acquired. Camera produced by PMD Company, an active imaging sensor which measures the time of flight of infrared light from generator to sensor was used to acquire depth image. Three kinds of image data was acquired from PMD camera namely distance image, intensity image and amplitude image. The three images were different forms of same data from sensor while the intensity image was more sensitive to the edge information in visual field. Tetracam ADC multispectral camera was used for multispectral image acquisition. The images acquired were calibrated using white board. To register the image, depth imaging principle was analyzed and intensity image was used for camera internal parameter calibration. Pinhole model was used and chessboard calibration method was used for camera internal parameters. Since the distance image can’t see Harris points, intensity image was used for image calibration instead. The distance image and intensity image had same internal parameters. The internal parameters were final used for depth image correction so as to generate lens distortion –free images. SIFT method was used to find the corresponding points between two images. The first step was to find feature point descriptors, the second step was to use Mahalanobis distance to find proper matches. Match ratio of 0.6 was appropriate through tests for this purpose. After feature points were found and matched, multispectral image and depth image were resized to same zoom level then were registered and cropped to same size based on the

  20. 3D coaxial out-of-plane metallic antennas for filtering and multi-spectral imaging in the infrared range.

    Science.gov (United States)

    Jacassi, Andrea; Bozzola, Angelo; Zilio, Pierfrancesco; Tantussi, Francesco; De Angelis, Francesco

    2016-06-27

    We fabricated and investigated a new configuration of 3D coaxial metallic antennas working in the infrared which combines the strong lateral light scattering of vertical plasmonic structures with the selective spectral transmission of 2D arrays of coaxial apertures. The coaxial structures are fabricated with a top-down method based on a template of hollow 3D antennas. Each antenna has a multilayer radial structure consisting of dielectric and metallic materials not achievable in a 2D configuration. A planar metallic layer is inserted normally to the antennas. The outer dielectric shell of the antenna defines a nanometric gap between the horizontal plane and the vertical walls. Thanks to this aperture, light can tunnel to the other side of the plane, and be transmitted to the far field in a set of resonances. These are investigated with finite-elements electromagnetic calculations and with Fourier-transform infrared spectroscopy measurements. The spectral position of the resonances can be tuned by changing the lattice period and/or the antenna length. Thanks to the strong scattering provided by the 3D geometry, the transmission peaks possess a high signal-to-noise ratio even when the illuminated area is less than 2 × 2 times the operation wavelength. This opens new possibilities for multispectral imaging in the IR with wavelength-scale spatial resolution.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-09-01

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

  2. Implementation of multispectral image fusion system based on SoPC

    Science.gov (United States)

    Meng, Lingfei; Wang, Zhihui

    2013-10-01

    Combining the theory of wavelet transform based image fusion and SOPC design method, the authors uses SOPC as the core device to design and implement a image fusion system. The fusion system adopts the Verilog hardware description language, Dsp builder and Quartus II development platform together with macro module to complete the logic design and timing control of each module. In the fusion system, we can achieve simple pixel-level image fusion of two registered images. This design not only builds up an image fusion system based on SOPC in accident, but also provides a hardware design principle in SoPC for the future design and Implementation of more comprehensive function of image processing.

  3. Illumination estimation from specular highlight in a multi-spectral image.

    Science.gov (United States)

    An, Dongsheng; Suo, Jinli; Wang, Haoqian; Dai, Qionghai

    2015-06-29

    The reflection spectrum of an object characterizes its surface material, but for non-Lambertian scenes, the recorded spectrum often deviates owing to specular contamination. To compensate for this deviation, the illumination spectrum is required, and it can be estimated from specularity. However, existing illumination-estimation methods often degenerate in challenging cases, especially when only weak specularity exists. By adopting the dichromatic reflection model, which formulates a specular-influenced image as a linear combination of diffuse and specular components, this paper explores two individual priors and one mutual prior upon these two components: (i) The chromaticity of a specular component is identical over all the pixels. (ii) The diffuse component of a specular-contaminated pixel can be reconstructed using its specular-free counterpart describing the same material. (iii) The spectrum of illumination usually has low correlation with that of diffuse reflection. A general optimization framework is proposed to estimate the illumination spectrum from the specular component robustly and accurately. The results of both simulation and real experiments demonstrate the robustness and accuracy of our method.

  4. Multispectral Imaging of Mars from the Mars Science Laboratory Mastcam Instruments: Spectral Properties and Mineralogic Implications Along the Gale Crater Traverse

    Science.gov (United States)

    Bell, James F.; Wellington, Danika; Hardgrove, Craig; Godber, Austin; Rice, Melissa S.; Johnson, Jeffrey R.; Fraeman, Abigail

    2016-10-01

    The Mars Science Laboratory (MSL) Curiosity rover Mastcam is a pair of multispectral CCD cameras that have been imaging the surface and atmosphere in three broadband visible RGB color channels as well as nine additional narrowband color channels between 400 and 1000 nm since the rover's landing in August 2012. As of Curiosity sol 1159 (the most recent PDS data release as of this writing), approximately 140 multispectral imaging targets have been imaged using all twelve unique bandpasses. Near-simultaneous imaging of an onboard calibration target allows rapid relative reflectance calibration of these data to radiance factor and estimated Lambert albedo, for direct comparison to lab reflectance spectra of rocks, minerals, and mixtures. Surface targets among this data set include a variety of outcrop and float rocks (some containing light-toned veins), unconsolidated pebbles and clasts, and loose sand and soil. Some of these targets have been brushed, scuffed, or otherwise disturbed by the rover in order to reveal the (less dusty) interiors of these materials, and those targets and each of Curiosity's drill holes and tailings piles have been specifically targeted for multispectral imaging.Analysis of the relative reflectance spectra of these materials, sometimes in concert with additional compositional and/or mineralogic information from Curiosity's ChemCam LIBS and passive-mode spectral data and CheMin XRD data, reveals the presence of relatively broad solid state crystal field and charge transfer absorption features characteristic of a variety of common iron-bearing phases, including hematite (both nanophase and crystalline), ferric sulfate, olivine, and pyroxene. In addition, Mastcam is sensitive to a weak hydration feature in the 900-1000 nm region that can provide insight on the hydration state of some of these phases, especially sulfates. Here we summarize the Mastcam multispectral data set and the major potential phase identifications made using that data set

  5. Multispectral fluorescence imaging technique for discrimination of cucumber (Cucumis Sativus) seed viability

    Science.gov (United States)

    In this study, we developed a nondestructive method for discriminating viable cucumber (Cucumis sativus) seeds based on hyperspectral fluorescence imaging. The fluorescence spectra of cucumber seeds in the 420–700 nm range were extracted from hyperspectral fluorescence images obtained using 365 nm u...

  6. Hyperspectral and Multispectral Imaging Technique for Food Quality and Safety Evaluation

    Science.gov (United States)

    In this chapter, recently developed ARS line-scan hyperspectral-based sensing technologies to address agro-food safety concerns are presented including a case study using the laboratory-based hyperspectral imaging platforms. An online line-scan imaging system capable of both hyperspectral and multi...

  7. Multi-spectral band selection for satellite-based systems

    Energy Technology Data Exchange (ETDEWEB)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-09-01

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed.

  8. LANDSAT 8 MULTISPECTRAL AND PANSHARPENED IMAGERY PROCESSING ON THE STUDY OF CIVIL ENGINEERING ISSUES

    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou

    2016-06-01

    Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  9. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    Science.gov (United States)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  10. Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

    Science.gov (United States)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoonsoo; O'Donnell, Colm P.

    2016-05-01

    An imaging device to detect fecal contamination in fresh produce fields could allow the producer avoid harvesting fecal contaminated produce. E.coli O157:H7 outbreaks have been associated with fecal contaminated leafy greens. In this study, in-field spectral profiles of bovine fecal matter, soil, and spinach leaves are compared. A common aperture imager designed with two identical monochromatic cameras, a beam splitter, and optical filters was used to simultaneously capture two-spectral images of leaves contaminated with both fecal matter and soil. The optical filters where 10 nm full width half maximum bandpass filters, one at 690 nm and the second at 710 nm. These were mounted in front of the object lenses. New images were created using the ratio of these two spectral images on a pixel by pixel basis. Image analysis results showed that the fecal matter contamination could be distinguished from soil and leaf on the ratio images. The use of this technology has potential to allow detection of fecal contamination in produce fields which can be a source of foodbourne illnesses. It has the added benefit of mitigating cross-contamination during harvesting and processing.

  11. Multispectral Fluorescence Imaging During Robot-assisted Laparoscopic Sentinel Node Biopsy: A First Step Towards a Fluorescence-based Anatomic Roadmap.

    Science.gov (United States)

    van den Berg, Nynke S; Buckle, Tessa; KleinJan, Gijs H; van der Poel, Henk G; van Leeuwen, Fijs W B

    2017-07-01

    During (robot-assisted) sentinel node (SN) biopsy procedures, intraoperative fluorescence imaging can be used to enhance radioguided SN excision. For this combined pre- and intraoperative SN identification was realized using the hybrid SN tracer, indocyanine green-(99m)Tc-nanocolloid. Combining this dedicated SN tracer with a lymphangiographic tracer such as fluorescein may further enhance the accuracy of SN biopsy. Clinical evaluation of a multispectral fluorescence guided surgery approach using the dedicated SN tracer ICG-(99m)Tc-nanocolloid, the lymphangiographic tracer fluorescein, and a commercially available fluorescence laparoscope. Pilot study in ten patients with prostate cancer. Following ICG-(99m)Tc-nanocolloid administration and preoperative lymphoscintigraphy and single-photon emission computed tomograpy imaging, the number and location of SNs were determined. Fluorescein was injected intraprostatically immediately after the patient was anesthetized. A multispectral fluorescence laparoscope was used intraoperatively to identify both fluorescent signatures. Multispectral fluorescence imaging during robot-assisted radical prostatectomy with extended pelvic lymph node dissection and SN biopsy. (1) Number and location of preoperatively identified SNs. (2) Number and location of SNs intraoperatively identified via ICG-(99m)Tc-nanocolloid imaging. (3) Rate of intraoperative lymphatic duct identification via fluorescein imaging. (4) Tumor status of excised (sentinel) lymph node(s). (5) Postoperative complications and follow-up. Near-infrared fluorescence imaging of ICG-(99m)Tc-nanocolloid visualized 85.3% of the SNs. In 8/10 patients, fluorescein imaging allowed bright and accurate identification of lymphatic ducts, although higher background staining and tracer washout were observed. The main limitation is the small patient population. Our findings indicate that a lymphangiographic tracer can provide additional information during SN biopsy based on ICG-(99m

  12. Relative dating of Hawaiian lava flows using multispectral thermal infrared images - A new tool for geologic mapping of young volcanic terranes

    Science.gov (United States)

    Kahle, Anne B.; Gillespie, Alan R.; Abbott, Elsa A.; Abrams, Michael J.; Walker, Richard E.

