Search results for "SPECTRA"

showing 10 items of 3542 documents

A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization

2011

International audience; We present a new method for the visualization of spectral images, based on a selection of three relevant spectral channels to build a Red-Green-Blue composite. Band selection is achieved by means of information measures at the first, second and third orders. Irrelevant channels are preliminarily removed by means of a center-surround entropy comparison. A visualization-oriented spectrum segmentation based on the use of color matching functions allows for computational ease and adjustment of the natural rendering. Results from the proposed method are presented and objectively compared to four other dimensionality reduction techniques in terms of naturalness and informa…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesBand SelectionComputer science0211 other engineering and technologies02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesRendering (computer graphics)Spectrum SegmentationData visualization[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingColor Matching FunctionsEntropy (information theory)Computer visionSegmentationElectrical and Electronic Engineering021101 geological & geomatics engineering0105 earth and related environmental sciencesVisualizationInformation Measuresbusiness.industryDimensionality reductionPattern recognitionImage segmentationVisualizationMulti/hyperspectral imageryGeneral Earth and Planetary SciencesArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Comparison of Bathymetric estimation using different satellite images in coastal sea waters

2009

Bathymetric estimation can be obtained from multispectral satellite images for shallow waters. The method is based on the rotation of a pair of spectral bands. One of the resulting images is depth-dependent. Therefore several pixels corresponding to different depths are required to numerically evaluate the linear relation between the pixel values and the real depth for a training area. The aim of this study is to compare, for one bathymetric estimation method and one mesotrophic site, the results of depth estimation with a large panel of satellite and aerial images: CASI, QUICKBIRD, CHRIS PROBA, ETM, HYPERION and MeRIS. For each image the pair of spectral bands chosen to compute the bathyme…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesPixelAerial survey[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral image0211 other engineering and technologies02 engineering and technologySpectral bands01 natural sciencesMultispectral pattern recognition[SPI]Engineering Sciences [physics][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer Science::Computer Vision and Pattern RecognitionGeneral Earth and Planetary SciencesBathymetry14. Life underwaterQuantization (image processing)Image resolution[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeologyComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Discrimination of coral reflectance spectra in the Red Sea

2002

Benthic populations can potentially be mapped from remotely acquired spectral imagery, provided that they have distinctive reflectance signatures. We examined the spectral reflectance characteristics of 14 genera of Red Sea coral using a submersible spectroradiometer. Coral spectra varied quantitatively and qualitatively over the depth interval 5–20 m. Tissue pigment content had a larger effect on reflectance than colony morphology. Ten coral genera could be discriminated with a statistical probability of 52% on the basis of their absolute reflectance. Six groups of two to three coral genera could be discriminated with a probability of 60% on the basis of their rates of change in reflectanc…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciences[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCoral0211 other engineering and technologies02 engineering and technologyAquatic Science01 natural sciencesSpectral line[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing14. Life underwaterComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographygeography.geographical_feature_categoryfungiPigment compositionCoral reefReflectivityWavelengthSpectroradiometerBenthic zone[SDE]Environmental SciencesEnvironmental science[SDE.BE]Environmental Sciences/Biodiversity and Ecology
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An Impulse Response Model for the 60 Ghz Channel Based on Spectral Techniques of alpha-stable Processes

2007

International audience; In order to make realistic simulations of the radio propagation mechanism in ultra-wide band channels, an appropriate model is needed. In this paper we propose a new technique to model the impulse response of the 60 Ghz channel. This new approach is based on the spectral analysis of alpha-stable processes. Our new model presents many advantages: firstly, the channel is characterized only by a one deterministic function (spectral density) in the place of four parameters. Secondly, the estimations procedure deals directly with the measured transfer functions which avoids loosing information in data pretreatment. Finally, an estimation of the spectral measure permits to…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingTransfer function[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0203 mechanical engineering[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0202 electrical engineering electronic engineering information engineeringSpectral analysisTransient response[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]Impulse response[STAT.AP]Statistics [stat]/Applications [stat.AP]business.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Spectral density020302 automobile design & engineering020206 networking & telecommunications[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH][ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Radio propagationTelecommunicationsbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmCommunication channel
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Multispectral Imaging using a Stereo Camera: Concept, Design and Assessment

