Search results for "Signal"

showing 10 items of 6924 documents

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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High-end colorimetric display characterization using an adaptive training set

2011

A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the int…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingColor spaceColor management01 natural scienceslaw.invention010309 opticsPolyharmonic spline[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer visionElectrical and Electronic EngineeringComputingMethodologies_COMPUTERGRAPHICSbusiness.industryColor correctionAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsKernel (image processing)RGB color model020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSmoothingInterpolation
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Needle-shape quality control by shadowgraphic image processing

2011

International audience; We propose a needle-shape quality-control method. To this end, we have devised a new acquisition system that combines a camera and a backlight. Needle measurements are carried out at a micrometric scale using shadowgraphic image processing. Our method not only distinguishes good needles from bad ones, but also allows classifying flawed needles into various categories of defects. This classification is important because some categories of defects can affect the entire production, whereas others do not. The results of our needle-shape quality-control method are validated using real samples directly off the manufacturing line. Needles are correctly classified at >97%, a…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceImage qualityImage processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyBacklightMathematical morphology[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingneedle020204 information systems[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionquality controlImage sensorRadon transformbusiness.industryGeneral EngineeringImage segmentationAtomic and Molecular Physics and Opticsimage processingmetrology[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingShape analysis (digital geometry)Optical Engineering
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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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Reaction-Diffusion Network For Geometric Multiscale High Speed Image Processing

2010

International audience; In the framework of heavy mid-level processing for high speed imaging, a nonlinear bi-dimensional network is proposed, allowing the implementation of active curve algorithms. Usually this efficient type of algorithm is prohibitive for real-time image processing due to its calculus charge and the inadequate structure for the use of serial or parallel architectures. Another kind of implementation philosophy is proposed here, by considering the active curve generated by a propagation phenomenon inspired from biological modeling. A programmable nonlinear reaction-diffusion system is proposed under front control and technological constraints. Geometric multiscale processin…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceNonlinear signal processingImage processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingType (model theory)Multiscale geometryComputational scienceImage analysisNonlinear signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingReaction–diffusion systemDigital image processing0202 electrical engineering electronic engineering information engineeringComputer visionStructure (mathematical logic)Biological modelingbusiness.industry020208 electrical & electronic engineeringNonlinear systemSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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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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A nonlinear oscillators network devoted to image processing

2004

A contrast enhancement and image inverting tool using a lattice of uncoupled nonlinear oscillators is proposed. We show theoretically and numerically that the gray scale picture contrast is strongly enhanced even if this one is initially very small. An image inversion can be also obtained in real time with the same Cellular Nonlinear Network (CNN) without reconfiguration of the network. A possible electronic implementation of this CNN is finally discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[ PHYS.COND.CM-DS-NN ] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]Image processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCellular nonlinear networksTopology01 natural sciencesGrayscale010305 fluids & plasmasNonlinear oscillators[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]010306 general physicsEngineering (miscellaneous)ComputingMilieux_MISCELLANEOUSArtificial neural networkApplied MathematicsControl reconfigurationInversion (meteorology)neural networks[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsNonlinear systemComputer Science::Computer Vision and Pattern RecognitionModeling and SimulationNonlinear dynamics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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