    1988-01-01

    The weathering of Hawaiian basalts in arid and semiarid environments is accompanied by changes in their thermal infrared emittance spectra. The spectral differences can be measured and mapped with multispectral imaging systems. The differences appear to be related to the degree of development, preservation, and alteration of glassy crusts; the oxidation of iron; and the accretion of silica-rich surface veneers. Because the measurements are quantitative and in image format, they are useful for estimating relative ages in geologic mapping of lava flows. In Hawaii this technique is most diagnostic for distinguishing among sparsely vegetated flows less than 1.5 ka in age.

  13. A Color-texture Approach Based on Mutual Information for Multispectral Image Classification

    Directory of Open Access Journals (Sweden)

    Hassan El Maia

    2010-10-01

    Full Text Available In this work we propose an approach to improve the results of color texture image classification. We construct a new space called hybrid color-texture space by selecting the most discriminating attributes for the textures. Attributes are calculating from the co-occurrence matrix. The selection is done by the algorithm MRMR based on the mutual information. The Support Vectors Machine classifier (SVMis used. A comparison with an iterative selection is also performed. The effectiveness of the proposed approach is evaluated on the VisTex database and on a SPOT HRV (XS image representing two forest areas in the region of Rabat.

  14. Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations

    Science.gov (United States)

    Kutser, Tiit; Vahtmäe, Ele; Martin, Georg

    2006-04-01

    One of the objectives of monitoring benthic algal cover is to observe short- and long-term changes in species distribution and structure of coastal benthic habitats as indicators of ecological state. Mapping benthic algal cover with conventional methods (diving) provides great accuracy and high resolution, yet is very expensive and is limited by the time and manpower necessary. We measured reflectance spectra of three indicator species for the Baltic Sea: Cladophora glomerata (green macroalgae), Furcellaria lumbricalis (red macroalgae), and Fucus vesiculosus (brown macroalgae) and used a bio-optical model in an attempt to estimate whether these algae are separable from each other and sandy bottom or deep water by means of satellite remote sensing. Our modelling results indicate that to some extent it is possible to map the studied species with multispectral satellite sensors in turbid waters. However, the depths where the macroalgae can be detected are often shallower than the maximum depths where the studied species usually grow. In waters deeper than just a few meters, the differences between the studied bottom types are seen only in band 2 (green) of the multispectral sensors under investigation. It means that multispectral sensors are capable of detecting difference in brightness only in one band which is insufficient for recognition of different bottom types in waters where no or few in situ data are available. Configuration of MERIS spectral bands allows the recognition of red, green and brown macroalgae based on their spectral signatures provided the algal belts are wider than MERIS spatial resolution. Commercial stock of F. lumbricalis in West-Estonian Archipelago covers area where MERIS 300 m spatial resolution is adequate. However, strong attenuation of light in the water column and signal to noise ratio of the sensor do not allow mapping of Furcellaria down to maximum depths where it occurs.

  15. Identifying fecal matter contamination in produce fields using multispectral reflectance imaging under ambient solar illumination

    Science.gov (United States)

    An imaging device to detect fecal contamination in fresh produce fields could allow the producer to avoid harvesting fecal-contaminated produce. E.coli O157:H7 outbreaks have been associated with fecal-contaminated leafy greens. In this study, in-field spectral profiles of bovine fecal matter, soil,...

  16. Experimental Results of Ground Disturbance Detection Using Uncooled Infrared Imagers in Wideband and Multispectral Modes

    Science.gov (United States)

    2012-02-01

    digitally at 14-bit resolution via a user interface by a computer. An adaptor was made and mounted to the front of the imager aperture for LWIR filter...1996). Mesure de signatures infrarouges de mines terrestres et expériences de perception. DREV-R- 9525. Defence R&D Canada. 43 pages. [2] Simard

  17. Rapid Assessment of Tablet Film Coating Quality by Multispectral UV Imaging

    DEFF Research Database (Denmark)

    Klukkert, Marten; Wu, Jian X.; Rantanen, Jukka

    2016-01-01

    for assessment of the coating layer quality of tablets. UV images were used to detect, characterize, and localize coating layer defects such as chipped parts, inhomogeneities, and cracks, as well as to evaluate the coating surface texture. Acetylsalicylic acid tablets were prepared on a rotary tablet press...

  18. Prostate Cancer Segmentation Using Multispectral Random Walks

    Science.gov (United States)

    Artan, Yusuf; Haider, Masoom A.; Yetik, Imam Samil

    Several studies have shown the advantages of multispectral magnetic resonance imaging (MRI) as a noninvasive imaging technique for prostate cancer localization. However, a large proportion of these studies are with human readers. There is a significant inter and intra-observer variability for human readers, and it is substantially difficult for humans to analyze the large dataset of multispectral MRI. To solve these problems a few studies were proposed for fully automated cancer localization in the past. However, fully automated methods are highly sensitive to parameter selection and often may not produce desirable segmentation results. In this paper, we present a semi-supervised segmentation algorithm by extending a graph based semi-supervised random walker algorithm to perform prostate cancer segmentation with multispectral MRI. Unlike classical random walker which can be applied only to dataset of single type of MRI, we develop a new method that can be applied to multispectral images. We prove the effectiveness of the proposed method by presenting the qualitative and quantitative results of multispectral MRI datasets acquired from 10 biopsy-confirmed cancer patients. Our results demonstrate that the multispectral MRI noticeably increases the sensitivity and jakkard measures of prostate cancer localization compared to single MR images; 0.71 sensitivity and 0.56 jakkard for multispectral images compared to 0.51 sensitivity and 0.44 jakkard for single MR image based segmentation.

  19. Review and Implementation of the Emerging CCSDS Recommended Standard for Multispectral and Hyperspectral Lossless Image Coding

    Science.gov (United States)

    Sanchez, Jose Enrique; Auge, Estanislau; Santalo, Josep; Blanes, Ian; Serra-Sagrista, Joan; Kiely, Aaron

    2011-01-01

    A new standard for image coding is being developed by the MHDC working group of the CCSDS, targeting onboard compression of multi- and hyper-spectral imagery captured by aircraft and satellites. The proposed standard is based on the "Fast Lossless" adaptive linear predictive compressor, and is adapted to better overcome issues of onboard scenarios. In this paper, we present a review of the state of the art in this field, and provide an experimental comparison of the coding performance of the emerging standard in relation to other state-of-the-art coding techniques. Our own independent implementation of the MHDC Recommended Standard, as well as of some of the other techniques, has been used to provide extensive results over the vast corpus of test images from the CCSDS-MHDC.

  20. Costal Bathymetry Estimation from Multispectral Image with Back Propagation Neural Network

    Science.gov (United States)

    Huang, S. Y.; Liu, C. L.; Ren, H.

    2016-06-01

    Bathymetric data in coastal area are important for marine sciences, hydrological applications and even for transportation and military purposes. Compare to traditional sonar and recent airborne bathymetry LIDAR systems, optical satellite images can provide information to survey a large area with single or multiple satellite images efficiently and economically. And it is especially suitable for coastal area because the penetration of visible light in water merely reaches 30 meters. In this study, a three-layer back propagation neural network is proposed to estimate bathymetry. In the learning stage, some training samples with known depth are adopted to train the weights of the neural network until the stopping criterion is satisfied. The spectral information is sent to the input layer and fits the true water depth with the output. The depths of training samples are manually measured from stereo images of the submerged reefs after water refraction correction. In the testing stage, all non-land pixels are processed. The experiments show the mean square errors are less than 3 meters.

  1. COSTAL BATHYMETRY ESTIMATION FROM MULTISPECTRAL IMAGE WITH BACK PROPAGATION NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    S. Y. Huang

    2016-06-01

    Full Text Available Bathymetric data in coastal area are important for marine sciences, hydrological applications and even for transportation and military purposes. Compare to traditional sonar and recent airborne bathymetry LIDAR systems, optical satellite images can provide information to survey a large area with single or multiple satellite images efficiently and economically. And it is especially suitable for coastal area because the penetration of visible light in water merely reaches 30 meters. In this study, a three-layer back propagation neural network is proposed to estimate bathymetry. In the learning stage, some training samples with known depth are adopted to train the weights of the neural network until the stopping criterion is satisfied. The spectral information is sent to the input layer and fits the true water depth with the output. The depths of training samples are manually measured from stereo images of the submerged reefs after water refraction correction. In the testing stage, all non-land pixels are processed. The experiments show the mean square errors are less than 3 meters.

  2. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  3. Pancam multispectral imaging results from the Spirit Rover at Gusev crater

    Science.gov (United States)

    Bell, J.F.; Squyres, S. W.; Arvidson, R. E.; Arneson, H.M.; Bass, D.; Blaney, D.; Cabrol, N.; Calvin, W.; Farmer, J.; Farrand, W. H.; Goetz, W.; Golombek, M.; Grant, J. A.; Greeley, R.; Guinness, E.; Hayes, A.G.; Hubbard, M.Y.H.; Herkenhoff, K. E.; Johnson, M.J.; Johnson, J. R.; Joseph, J.; Kinch, K.M.; Lemmon, M.T.; Li, R.; Madsen, M.B.; Maki, J.N.; Malin, M.; McCartney, E.; McLennan, S.; McSween, H.Y.; Ming, D. W.; Moersch, J.E.; Morris, R.V.; Dobrea, E.Z.N.; Parker, T.J.; Proton, J.; Rice, J. W.; Seelos, F.; Soderblom, J.; Soderblom, L.A.; Sohl-Dickstein, J. N.; Sullivan, R.J.; Wolff, M.J.; Wang, A.

    2004-01-01

    Panoramic Camera images at Gusev crater reveal a rock-strewn surface interspersed with high- to moderate-albedo fine-grained deposits occurring in part as drifts or in small circular swales or hollows. Optically thick coatings of fine-grained ferric iron-rich dust dominate most bright soil and rock surfaces. Spectra of some darker rock surfaces and rock regions exposed by brushing or grinding show near-infrared spectral signatures consistent with the presence of mafic silicates such as pyroxene or olivine. Atmospheric observations show a steady decline in dust opacity during the mission, and astronomical observations captured solar transits by the martian moons, Phobos and Deimos, as well as a view of Earth from the martian surface.

  4. Identification and mapping of soil erosion areas in the Blue Nile-Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

    Directory of Open Access Journals (Sweden)

    M. El Haj Tahir

    2010-01-01

    Full Text Available This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.

  5. Identification and mapping of soil erosion areas in the Blue Nile-Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

    Science.gov (United States)

    El Haj Tahir, M.; Kääb, A.; Xu, C.-Y.

    2010-01-01

    This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM) is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.

  6. Transferring results from NIR-hyperspectral to NIR-multispectral imaging systems

    DEFF Research Database (Denmark)

    Calvini, Rosalba; Amigo Rubio, Jose Manuel; Ulrici, Alessandro

    2017-01-01

    commercially available filters matching the selected spectral regions, and used to calculate multivariate classification models with Partial Least Squares-Discriminant Analysis (PLS-DA) and sparse PLS-DA. Proper strategies for the definition of the training set and the selection of the most effective...