2011

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…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-836002 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural scienceslcsh:Telecommunicationlaw.inventionMultispectral pattern recognitionstereo camera010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawCamera auto-calibrationlcsh:TK5101-67200103 physical sciences0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionreflectance estimationPixelColor imagebusiness.industrylcsh:ElectronicsReflectivityLens (optics)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]Stereo cameraComputer stereo visionCamera resectioning
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Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images

2011

International audience; In this paper, we introduce a new approach for color visu- alization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discon- tinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes' centroids. Results on two hyperspec- tral datasets illustrate the efficiency of…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulation0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionSegmentationspectral imageseducationspatially variantvisualization021101 geological & geomatics engineeringdimensionality reductioneducation.field_of_studyPixelbusiness.industryDimensionality reductionHyperspectral imagingIndependent component analysisVisualizationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusinessDistance transform[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Validation of a 2D multispectral camera: application to dermatology/cosmetology on a population covering five skin phototypes

2011

International audience; This paper presents the validation of a new multispectral camera specifically developed for dermatological application based on healthy participants from five different Skin PhotoTypes (SPT). The multispectral system provides images of the skin reflectance at different spectral bands, coupled with a neural network-based algorithm that reconstructs a hyperspectral cube of cutaneous data from a multispectral image. The flexibility of neural network based algorithm allows reconstruction at different wave ranges. The hyperspectral cube provides both high spectral and spatial information. The study population involves 150 healthy participants. The participants are classif…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulationMultispectral imageSkin imaging system[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingspectral reflectance01 natural sciencesspectral reconstructionMultispectral pattern recognition010309 optics030207 dermatology & venereal diseases03 medical and health sciencesFitzpatrick scale0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical scienceseducationRemote sensingvalidationeducation.field_of_studyHyperspectral imagingSpectral bandshyperspectral cubemultispectral imageFace (geometry)Cube[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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An evaluation framework and a benchmark for multi/hyperspectral image compression

2011

International audience; This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencebusiness.industryMultispectral image0211 other engineering and technologiesPattern recognition02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcompressionwaveletsWavelet[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingCompression (functional analysis)Hyperspectral image compression0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinessDecorrelation[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMulti/hyperspectral images021101 geological & geomatics engineeringImage compression
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Source separation on hyperspectral cube applied to dermatology

2010

International audience; This paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source compone…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingMaterials science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingHuman skin[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciences010309 opticsAbsorbanceOptics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringSource separationSource separation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPolynomial regressionIndependent Component Analysis.Spectral reflectanceKurtosisintegumentary systembusiness.industryNon-GaussianityHyperspectral imagingIndependent component analysisIndependent Component Analysis3. Good healthSkin patch020201 artificial intelligence & image processingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingVisible spectrum
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Integration of 3D and multispectral data for cultural heritage applications: Survey and perspectives

2013

International audience; Cultural heritage is increasingly put through imaging systems such as multispectral cameras and 3D scanners. Though these acquisition systems are often used independently, they collect complementary information (spectral vs. spatial) used for the study, archiving and visualization of cultural heritage. Recording 3D and multispectral data in a single coordinate system enhances the potential insights in data analysis. Wepresent the state of the art of such acquisition systems and their applications for the study of cultural her- itage. Wealso describe existing registration techniques that can be used to obtain 3D models with multispec- tral texture and explore the idea…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingRegistration[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION3d model[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologycomputer.software_genre3D digitizationMultispectral imaging[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability0202 electrical engineering electronic engineering information engineering[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimedia020207 software engineeringData fusionSensor fusionData scienceVisualizationCultural heritagePhotogrammetryPhotogrammetrySignal ProcessingCultural heritage020201 artificial intelligence & image processingComputer Vision and Pattern Recognition[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingcomputerImage and Vision Computing
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