  7. Monitoring urban growth by using segmentation-classification of multispectral Landsat images in Izmit, Turkey.

    Science.gov (United States)

    Yildiz, Selin; Doker, Mehmet Fatih

    2016-07-01

    Assessing the spatial land use and land cover (LULC) information is essential for decision making and management of landscapes. In fact, LULC information has been changed dramatically in fast-growing cities. This results in wrong land use problems due to unplanned and uncontrolled urbanization. The planning and evaluating of limited natural resources under the pressure of a growing population can be possible when a precise land use management plan is established. Therefore, it is imperative to monitor continuous LULC changes for future planning. Remote sensing (RS) technique is used for determining changes in LULC in urban areas. In this study, we have focused on Izmit, which is one of a growing number of metropolitan cities where the impact of the spatial growing period on LULC has been assessed over the past 30 years by using RS data. We have utilized the segmentation process and supervised classification of Landsat satellite images for four different dates (1985, 1995, 2005, and 2015). The outcome of this research can be summarized by significant changes in the shares of urban areas and farmland LULC classes. The overall observed increase in urban area class is up to 2177 ha between 1985 and 2015 period and this dramatic change has resulted in the decline of 1211 ha of farmland. Another conclusion is that the new residential areas have been created to the north, south and east of Izmit during this period.

  8. Multi-spectral camera development

    CSIR Research Space (South Africa)

    Holloway, M

    2012-10-01

    Full Text Available stream_source_info Holloway_2012.pdf.txt stream_content_type text/plain stream_size 6209 Content-Encoding ISO-8859-1 stream_name Holloway_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Multi-Spectral Camera... Development 4th Biennial Conference Presented by Mark Holloway 10 October 2012 Fused image ? Red, Green and Blue Applications of the Multi-Spectral Camera ? CSIR 2012 Slide 2 Green and Blue, Near Infrared (IR) RED Applications of the Multi...

  9. Quantitative Retrieval of Soil Nutrient in Sandy Land Based on BJ-1 Multispectral Image

    Science.gov (United States)

    Wu, Junjun; Li, Zengyuan; Gao, Zhihai; Wang, Bengyu; Bai, Lina; Sun, Bin; Li, Changlong; Ding, Xiangyuan

    2014-11-01

    To research an indicator for sandy information, this paper conducts a study on soil nutrient in sandy land. Firstly, the difference of soil nutrient between sandy land and the other was analyzed. Secondly, the correlation between soil nutrient index and band was studied. Then the best inversion band and model was determined and evaluated. Finally, the distribution of soil nutrient was obtained. As the result indicated that the divergence of total nitrogen in different land was the maximum among the three nutrient indicators. With the development of desertification, total nitrogen declined dramatically. The correlation coefficient between each band and total nitrogen was relatively higher, and it reached 0.6. In addition, taking the reciprocal for the sum of three bands as the independent variable was an excellent choice, it could reflect the sandy information better than the single band. The quantitative retrieval model was checked by independent sample, and RMSE was 0.0407.

  10. Estimation of Critical Parameters in Concrete Production Using Multispectral Vision Technology

    DEFF Research Database (Denmark)

    Hansen, Michael Edberg; Ersbøll, Bjarne Kjær; Carstensen, Jens Michael;

    2005-01-01

    We analyze multispectral reflectance images of concrete aggregate material, and design computational measures of the important and critical parameters used in concrete production. The features extracted from the images are exploited as explanatory variables in regression models and used to predict...

  11. Classification of human carcinoma cells using multispectral imagery

    Science.gov (United States)

    Ćinar, Umut; Y. Ćetin, Yasemin; Ćetin-Atalay, Rengul; Ćetin, Enis

    2016-03-01

    In this paper, we present a technique for automatically classifying human carcinoma cell images using textural features. An image dataset containing microscopy biopsy images from different patients for 14 distinct cancer cell line type is studied. The images are captured using a RGB camera attached to an inverted microscopy device. Texture based Gabor features are extracted from multispectral input images. SVM classifier is used to generate a descriptive model for the purpose of cell line classification. The experimental results depict satisfactory performance, and the proposed method is versatile for various microscopy magnification options.

  12. Multispectral imaging observations of Neptune's cloud structure with Gemini-North

    Science.gov (United States)

    Irwin, P. G. J.; Teanby, N. A.; Davis, G. R.; Fletcher, L. N.; Orton, G. S.; Tice, D.; Hurley, J.; Calcutt, S. B.

    2011-11-01

    Observations of Neptune were made in September 2009 with the Gemini-North Telescope in Hawaii, using the NIFS instrument in the H-band covering the wavelength range 1.477-1.803 μm. Observations were acquired in adaptive optics mode and have a spatial resolution of approximately 0.15-0.25″. The observations were analysed with a multiple-scattering retrieval algorithm to determine the opacity of clouds at different levels in Neptune's atmosphere. We find that the observed spectra at all locations are very well fit with a model that has two thin cloud layers, one at a pressure level of ˜2 bar all over the planet and an upper cloud whose pressure level varies from 0.02 to 0.08 bar in the bright mid-latitude region at 20-40°S to as deep as 0.2 bar near the equator. The opacity of the upper cloud is found to vary greatly with position, but the opacity of the lower cloud deck appears remarkably uniform, except for localised bright spots near 60°S and a possible slight clearing near the equator. A limb-darkening analysis of the observations suggests that the single-scattering albedo of the upper cloud particles varies from ˜0.4 in regions of low overall albedo to close to 1.0 in bright regions, while the lower cloud is consistent with particles that have a single-scattering albedo of ˜0.75 at this wavelength, similar to the value determined for the main cloud deck in Uranus' atmosphere. The Henyey-Greenstein scattering particle asymmetry of particles in the upper cloud deck are found to be in the range g ˜ 0.6-0.7 (i.e. reasonably strongly forward scattering). Numerous bright clouds are seen near Neptune's south pole at a range of pressure levels and at latitudes between 60 and 70°S. Discrete clouds were seen at the pressure level of the main cloud deck (˜2 bar) at 60°S on three of the six nights observed. Assuming they are the same feature we estimate the rotation rate at this latitude and pressure to be 13.2 ± 0.1 h. However, the observations are not

  13. Multispectral fingerprinting for improved in vivo cell dynamics analysis

    Directory of Open Access Journals (Sweden)

    Cooper Cameron HJ

    2010-09-01

    Full Text Available Abstract Background Tracing cell dynamics in the embryo becomes tremendously difficult when cell trajectories cross in space and time and tissue density obscure individual cell borders. Here, we used the chick neural crest (NC as a model to test multicolor cell labeling and multispectral confocal imaging strategies to overcome these roadblocks. Results We found that multicolor nuclear cell labeling and multispectral imaging led to improved resolution of in vivo NC cell identification by providing a unique spectral identity for each cell. NC cell spectral identity allowed for more accurate cell tracking and was consistent during short term time-lapse imaging sessions. Computer model simulations predicted significantly better object counting for increasing cell densities in 3-color compared to 1-color nuclear cell labeling. To better resolve cell contacts, we show that a combination of 2-color membrane and 1-color nuclear cell labeling dramatically improved the semi-automated analysis of NC cell interactions, yet preserved the ability to track cell movements. We also found channel versus lambda scanning of multicolor labeled embryos significantly reduced the time and effort of image acquisition and analysis of large 3D volume data sets. Conclusions Our results reveal that multicolor cell labeling and multispectral imaging provide a cellular fingerprint that may uniquely determine a cell's position within the embryo. Together, these methods offer a spectral toolbox to resolve in vivo cell dynamics in unprecedented detail.

  14. Geologic analyses of LANDSAT-1 multispectral imagery of a possible power plant site employing digital and analog image processing. [in Pennsylvania

    Science.gov (United States)

    Lovegreen, J. R.; Prosser, W. J.; Millet, R. A.

    1975-01-01

    A site in the Great Valley subsection of the Valley and Ridge physiographic province in eastern Pennsylvania was studied to evaluate the use of digital and analog image processing for geologic investigations. Ground truth at the site was obtained by a field mapping program, a subsurface exploration investigation and a review of available published and unpublished literature. Remote sensing data were analyzed using standard manual techniques. LANDSAT-1 imagery was analyzed using digital image processing employing the multispectral Image 100 system and using analog color processing employing the VP-8 image analyzer. This study deals primarily with linears identified employing image processing and correlation of these linears with known structural features and with linears identified manual interpretation; and the identification of rock outcrops in areas of extensive vegetative cover employing image processing. The results of this study indicate that image processing can be a cost-effective tool for evaluating geologic and linear features for regional studies encompassing large areas such as for power plant siting. Digital image processing can be an effective tool for identifying rock outcrops in areas of heavy vegetative cover.

  15. Thermal surveillance of Cascade Range volcanoes using ERTS-1 multispectral scanner, aircraft imaging systems, and ground-based data communication platforms

    Science.gov (United States)

    Friedman, J. D.; Frank, D. G.; Preble, D.; Painter, J. E.

    1973-01-01

    A combination of infrared images depicting areas of thermal emission and ground calibration points have proved to be particularly useful in plotting time-dependent changes in surface temperatures and radiance and in delimiting areas of predominantly convective heat flow to the earth's surface in the Cascade Range and on Surtsey Volcano, Iceland. In an integrated experiment group using ERTS-1 multispectral scanner (MSS) and aircraft infrared imaging systems in conjunction with multiple thermistor arrays, volcano surface temperatures are relayed daily to Washington via data communication platform (DCP) transmitters and ERTS-1. ERTS-1 MSS imagery has revealed curvilinear structures at Lassen, the full extent of which have not been previously mapped. Interestingly, the major surface thermal manifestations at Lassen are aligned along these structures, particularly in the Warner Valley.

  16. Image fusion algorithm of multi-spectral and panchromatic images adopting region mutual information%采用区域互信息的多光谱与全色图像融合算法

    Institute of Scientific and Technical Information of China (English)

    王金玲; 贺小军; 宋克非

    2014-01-01

    For advancing the fusion algorithm quality of multi-spectral and panchromatic images, an image fusion algorithm of multi-spectral and panchromatic images was presented by region mutual information. Firstly the multi-spectral image was turned to HSV color space, and region segmentation was applied to V component by the method of watershed and region combination, and spectral distance was taken as the region combination estimation. Secondly the V component of multi-spectral image and panchromatic image were decomposed multi-resolution by nonsubsample Contourlet transform(NSCT), the region segmentation was mapping to the panchromatic image, and the multi-resolution decomposition coefficient was fused by calculating the mutual information of corresponding region to obtain the decomposition coefficient of fusion image. Lastly the fusion image reconfiguration was realized through NSCT inverse transform. The experimental result shows that the image fusion algorithm presented by this paper retains the spectral information of multi-spectral image adequately, meanwhile injects details information of panchromatic image as much as possible, which advances the edge characteristic of multi-spectral image effectively.%为了提高多光谱与全色图像融合算法质量,提出了一种采用区域互信息的多光谱与全色图像融合算法。首先将多光谱图像变换至 HSV 彩色空间,并采用分水岭与区域合并的方法对 V 分量进行区域分割,得到区域分割映射,欧氏光谱距离作为区域合并的测度。然后采用非下采样 Contourlet变换(Nonsubsample Contourlet Transform,NSCT)对多光谱图像 V 分量和全色图像进行多分辨率分解,将区域分割结果映射至全色图像,通过计算对应区域间的互信息对多分辨率分解系数进行融合,获得融合图像的分解系数,最后通过 NSCT 反变换实现融合图像重构。图像融合算法对比实验表明,文中融合算法在充分保

  17. Spatial Co-Registration of Ultra-High Resolution Visible, Multispectral and Thermal Images Acquired with a Micro-UAV over Antarctic Moss Beds

    Directory of Open Access Journals (Sweden)

    Darren Turner

    2014-05-01

    Full Text Available In recent times, the use of Unmanned Aerial Vehicles (UAVs as tools for environmental remote sensing has become more commonplace. Compared to traditional airborne remote sensing, UAVs can provide finer spatial resolution data (up to 1 cm/pixel and higher temporal resolution data. For the purposes of vegetation monitoring, the use of multiple sensors such as near infrared and thermal infrared cameras are of benefit. Collecting data with multiple sensors, however, requires an accurate spatial co-registration of the various UAV image datasets. In this study, we used an Oktokopter UAV to investigate the physiological state of Antarctic moss ecosystems using three sensors: (i a visible camera (1 cm/pixel, (ii a 6 band multispectral camera (3 cm/pixel, and (iii a thermal infrared camera (10 cm/pixel. Imagery from each sensor was geo-referenced and mosaicked with a combination of commercially available software and our own algorithms based on the Scale Invariant Feature Transform (SIFT. The validation of the mosaic’s spatial co-registration revealed a mean root mean squared error (RMSE of 1.78 pixels. A thematic map of moss health, derived from the multispectral mosaic using a Modified Triangular Vegetation Index (MTVI2, and an indicative map of moss surface temperature were then combined to demonstrate sufficient accuracy of our co-registration methodology for UAV-based monitoring of Antarctic moss beds.

  18. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  19. Multispectral imaging as a potential tool for seed health testing of spinach (Spinacia oleracea L.)

    DEFF Research Database (Denmark)

    Olesen, Merete Halkjær; Carstensen, Jens Michael; Boelt, Birte

    2011-01-01

    Seed health tests are time consuming and require substantial training for characterization of pathogenic fungi on seed. A new approach to use a multispectral vision system for identifying surface properties of different fungal infections has been tested in spinach (Spinacia oleracea L.) at Aarhus...... based on mean pixel intensity, Canonical Discriminant Analysis (CDA) and classification by Jeffries-Matusita (JM) distance illustrates that a combination of Near Infrared spectra (NIR) and Visual spectra (VIS) is able to identify uninfected seeds from infected seeds ranging from 80-100%. Classification....... and Stemphylium spp. needs further development before practical application....

  20. Lossless, Multi-Spectral Data Compressor for Improved Compression for Pushbroom-Type Instruments

    Science.gov (United States)

    Klimesh, Matthew

    2008-01-01

    A low-complexity lossless algorithm for compression of multispectral data has been developed that takes into account pushbroom-type multispectral imagers properties in order to make the file compression more effective.

  1. Use of a benzimidazole derivative BF-188 in fluorescence multispectral imaging for selective visualization of tau protein fibrils in the Alzheimer's disease brain.

    Science.gov (United States)

    Harada, Ryuichi; Okamura, Nobuyuki; Furumoto, Shozo; Yoshikawa, Takeo; Arai, Hiroyuki; Yanai, Kazuhiko; Kudo, Yukitsuka

    2014-02-01

    Selective visualization of amyloid-β and tau protein deposits will help to understand the pathophysiology of Alzheimer's disease (AD). Here, we introduce a novel fluorescent probe that can distinguish between these two deposits by multispectral fluorescence imaging technique. Fluorescence spectral analysis was performed using AD brain sections stained with novel fluorescence compounds. Competitive binding assay using [(3)H]-PiB was performed to evaluate the binding affinity of BF-188 for synthetic amyloid-β (Aβ) and tau fibrils. In AD brain sections, BF-188 clearly stained Aβ and tau protein deposits with different fluorescence spectra. In vitro binding assays indicated that BF-188 bound to both amyloid-β and tau fibrils with high affinity (K i  tau deposits as well as amyloid-β in the brain.

  2. Multispectral Microimager for Astrobiology

    Science.gov (United States)

    Sellar, R. Glenn; Farmer, Jack D.; Kieta, Andrew; Huang, Julie

    2006-01-01

    A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

  3. Multispectral Enhancement towards Digital Staining

    Directory of Open Access Journals (Sweden)

    Pinky A. Bautista

    2012-01-01

    Full Text Available Background: Digital staining can be considered as a special form of image enhancement wherein the concern is not only to increase the contrast between the background objects and objects of interest, but to also impart the colors that mark the objects’ unique reactions to a specific stain. In this paper, we extended the previously proposed multispectral enhancement methods such that the colors of the background pixels can also be changed.

  4. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  5. Semantic segmentation of multispectral overhead imagery

    Science.gov (United States)

    Prasad, Lakshman; Pope, Paul A.; Sentz, Kari

    2016-05-01

    Land cover classification uses multispectral pixel information to separate image regions into categories. Image segmentation seeks to separate image regions into objects and features based on spectral and spatial image properties. However, making sense of complex imagery typically requires identifying image regions that are often a heterogeneous mixture of categories and features that constitute functional semantic units such as industrial, residential, or commercial areas. This requires leveraging both spectral classification and spatial feature extraction synergistically to synthesize such complex but meaningful image units. We present an efficient graphical model for extracting such semantically cohesive regions. We employ an initial hierarchical segmentation of images into features represented as nodes of an attributed graph that represents feature properties as well as their adjacency relations with other features. This provides a framework to group spectrally and structurally diverse features, which are nevertheless semantically cohesive, based on user-driven identifications of features and their contextual relationships in the graph. We propose an efficient method to construct, store, and search an augmented graph that captures nonadjacent vicinity relationships of features. This graph can be used to query for semantic notional units consisting of ontologically diverse features by constraining it to specific query node types and their indicated/desired spatial interaction characteristics. User interaction with, and labeling of, initially segmented and categorized image feature graph can then be used to learn feature (node) and regional (subgraph) ontologies as constraints, and to identify other similar semantic units as connected components of the constraint-pruned augmented graph of a query image.

  6. Part task investigation of multispectral image fusion using gray scale and synthetic color night-vision sensor imagery for helicopter pilotage

    Science.gov (United States)

    Steele, Paul M.; Perconti, Philip

    1997-06-01

    Today, night vision sensor and display systems used in the pilotage or navigation of military helicopters are either long wave IR thermal sensors (8 - 12 microns) or image intensified, visible and near IR (0.6 - 0.9 microns), sensors. The sensor imagery is displayed using a monochrome phosphor on a Cathode Ray Tube or night vision goggle. Currently, there is no fielded capability to combine the best attributes of the emissive radiation sensed by the thermal sensor and the reflected radiation sensed by the image intensified sensor into a single fused image. However, recent advances in signal processing have permitted the real time image fusion and display of multispectral sensors in either monochrome or synthetic chromatic form. The merits of such signal processing is explored. A part task simulation using a desktop computer, video playback unit, and a biocular head mounted display was conducted. Response time and accuracy measures of test subject responses to visual perception tasks were taken. Subjective ratings were collected to determine levels of pilot acceptance. In general, fusion based formats resulted in better subject performance. The benefits of integrating synthetic color to fused imagery, however, is dependent on the color algorithm used, the visual task performed, and scene content.

  7. Characteristics of Xanthosoma sagittifolium roots during cooking, using physicochemical analysis, uniaxial compression, multispectral imaging and low field NMR spectroscopy

    DEFF Research Database (Denmark)

    Boakye, Abena Achiaa; Gudjónsdóttir, María; Skytte, Jacob Lercke

    2017-01-01

    properties. However, up to four fast-interacting water populations were observed in the roots, dependent on the root variety and their degree of gelatinization during cooking. Changes in the relaxation parameters indicated weak gelatinization of starch at approximately 80 °C in both varieties. However......, shorter relaxation times and a higher proportion of restricted water in the white variety indicated that this variety was slightly more sensitive towards gelatinization. A strong negative correlation existed between dry matter and all multispectral wavelengths >800 nm, suggesting the potential use...... of that spectral region for rapid analysis of dry matter and water content of the roots. The small, but significant differences in the structural and gelatinization characteristics of the two varieties indicated that they may not be equally suited for further processing, e.g. to flours or starches. Processors thus...

  8. Multi-spectral remote sensing image true color synthesis technique based on artificial target%基于人工靶标的多光谱遥感图像真彩色合成

    Institute of Scientific and Technical Information of China (English)

    黄红莲; 易维宁; 杜丽丽; 崔文煜; 曾献芳

    2016-01-01

    Multi-spectral true color synthesized images have the prospects of broad application in the interpretation of remote sensing image, target recognition and information processing etc. The technique of true color synthesis depends on the accuracy of the obtained tristimulus values CIE-XYZ, which is used to establish the right relationship between the system of camera′s RGB and human being′s visual color. So, a method of true color image synthesis based on the information of artificial target was proposed by laying the man-made targets when the satellite passes. And, the transformation matrix between camera′s RGB trichromatic system and human being′s visual color system was estimated from the reflectance spectrum of man-made targets. Eventually, the suitable true color correction model was established in the certain atmospheric conditions. Experiment of true color correction was conducted on the multi-spectral images of GF-1 satellite, and the results show that good color correction effects has been exhibited on even every image with different degrees of color′s richness.%多光谱真彩色合成图像在遥感图像解译判读、 目标识别和信息处理等领域具有广阔的应用前景.真彩色合成技术取决于获得准确的X、Y、Z三刺激值,以建立相机RGB三基色体系与人眼视觉颜色体系之间的关系.为此,提出了基于彩色目标光谱信息的多光谱图像真彩色合成方法,通过在卫星过顶时铺设人工靶标,利用实测的靶标反射率光谱,计算相机三基色体系RGB与人眼视觉颜色体系CIE-XYZ之间的转换矩阵,构建适用于一定大气条件下的真彩色校正模型.利用高分一号卫星多光谱图像进行真彩色校正实验的结果表明,该方法对色彩丰富度不同的图像均具有较好的颜色校正效果.

  9. Geometric calibration of lens and filter distortions for multispectral filter-wheel cameras.

    Science.gov (United States)

    Brauers, Johannes; Aach, Til

    2011-02-01

    High-fidelity color image acquisition with a multispectral camera utilizes optical filters to separate the visible electromagnetic spectrum into several passbands. This is often realized with a computer-controlled filter wheel, where each position is equipped with an optical bandpass filter. For each filter wheel position, a grayscale image is acquired and the passbands are finally combined to a multispectral image. However, the different optical properties and non-coplanar alignment of the filters cause image aberrations since the optical path is slightly different for each filter wheel position. As in a normal camera system, the lens causes additional wavelength-dependent image distortions called chromatic aberrations. When transforming the multispectral image with these aberrations into an RGB image, color fringes appear, and the image exhibits a pincushion or barrel distortion. In this paper, we address both the distortions caused by the lens and by the filters. Based on a physical model of the bandpass filters, we show that the aberrations caused by the filters can be modeled by displaced image planes. The lens distortions are modeled by an extended pinhole camera model, which results in a remaining mean calibration error of only 0.07 pixels. Using an absolute calibration target, we then geometrically calibrate each passband and compensate for both lens and filter distortions simultaneously. We show that both types of aberrations can be compensated and present detailed results on the remaining calibration errors.

  10. Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

    Directory of Open Access Journals (Sweden)

    Ahmad Chaddad

    Full Text Available This paper proposes to characterize the continuum of colorectal cancer (CRC using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma.In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG filter, discrete wavelets (DW and gray level co-occurrence matrices (GLCM. To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models.Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01. Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%.These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images.

  11. Infrared image processing devoted to thermal non-contact characterization-Applications to Non-Destructive Evaluation, Microfluidics and 2D source term distribution for multispectral tomography

    Science.gov (United States)

    Batsale, Jean-Christophe; Pradere, Christophe

    2015-11-01

    The cost of IR cameras is more and more decreasing. Beyond the preliminary calibration step and the global instrumentation, the infrared image processing is then one of the key step for achieving in very broad domains. Generally the IR images are coming from the transient temperature field related to the emission of a black surface in response to an external or internal heating (active IR thermography). The first applications were devoted to the so called thermal Non-Destructive Evaluation methods by considering a thin sample and 1D transient heat diffusion through the sample (transverse diffusion). With simplified assumptions related to the transverse diffusion, the in-plane diffusion and transport phenomena can be also considered. A general equation can be applied in order to balance the heat transfer at the pixel scale or between groups of pixels in order to estimate several fields of thermophysical properties (heterogeneous field of in-plane diffusivity, flow distributions, source terms). There is a lot of possible strategies to process the space and time distributed big amount of data (previous integral transformation of the images, compression, elimination of the non useful areas...), generally based on the necessity to analyse the derivative versus space and time of the temperature field. Several illustrative examples related to the Non-Destructive Evaluation of heterogeneous solids, the thermal characterization of chemical reactions in microfluidic channels and the design of systems for multispectral tomography, will be presented.

  12. Spatio-temporal modelling of biomass of intensively grazed perennial dairy pastures using multispectral remote sensing

    Science.gov (United States)

    Edirisinghe, Asoka; Clark, Dave; Waugh, Deanne

    2012-06-01

    Pasture biomass is a vital input for management of dairy systems in New Zealand. An accurate estimate of pasture biomass information is required for the calculation of feed budget, on which decisions are made for farm practices such as conservation, nitrogen use, rotational lengths and supplementary feeding leading to profitability and sustainable use of pasture resources. The traditional field based methods of measuring pasture biomass such as using rising plate metres (RPM) are largely inefficient in providing the timely information at the spatial extent and temporal frequency demanded by commercial environments. In recent times remote sensing has emerged as an alternative tool. In this paper we have examined the Normalised Difference Vegetation Index (NDVI) derived from medium resolution imagery of SPOT-4 and SPOT-5 satellite sensors to predict pasture biomass of intensively grazed dairy pastures. In the space and time domain analysis we have found a significant dependency of time over the season and no dependency of space across the scene at a given time for the relationship between NDVI and field based pasture biomass. We have established a positive correlation (81%) between the two variables in a pixel scale analysis. The application of the model on 2 selected farms over 3 images and aggregation of the predicted biomass to paddock scale has produced paddock average pasture biomass values with a coefficient of determination of 0.71 and a standard error of 260 kg DM ha-1 in the field observed range between 1500 and 3500 kg DM ha-1. This result indicates a high potential for operational use of remotely sensed data to predict pasture biomass of intensively grazed dairy pastures.

  13. Uav Multispectral Survey to Map Soil and Crop for Precision Farming Applications

    Science.gov (United States)

    Sonaa, Giovanna; Passoni, Daniele; Pinto, Livio; Pagliari, Diana; Masseroni, Daniele; Ortuani, Bianca; Facchi, Arianna

    2016-06-01

    New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

  14. UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS

    Directory of Open Access Journals (Sweden)

    G. Sona

    2016-06-01

    Full Text Available New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients. Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field, to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB and false color (NIR-RG images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

  15. Multi-spectral wide-field imaging for PplX PDT dosimetry of skin (Conference Presentation)

    Science.gov (United States)

    LaRochelle, Ethan; Chun, Hayden H.; Hasan, Tayyaba; Pogue, Brian W.; Maytin, Edward V.; Chapman, Michael S.; Davis, Scott C.

    2016-03-01

    Actinic Kertoses (AK) are common pre-cancerous lesions associated with sun-damaged skin. While generally benign, the condition can progress to squamous cell carcinoma (SCC) and is a particular concern for immunosuppressed patients who are susceptible to uncontrolled AK and SCC. Among the FDA-approved treatment options for AK, ALA-based photodynamic therapy is unique in that it is non-scarring and can be repeated on the same area. However, response rates vary widely due to variations in drug and light delivery, PpIX production, and tissue oxygenation. Thus, developing modalities to predict response is critical to enable patient-specific treatment-enhancing interventions. To that end, we have developed a wide-field spectrally-resolved fluorescence imaging system capable of red and blue light excitation. While blue light excites PpIX efficiently, poor photon penetration limits the image content to superficial layers of skin. Red light excitation, on the other hand, can reveal fluorescence information originating from deeper in tissue, which may provide relevant information about PpIX distribution. Our instrument illuminates the skin via a fiber-based ring illuminator, into which is coupled sequentially a white light source, and blue and red laser diodes. Light emitted from the tissue passes through a high-speed filter wheel with filters selected to resolve the PpIX emission spectrum. This configuration enables the use of spectral fitting to decouple PpIX fluorescence from background signal, improving sensitivity to low concentrations of PpIX. Images of tissue-simulating phantoms and animal models confirm a linear response to PpIX, and the ability to image sub-surface PpIX inaccessible with blue light using red excitation.

  16. Retrospective assessment of macrophytic communities in southern Lake Garda (Italy from in situ and MIVIS (Multispectral Infrared and Visible Imaging Spectrometer data

    Directory of Open Access Journals (Sweden)

    Claudia Giardino

    2012-01-01

    Full Text Available In situ and hyperspectral MIVIS (Multispectral Infrared and Visible Imaging Spectrometer images acquired over a period of 13 years are used to assess changes in macrophyte colonization patterns in the coastal zones of the Sirmione Peninsula in the southern part of Lake Garda (Italy. In situ data (abundance, cover density and diversity of macrophyte communities and MIVIS-derived maps of colonized substrates are analyzed by considering the variability of the main hydrological and physicochemical variables in order to indicate the main factors that explain the spatiotemporal variability of macrophyte communities. The results show a considerable modification in terms of macrophyte structural complexity and colonized areas. Almost 98% of macrophyte meadows (in particular communities with a density of over 70% are lost and subsequently replaced by moderate to extremely rare communities with density from 10% to 40%. Well-established submerged macrophytes are replaced by de-structured communities characterized by moderate to scarce density: on average lower than 30%. The study indicates that macrophyte distribution along the littoral zone of the Sirmione Peninsula is certainly linked to water transparency and water level fluctuation. The results also indicate that the worsening of eutrophication may be associated with the gradual disappearance of macrophyte meadows, but may also be accelerated by herbivorous aquatic birds grazing there. Lastly, the increasing frequency and number of catamaran tours could be considered a threat for the stability of these valuable communities.

  17. Survey of Hyperspectral and Multispectral Imaging Technologies (Etude sur les technologies d’imagerie hyperspectrale et multispectrale)

    Science.gov (United States)

    2007-05-01

    Prism-Grating-Prism Imaging Spectrograph 3-4 Figure 5 Basic Principle of the IMSS 3-5 Figure 6 Optical Scheme of Sagnac and Michelson Imaging...the dispersive techniques in imaging spectrometers applications is the Image Multi- Spectral Sensing ( IMSS ) technology, developed and patented by...Pacific Advanced Technology since 1992.The IMSS is based on the principle of diffractive optics; as such it is a combination of a diffractive imaging

  18. A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat

    NARCIS (Netherlands)

    Reyniers, M.; Walvoort, D.J.J.; Baardemaaker, De J.

    2006-01-01

    The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are

  19. D Land Cover Classification Based on Multispectral LIDAR Point Clouds

    Science.gov (United States)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  20. Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Palubinskas, G.

    2016-06-01

    Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods `better' satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald's protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property `better' should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

  1. Multispectral imaging system based on light-emitting diodes for the detection of melanomas and basal cell carcinomas: a pilot study

    Science.gov (United States)

    Delpueyo, Xana; Vilaseca, Meritxell; Royo, Santiago; Ares, Miguel; Rey-Barroso, Laura; Sanabria, Ferran; Puig, Susana; Pellacani, Giovanni; Noguero, Fernando; Solomita, Giuseppe; Bosch, Thierry

    2017-06-01

    This article proposes a multispectral system that uses the analysis of the spatial distribution of color and spectral features to improve the detection of skin cancer lesions, specifically melanomas and basal cell carcinomas. The system consists of a digital camera and light-emitting diodes of eight different wavelengths (414 to 995 nm). The parameters based on spectral features of the lesions such as reflectance and color, as well as others empirically computed using reflectance values, were calculated pixel-by-pixel from the images obtained. Statistical descriptors were calculated for every segmented lesion [mean (x˜), standard deviation (σ), minimum, and maximum]; descriptors based on the first-order statistics of the histogram [entropy (Ep), energy (En), and third central moment (μ3)] were also obtained. The study analyzed 429 pigmented and nonpigmented lesions: 290 nevi and 139 malignant (95 melanomas and 44 basal cell carcinomas), which were split into training and validation sets. Fifteen parameters were found to provide the best sensitivity (87.2% melanomas and 100% basal cell carcinomas) and specificity (54.5%). The results suggest that the extraction of textural information can contribute to the diagnosis of melanomas and basal cell carcinomas as a supporting tool to dermoscopy and confocal microscopy.

  2. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  3. 多光谱低空遥感图像光照辐射度校正%Radiometric calibration of low altitude multispectral remote sensing images

    Institute of Scientific and Technical Information of China (English)

    汪沛; 张俊雄; 兰玉彬; 周志艳; 罗锡文

    2014-01-01

    includes the development of micro UAV remote sensing platforms, information acquisition technology, image processing, and analysis and application of crop management, is reviewed in this paper. Micro UAV mainly has two types: rotor helicopter and fixed-wing aircraft. The rotor helicopter has been used more widely in acquiring information of the field, because it has the ability of taking off and landing vertically, fixed-point hovering, and slow cruising. Japan was the first country that has used the micro-UAV in agricultural production, and is one of the countries that have the best and most mature technologies in using remote UAV in agriculture today. The United States, Netherlands, Israel, and the United Kingdom also have a very good development all over the world. The beginning of research and development of micro UAV in China was much later than the other developed countries, but it has a booming development and grows rapidly. In this paper, parameters and characteristics of different models of the micro UAVs from eight companies in China have been listed for comparison. In remote sensing information acquiring systems, due to the limited load capacity of micro-UAV, digital camera and light-weight multispectral camera are two main instruments that are used on micro UAV for remote sensing information acquiring. How to adjust the posture of airborne remote sensors quickly and accurately so that the detecting target is always in the center of monitoring view, and how to realize remote controlling, image and information capturing, and transmission wirelessly are some of the focuses of UAV remote sensing technology at present. Limited by the stability and load capacity of the micro UAV, the remote sensing image always appears with the defects including a small view, large angle inclination, and serious irregular image overlap. So, solving the problem of correction, matching, mosaicing, fusing, and analyzing of the remote sensing images is one of the most important research

  4. Intraoperative Multispectral Fluorescence Imaging for the Detection of the Sentinel Lymph Node in Cervical Cancer : A Novel Concept

    NARCIS (Netherlands)

    Crane, Lucia M. A.; Themelis, George; Pleijhuis, Rick G.; Harlaar, Niels J.; Sarantopoulos, Athanasios; Arts, Henriette J. G.; van der Zee, Ate G. J.; Vasilis, Ntziachristos; van Dam, Gooitzen M.

    2011-01-01

    Real-time intraoperative near-infrared fluorescence (NIRF) imaging is a promising technique for lymphatic mapping and sentinel lymph node (SLN) detection. The purpose of this technical feasibility pilot study was to evaluate the applicability of NIRF imaging with indocyanin green (ICG) for the detec

  5. Multivariate Alteration Detection (MAD) and MAF Postprocessing in Multispectral, Bitemporal Image Data: New Approaches to Change Detection Studies

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut; Simpson, James J.

    1998-01-01

    type analyses of simple difference images. Case studies with AHVRR and Landsat MSS data using simple linear stretching and masking of the change images show the usefulness of the new MAD and MAF/MAD change detection schemes. Ground truth observations confirm the detected changes. A simple simulation...

  6. Multispectral tissue analysis and classification towards enabling automated robotic surgery

    Science.gov (United States)

    Triana, Brian; Cha, Jaepyeong; Shademan, Azad; Krieger, Axel; Kang, Jin U.; Kim, Peter C. W.

    2014-02-01

    Accurate optical characterization of different tissue types is an important tool for potentially guiding surgeons and enabling automated robotic surgery. Multispectral imaging and analysis have been used in the literature to detect spectral variations in tissue reflectance that may be visible to the naked eye. Using this technique, hidden structures can be visualized and analyzed for effective tissue classification. Here, we investigated the feasibility of automated tissue classification using multispectral tissue analysis. Broadband reflectance spectra (200-1050 nm) were collected from nine different ex vivo porcine tissues types using an optical fiber-probe based spectrometer system. We created a mathematical model to train and distinguish different tissue types based upon analysis of the observed spectra using total principal component regression (TPCR). Compared to other reported methods, our technique is computationally inexpensive and suitable for real-time implementation. Each of the 92 spectra was cross-referenced against the nine tissue types. Preliminary results show a mean detection rate of 91.3%, with detection rates of 100% and 70.0% (inner and outer kidney), 100% and 100% (inner and outer liver), 100% (outer stomach), and 90.9%, 100%, 70.0%, 85.7% (four different inner stomach areas, respectively). We conclude that automated tissue differentiation using our multispectral tissue analysis method is feasible in multiple ex vivo tissue specimens. Although measurements were performed using ex vivo tissues, these results suggest that real-time, in vivo tissue identification during surgery may be possible.

  7. Hyperspectral Imaging of Functional Patterns for Disease Assessment and Treatment Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Demos, S; Hattery, D; Hassan, M; Aleman, K; Little, R; Yarchoan, R; Gandjbakhche, A

    2003-12-05

    We have designed and built a six-band multi-spectral NIR imaging system used in clinical testing on cancer patients. From our layered tissue model, we create blood volume and blood oxygenation images for patient treatment monitoring.

  8. Embry-Riddle Aeronautical University multispectral sensor and data fusion laboratory: a model for distributed research and education

    Science.gov (United States)

    McMullen, Sonya A. H.; Henderson, Troy; Ison, David

    2017-05-01

    The miniaturization of unmanned systems and spacecraft, as well as computing and sensor technologies, has opened new opportunities in the areas of remote sensing and multi-sensor data fusion for a variety of applications. Remote sensing and data fusion historically have been the purview of large government organizations, such as the Department of Defense (DoD), National Aeronautics and Space Administration (NASA), and National Geospatial-Intelligence Agency (NGA) due to the high cost and complexity of developing, fielding, and operating such systems. However, miniaturized computers with high capacity processing capabilities, small and affordable sensors, and emerging, commercially available platforms such as UAS and CubeSats to carry such sensors, have allowed for a vast range of novel applications. In order to leverage these developments, Embry-Riddle Aeronautical University (ERAU) has developed an advanced sensor and data fusion laboratory to research component capabilities and their employment on a wide-range of autonomous, robotic, and transportation systems. This lab is unique in several ways, for example, it provides a traditional campus laboratory for students and faculty to model and test sensors in a range of scenarios, process multi-sensor data sets (both simulated and experimental), and analyze results. Moreover, such allows for "virtual" modeling, testing, and teaching capability reaching beyond the physical confines of the facility for use among ERAU Worldwide students and faculty located around the globe. Although other institutions such as Georgia Institute of Technology, Lockheed Martin, University of Dayton, and University of Central Florida have optical sensor laboratories, the ERAU virtual concept is the first such lab to expand to multispectral sensors and data fusion, while focusing on the data collection and data products and not on the manufacturing aspect. Further, the initiative is a unique effort among Embry-Riddle faculty to develop multi

  9. Lattice algebra approach to multispectral analysis of ancient documents.

    Science.gov (United States)

    Valdiviezo-N, Juan C; Urcid, Gonzalo

    2013-02-01

    This paper introduces a lattice algebra procedure that can be used for the multispectral analysis of historical documents and artworks. Assuming the presence of linearly mixed spectral pixels captured in a multispectral scene, the proposed method computes the scaled min- and max-lattice associative memories to determine the purest pixels that best represent the spectra of single pigments. The estimation of fractional proportions of pure spectra at each image pixel is used to build pigment abundance maps that can be used for subsequent restoration of damaged parts. Application examples include multispectral images acquired from the Archimedes Palimpsest and a Mexican pre-Hispanic codex.

  10. Landsat 1-5 Multispectral Scanner V1

    Data.gov (United States)

    National Aeronautics and Space Administration — Abstract: The Landsat Multispectral Scanner (MSS) was a sensor onboard Landsats 1 through 5 and acquired images of the Earth nearly continuously from July 1972 to...

  11. A Better Method for SAR Image and Multi-Spectral Image Fusion Based on Nonsubsampled Contourlet Transform (NSCT) and Genetic Algorithm%基于NSCT和遗传算法的SAR图像和多光谱图像融合

    Institute of Scientific and Technical Information of China (English)

    时丕丽; 郭雷; 李晖晖; 杨宁; 陈智慧

    2012-01-01

    SAR image or multispectral image has big difference in imaging mechanism and spectral characteristics. Sections 1 and 2 of the full paper explain our image fusion method mentioned in the title, which we believe is new and better than previous ones. Their cpre consists of : (1) by using the multi-scale, multi-direction ad spare decomposition capability of the NSCT, we transform the SAR and multispectral source images into NSCT domain; (2) we fuse the low frequencey coefficients by maximizing the regional entropy; then we calculate the values of the high-frequence subband regional correlation coefficients, divide them into different ranges according to the threshold values selected by genetic algorithm and fuse the correlation coefficients in different ranges, ( 3) we take the inverse NSCT transform, thus obtatining the fused images. Section 3 simulates our image fusion method; the simulation results , given in Fig. 4 and Table 1, and their analysis show preliminarily that our image fusion method performs indeed much better than the exsiting regional-based/pixel-based Contourlet/NSCT.%合成孔径雷达(SAR)图像与多光谱图像成像机理和光谱特性差异较大,一般的融合方法很难取得满意的融合结果.文章提出了一种基于Nonsuosampled Contourlet transform(NSCT)和遗传算法的融合算法,首先将经过预处理后的图像进行NSCT分解,低频系数采取区域信息熵最大的准则融合;高频子带计算区域相关性,对相关性在不同阈值范围内的系数进行融合,阈值的选取采用遗传算法进行搜索;最后对融合系数进行NSCT逆变换,得到融合结果.仿真结果表明该算法显著优于基于像素点和基于区域的融合方法.

  12. METHOD OF RADIOMETRIC DISTORTION CORRECTION OF MULTISPECTRAL DATA FOR THE EARTH REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    A. N. Grigoriev

    2015-07-01

    Full Text Available The paper deals with technologies of ground secondary processing of heterogeneous multispectral data. The factors of heterogeneous data include uneven illumination of objects on the Earth surface caused by different properties of the relief. A procedure for the image restoration of spectral channels by means of terrain distortion compensation is developed. The object matter of this paper is to improve the quality of the results during image restoration of areas with large and medium landforms. Methods. Researches are based on the elements of the digital image processing theory, statistical processing of the observation results and the theory of multi-dimensional arrays. Main Results. The author has introduced operations on multidimensional arrays: concatenation and elementwise division. Extended model description for input data about the area is given. The model contains all necessary data for image restoration. Correction method for multispectral data radiometric distortions of the Earth remote sensing has been developed. The method consists of two phases: construction of empirical dependences for spectral reflectance on the relief properties and restoration of spectral images according to semiempirical data. Practical Relevance. Research novelty lies in developme nt of the application theory of multidimensional arrays with respect to the processing of multispectral data, together with data on the topography and terrain objects. The results are usable for development of radiometric data correction tools. Processing is performed on the basis of a digital terrain model without carrying out ground works connected with research of the objects reflective properties.

  13. Enhanced multi-spectral imaging of live breast cancer cells using immunotargeted gold nanoshells and two-photon excitation microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Bickford, Lissett; Sun Jiantang; Fu, Kun; Lewinski, Nastassja; Nammalvar, Vengadesan; Chang, Joseph; Drezek, Rebekah [Department of Bioengineering, Rice University, Houston, TX 77005 (United States)], E-mail: drezek@rice.edu

    2008-08-06

    We demonstrate the capability of using immunotargeted gold nanoshells as contrast agents for in vitro two-photon microscopy. The two-photon luminescence properties of different-sized gold nanoshells are first validated using near-infrared excitation at 780 nm. The utility of two-photon microscopy as a tool for imaging live HER2-overexpressing breast cancer cells labeled with anti-HER2-conjugated nanoshells is then explored and imaging results are compared to normal breast cells. Five different imaging channels are simultaneously examined within the emission wavelength range of 451-644 nm. Our results indicate that under near-infrared excitation, superior contrast of SK-BR-3 cancer cells labeled with immunotargeted nanoshells occurs at an emission wavelength ranging from 590 to 644 nm. Luminescence from labeled normal breast cells and autofluorescence from unlabeled cancer and normal cells remain imperceptible under the same conditions.

  14. Enhanced multi-spectral imaging of live breast cancer cells using immunotargeted gold nanoshells and two-photon excitation microscopy

    Science.gov (United States)

    Bickford, Lissett; Sun, Jiantang; Fu, Kun; Lewinski, Nastassja; Nammalvar, Vengadesan; Chang, Joseph; Drezek, Rebekah

    2008-08-01

    We demonstrate the capability of using immunotargeted gold nanoshells as contrast agents for in vitro two-photon microscopy. The two-photon luminescence properties of different-sized gold nanoshells are first validated using near-infrared excitation at 780 nm. The utility of two-photon microscopy as a tool for imaging live HER2-overexpressing breast cancer cells labeled with anti-HER2-conjugated nanoshells is then explored and imaging results are compared to normal breast cells. Five different imaging channels are simultaneously examined within the emission wavelength range of 451-644 nm. Our results indicate that under near-infrared excitation, superior contrast of SK-BR-3 cancer cells labeled with immunotargeted nanoshells occurs at an emission wavelength ranging from 590 to 644 nm. Luminescence from labeled normal breast cells and autofluorescence from unlabeled cancer and normal cells remain imperceptible under the same conditions.

  15. Multiresolution Fusion of Remote Sensing Images Based on Resolution Degradation Model

    Institute of Scientific and Technical Information of China (English)

    LI Junli; SUN Jiabing; MAO Xi

    2005-01-01

    A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM+ panchromatic and multispectral images are used to assess the new method. Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS, PCA, Brovey, OWT(Orthogonal Wavelet Transform) and RWT(Redundant Wavelet Transform). The results show that the new method can keep almost the same spatial resolution as the panchromatic images, and the spectral effect of the new method is as good as those of wavelet-based methods.

  16. Radiometric Cross-Calibration of GF-4 in Multispectral Bands

    Directory of Open Access Journals (Sweden)

    Aixia Yang

    2017-03-01

    Full Text Available The GaoFen-4 (GF-4, launched at the end of December 2015, is China’s first high-resolution geostationary optical satellite. A panchromatic and multispectral sensor (PMS is onboard the GF-4 satellite. Unfortunately, the GF-4 has no onboard calibration assembly, so on-orbit radiometric calibration is required. Like the charge-coupled device (CCD onboard HuanJing-1 (HJ or the wide field of view sensor (WFV onboard GaoFen-1 (GF-1, GF-4 also has a wide field of view, which provides challenges for cross-calibration with narrow field of view sensors, like the Landsat series. A new technique has been developed and used to calibrate HJ-1/CCD and GF-1/WFV, which is verified viable. The technique has three key steps: (1 calculate the surface using the bi-directional reflectance distribution function (BRDF characterization of a site, taking advantage of its uniform surface material and natural topographic variation using Landsat Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI imagery and digital elevation model (DEM products; (2 calculate the radiance at the top-of-the atmosphere (TOA with the simulated surface reflectance using the atmosphere radiant transfer model; and (3 fit the calibration coefficients with the TOA radiance and corresponding Digital Number (DN values of the image. This study attempts to demonstrate the technique is also feasible to calibrate GF-4 multispectral bands. After fitting the calibration coefficients using the technique, extensive validation is conducted by cross-validation using the image pairs of GF-4/PMS and Landsat-8/OLI with similar transit times and close view zenith. The validation result indicates a higher accuracy and frequency than that given by the China Centre for Resources Satellite Data and Application (CRESDA using vicarious calibration. The study shows that the new technique is also quite feasible for GF-4 multispectral bands as a routine long-term procedure.

  17. Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

    Science.gov (United States)

    Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

    2010-07-02

    This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude.

  18. Application of multispectral systems for the diagnosis of plant diseases

    Science.gov (United States)

    Feng, Jie; Liao, Ningfang; Wang, Guolong; Luo, Yongdao; Liang, Minyong

    2008-03-01

    Multispectral imaging technique combines space imaging and spectral detecting. It can obtain the spectral information and image information of object at the same time. Base on this concept, A new method proposed multispectral camera system to demonstrated plant diseases. In this paper, multispectral camera was used as image capturing device. It consists of a monochrome CCD camera and 16 narrow-band filters. The multispectral images of Macbeth 24 color patches are captured under the illumination of incandescent lamp in this experiment The 64 spectral reflectances of each color patches are calculated using Spline interpolation from 400 to 700nm in the process. And the color of the object is reproduced from the estimated spectral reflectance. The result for reproduction is contrast with the color signal using X-rite PULSE spectrophotometer. The average and maximum ΔΕ * ab are 9.23 and 12.81. It is confirmed that the multispectral system realizes the color reproduction of plant diseases from narrow-band multispectral image.

  19. 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

  20. Visualizing the size, shape, morphology, and localized surface plasmon resonance of individual gold nanoshells by near-infrared multispectral imaging microscopy.

    Science.gov (United States)

    Mejac, Irena; Bryan, William W; Lee, T Randall; Tran, Chieu D

    2009-08-15

    We have successfully utilized the newly developed near-infrared multispectral imaging (NIR-MSI) microscope to observe and measure directly the localized surface plasmon absorption (LSPR) of individual gold nanoshells. The NIR-MSI is suited for this task because it can simultaneously record spectral and spatial information of a sample with high sensitivity (single pixel resolution) and high spatial resolution (approximately 0.9 microm/pixel). Importantly, the LSPR of individual nanoshells measured by the NIR-MSI microscope agrees well with the spectra calculated theoretically using Mie scattering for the nanoshells (i.e., nanoshells with silica cores approximately 800 nm in diameter and gold shell thicknesses of approximately 35 nm). Additionally, the NIR-MSI microscope enables measurement of LSPR at different positions within a single nanoshell. LSPR spectra were found to be distinct at various positions within a single nanoshell. Since LSPR spectra are known to depend on the shape and morphology of the nanoshells, these results seem to suggest that the individual nanoshells are not smooth and well-defined, but are rather rough and inhomogeneous. The LSPR spectra of single nanoshells in several different solvents were also examined using NIR-MSI and were found to depend on the dielectric constant of the medium. However, the relationship was discovered to be more complex than simply following the Drude equation. Specifically, when (lambda(max)/fwhm)(2) values of LSPR for single gold nanoshells were plotted as a function of 2n(2) (or 2epsilon) for nanoshells in six different solvents, a linear relationship was found for only three solvents: D(2)O, acetonitrile-d(3), and ethyl acetate. Acetone-d(6) showed a slight deviation, whereas formamide and pyridine-d(5) exhibited distinctly different correlations.

  1. Classification of Histology Sections via Multispectral Convolutional Sparse Coding.

    Science.gov (United States)

    Zhou, Yin; Chang, Hang; Barner, Kenneth; Spellman, Paul; Parvin, Bahram

    2014-06-01

    Image-based classification of histology sections plays an important role in predicting clinical outcomes. However this task is very challenging due to the presence of large technical variations (e.g., fixation, staining) and biological heterogeneities (e.g., cell type, cell state). In the field of biomedical imaging, for the purposes of visualization and/or quantification, different stains are typically used for different targets of interest (e.g., cellular/subcellular events), which generates multi-spectrum data (images) through various types of microscopes and, as a result, provides the possibility of learning biological-component-specific features by exploiting multispectral information. We propose a multispectral feature learning model that automatically learns a set of convolution filter banks from separate spectra to efficiently discover the intrinsic tissue morphometric signatures, based on convolutional sparse coding (CSC). The learned feature representations are then aggregated through the spatial pyramid matching framework (SPM) and finally classified using a linear SVM. The proposed system has been evaluated using two large-scale tumor cohorts, collected from The Cancer Genome Atlas (TCGA). Experimental results show that the proposed model 1) outperforms systems utilizing sparse coding for unsupervised feature learning (e.g., PSD-SPM [5]); 2) is competitive with systems built upon features with biological prior knowledge (e.g., SMLSPM [4]).

  2. MRI and PET images fusion based on human retina model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The diagnostic potential of brain positron emission tomography (PET) imaging is limited by low spatial resolution.For solving this problem we propose a technique for the fusion of PET and MRI images. This fusion is a trade-off between the spectral information extracted from PET images and the spatial information extracted from high spatial resolution MRI. The proposed method can control this trade-off. To achieve this goal, it is necessary to build a multiscale fusion model, based on the retinal cell photoreceptors model. This paper introduces general prospects of this model, and its application in multispectral medical image fusion. Results showed that the proposed method preserves more spectral features with less spatial distortion.transform methods, the best spectral and spatial quality is only achieved simultaneously with the proposed feature-based data fusion method. This method does not require resampling images, which is an advantage over the other methods, and can perform in any aspect ratio between the pixels of MRI and PET images.

  3. Multispectral videography for site-specific farm management

    Science.gov (United States)

    Anderson, Gerald L.; Yang, C.

    1996-11-01

    Researchers are expending considerable effort to develop the technology and methodology needed to identify and map within-field management zones for site-specific farming. Much of the research has focused on the use of either a high-density geographically referenced grid of soil samples or mechanical yield sensor measurements that record geographic positions and production levels. In either case, complex spatial models are generally used to extrapolate the various soil variables and production level information across the entire field. Both procedures produce a wealth of information, however, the analysis of soil samples tend to be quite expensive and the accuracy of mechanical yield measurements does vary. This study represents an ongoing effort designed to evaluate remote sensing as a tool for determining within field management zones. Color-infrared aerial photography and multispectral videography were used in concert to map and stratify two grain sorghum fields into regions or zones of homogeneous spectral response. A limited number of soil and plant samples were acquired to characterize the biotic and edaphic conditions within each zone. Results obtained during the first year of the study indicated that multispectral video can be used to develop within field management zones. Simple univariate analysis indicated that soil pH, Ca, and Fe were important variables affecting yield. Analysis of the yield data indicated that the economic returns from 17% of the first field and 20% of the second field were insufficient to recoup planting costs. Multispectral video also proved instrumental in modeling the spatial variability of yield. A significant negative correlation (r2 greater than 0.90) was obtained between the red spectral band and crop yields for both fields. Stratification, in this case using image data, reduces the number of samples required to characterize a field by reducing the variance associated within each stratum. Image data also provided a

  4. Multi-spectral photoacoustic elasticity tomography

    Science.gov (United States)

    Liu, Yubin; Yuan, Zhen

    2016-01-01

    The goal of this work was to develop and validate a spectrally resolved photoacoustic imaging method, namely multi-spectral photoacoustic elasticity tomography (PAET) for quantifying the physiological parameters and elastic modulus of biological tissues. We theoretically and experimentally examined the PAET imaging method using simulations and in vitro experimental tests. Our simulation and in vitro experimental results indicated that the reconstructions were quantitatively accurate in terms of sizes, the physiological and elastic properties of the targets. PMID:27699101

  5. Multispectral and Texture Feature Application in Image-Object Analysis of Summer Vegetation in Eastern Tajikistan Pamirs

    Directory of Open Access Journals (Sweden)

    Eric Ariel L. Salas

    2016-01-01

    Full Text Available We tested the Moment Distance Index (MDI in combination with texture features for the summer vegetation mapping in the eastern Pamir Mountains, Tajikistan using the 2014 Landsat OLI (Operational Land Imager image. The five major classes identified were sparse vegetation, medium-dense vegetation, dense vegetation, barren land, and water bodies. By utilizing object features in a random forest (RF classifier, the overall classification accuracy of the land cover maps were 92% using a set of variables including texture features and MDI, and 84% using a set of variables including texture but without MDI. A decrease of the Kappa statistics, from 0.89 to 0.79, was observed when MDI was removed from the set of predictor variables. McNemar’s test showed that the increase in the classification accuracy due to the addition of MDI was statistically significant (p < 0.05. The proposed method provides an effective way of discriminating sparse vegetation from barren land in an arid environment, such as the Pamir Mountains.

  6. Illuminating cellular structure and function in the early secretory pathway by multispectral 3D imaging in living cells

    Science.gov (United States)

    Rietdorf, Jens; Stephens, David J.; Squire, Anthony; Simpson, Jeremy; Shima, David T.; Paccaud, Jean-Pierre; Bastiaens, Philippe I.; Pepperkok, Rainer

    2000-04-01

    Membrane traffic between the endoplasmic reticulum (ER) and the Golgi complex is regulated by two vesicular coat complexes, COPII and COPI. COPII has been implicated in selective packaging of anterograde cargo into coated transport vesicles budding from the ER. COPI-coated vesicles are proposed to mediate recycling of proteins from the Golgi complex to the ER. We have used multi spectral 3D imaging to visualize COPI and COPII behavior simultaneously with various GFP-tagged secretory markers in living cells. This shows that COPII and COPI act sequentially whereby COPI association with anterograde transport complexes is involved in microtubule-based transport and the en route segregation of ER recycling molecules from secretory cargo within TCS in transit to the Golgi complex. We have also investigated the possibility to discriminate spectrally GFP fusion proteins by fluorescence lifetime imaging. This shows that at least two, and possibly up to three GFP fusion proteins can be discriminated and localized in living cells using a single excitation wavelength and a single broad band emission filter.

  7. Photothermal multispectral image cytometry for quantitative histology of nanoparticles and micrometastasis in intact, stained and selectively burned tissues.

    Science.gov (United States)

    Nedosekin, Dmitry A; Shashkov, Evgeny V; Galanzha, Ekaterina I; Hennings, Leah; Zharov, Vladimir P

    2010-11-01

    There is a rapidly growing interest in the advanced analysis of histological data and the development of appropriate detection technologies in particular for mapping of nanoparticle distributions in tissue in nanomedicine applications. We evaluated photothermal (PT) scanning cytometry for color-coded imaging, spectral identification, and quantitative detection of individual nanoparticles and abnormal cells in histological samples with and without staining. Using this tool, individual carbon nanotubes, gold nanorods, and melanoma cells with intrinsic melanin markers were identified in unstained (e.g. sentinel lymph nodes) and conventionally-stained tissues. In addition, we introduced a spectral burning technique for histology through selective laser bleaching areas with nondesired absorption background and nanobubble-based PT signal amplification. The obtained data demonstrated the promise of PT cytometry in the analysis of low-absorption samples and mapping of various individual nanoparticles' distribution that would be impossible with existing assays. Comparison of PT cytometry and photoacoustic (PA) cytometry previously developed by us, revealed that these methods supplement each other with a sensitivity advantage (up to 10-fold) of contactless PT technique in assessment of thin (≤100 μm) histological samples, while PA imaging provides characterization of thicker samples which, however, requires an acoustic contact with transducers. A potential of high-speed integrated PT-PA cytometry for express histology and immunohistochemistry of both intact and stained heterogeneous tissues with high sensitivity at the zepromolar concentration level is further highlighted.

  8. Design and implementation of digital airborne multispectral camera system

    Science.gov (United States)

    Lin, Zhaorong; Zhang, Xuguo; Wang, Li; Pan, Deai

    2012-10-01

    The multispectral imaging equipment is a kind of new generation remote sensor, which can obtain the target image and the spectra information simultaneously. A digital airborne multispectral camera system using discrete filter method had been designed and implemented for unmanned aerial vehicle (UAV) and manned aircraft platforms. The digital airborne multispectral camera system has the advantages of larger frame, higher resolution, panchromatic and multispectral imaging. It also has great potential applications in the fields of environmental and agricultural monitoring and target detection and discrimination. In order to enhance the measurement precision and accuracy of position and orientation, Inertial Measurement Unit (IMU) is integrated in the digital airborne multispectral camera. Meanwhile, the Temperature Control Unit (TCU) guarantees that the camera can operate in the normal state in different altitudes to avoid the window fogging and frosting which will degrade the imaging quality greatly. Finally, Flying experiments were conducted to demonstrate the functionality and performance of the digital airborne multispectral camera. The resolution capability, positioning accuracy and classification and recognition ability were validated.

  9. The Multispectral Microscopic Imager: Integrating Microimaging with Spectroscopy for the In-Situ Exploration of the Moon

    Science.gov (United States)

    Nunez, J. I.; Farmer, J. D.; Sellar, R. G.; Allen, Carlton C.

    2010-01-01

    To maximize the scientific return, future robotic and human missions to the Moon will need to have in-situ capabilities to enable the selection of the highest value samples for returning to Earth, or a lunar base for analysis. In order to accomplish this task efficiently, samples will need to be characterized using a suite of robotic instruments that can provide crucial information about elemental composition, mineralogy, volatiles and ices. Such spatially-correlated data sets, which place mineralogy into a microtextural context, are considered crucial for correct petrogenetic interpretations. . Combining microscopic imaging with visible= nearinfrared reflectance spectroscopy, provides a powerful in-situ approach for obtaining mineralogy within a microtextural context. The approach is non-destructive and requires minimal mechanical sample preparation. This approach provides data sets that are comparable to what geologists routinely acquire in the field, using a hand lens and in the lab using thin section petrography, and provide essential information for interpreting the primary formational processes in rocks and soils as well as the effects of secondary (diagenetic) alteration processes. Such observations lay a foundation for inferring geologic histories and provide "ground truth" for similar instruments on orbiting satellites; they support astronaut EVA activities and provide basic information about the physical properties of soils required for assessing associated health risks, and are basic tools in the exploration for in-situ resources to support human exploration of the Moon.

  10. Design of a multispectral digital colposcope

    Science.gov (United States)

    MacKinnon, N. B.; Cardeno, M.; Au, S.; MacAulay, C. E.; Pikkula, B. M.; Serachitopol, D.; Follen, M.; Park, S. Y.; Richards-Kortum, R.

    2007-02-01

    Measurement quality assurance plans for optical devices should be a mandatory part of grant funding submissions and should explicitly affect scoring during review. These should include calibration strategy, standards selection strategy, performance verification plan, performance validation plan and thorough preclinical performance validation. A multispectral digital colposcope (MDC) has been designed to collect image data from patients as part of an NIH sponsored clinical trial, based on a technology assessment model. Calibration strategy, standards selection and performance verification methods are presented that may be used as a template for smaller groups or more limited studies. With the MDC, red green and blue fluorescence images are captured under ultraviolet light excitation and red and green images are captured under blue light excitation. Red, green and blue reflectance images are captured under broadband white light illumination from a metal halide lamp in three modes - ordinary reflectance, and with polarized illumination in combination with parallel and cross-polarized filtered imaging. The highly automated system was designed to collect images of the cervix prior to and following the application of acetic acid. Three systems have been built and will be operated in clinics in Vancouver, Canada, Houston, Texas and other locations in the developed and developing world including Nigeria. The system is designed with a comprehensive set of calibration and performance verification standards, based on our experience with large scale multi-center spectroscopy clinical trials and measurements are made frequently prior to and following patient measurements. Automated performance verification procedures are being designed based on measurements made during pilot studies to facilitate larger clinical trials.

  11. Multi-spectral pyrometry—a review

    Science.gov (United States)

    Araújo, António

    2017-08-01

    In pyrometry measurements, the unknown target emissivity is a critical source of uncertainty, especially when the emissivity is low. Aiming to overcome this problem, various multi-spectral pyrometry systems and processing techniques have been proposed in the literature. Basically, all multi-spectral systems are based on the same principle: the radiation emitted by the target is measured at different channels having different spectral characteristics, and the emissivity is modelled as a function of wavelength with adjustable parameters to be obtained empirically, resulting in a system of equations whose solution is the target temperature and the parameters of the emissivity function. The present work reviews the most important multi-spectral developments. Concerning the spectral width of the measurement channels, multi-spectral systems are divided into multi-wavelength (monochromatic channels) and multi-band (wide-band channels) systems. Regarding the number of unknowns and equations (one equation per channel), pyrometry systems can either be determined (same number of unknowns and equations, having a unique solution) or overdetermined (more equations than unknowns, to be solved by least-squares). Generally, higher-order multi-spectral systems are overdetermined, since the uncertainty of the solutions obtained from determined systems increases as the number of channels increases, so that determined systems normally have less than four channels. In terms of the spectral characteristics of the measurement channels, narrow bands, far apart from each other and shifted towards lower wavelengths, seem to provide more accurate solutions. Many processing techniques have been proposed, but they strongly rely on the relationship between emissivity and wavelength, which is, in turn, strongly dependent on the characteristics of a particular target. Several accurate temperature and/or emissivity results have been reported, but no universally accepted multi-spectral technique has

  12. Multispectral colormapping using penalized least square regression

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

    2010-01-01

    based multispectral system with a total of 11 channels in the visible area. To obtain interpretable models, the method estimates the projection coefficients with regard to their neighbors as well as the target. This results in relatively smooth coefficient curves which are correlated with the CIE...

  13. Combining kriging, multispectral and multimodal microscopy to resolve malaria-infected erythrocyte contents.

    Science.gov (United States)

    Dabo-Niang, S; Zoueu, J T

    2012-09-01