Search results for "Full spectral imaging"

showing 8 items of 8 documents

Optimized Class-Separability in Hyperspectral Images

2016

International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…

010504 meteorology & atmospheric sciencesBand SelectionComputer science0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[SDU.STU]Sciences of the Universe [physics]/Earth Sciences02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesTransformation[SPI]Engineering Sciences [physics][ SPI.NRJ ] Engineering Sciences [physics]/Electric powerDisplay[ SPI ] Engineering Sciences [physics]Computer visionclass separabilityFusion021101 geological & geomatics engineering0105 earth and related environmental sciencesColor imagebusiness.industry[SPI.NRJ]Engineering Sciences [physics]/Electric powerHyperspectral imagingPattern recognition[ SDU.STU ] Sciences of the Universe [physics]/Earth SciencesImage segmentationSpectral bandsDimensionality reductionVisualization[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsImaging spectroscopyFull spectral imagingRGB color modelArtificial intelligencehyper-spectral image visualizationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A sensor-data-based denoising framework for hyperspectral images

2015

Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term…

Blind deconvolution[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingHyperspectral imagingAnisotropic diffusionComputer scienceNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technology01 natural sciences010309 opticsOptics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesdenoising0202 electrical engineering electronic engineering information engineeringbusiness.industryHyperspectral imagingcomputer.file_formatNon-local meansAtomic and Molecular Physics and OpticsLight intensityFull spectral imagingComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingImage file formatsNoise (video)businesscomputer
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Spatial/spectral information trade-off in hyperspectral images

2015

This paper shows an empirical analysis of the trade-off between the spectral and the spatial information content of hyperspectral images. The objective of this study is to provide some insights into how changes and variations of both resolutions may affect the information content of the resulting image. This is useful for different stages of hyperspectral image processing: from acquisition to final applications. We propose two alternative approaches to measure the information content of a hyperspectral image: first, a second order approximation where the data distribution is supposed to be Gaussian, and secondly a higher order approximation where no assumption about the data distribution is…

Computer sciencebusiness.industryGaussianHyperspectral imagingPattern recognitionsymbols.namesakeFull spectral imagingsymbolsEntropy (information theory)Computer visionArtificial intelligencebusinessSpatial analysisImage resolution2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Scene-based spectral calibration assessment of high spectral resolution imaging spectrometers

2009

An accurate knowledge of the spectral calibration of imaging spectrometers is required for optimum data processing and interpretation. The scene-based spectral characterization of imaging spectrometers is frequently necessary to update or replace the pre-flight laboratory-based spectral characterization supplied by the data provider. An automatic method for the estimation of spectral calibration parameters (channel position and bandwidth) at atmospheric absorption regions from high spectral resolution imaging spectrometers (spectral sampling interval below 5 nm) is presented in this contribution. The method has been tested on two commercial instruments with spectral sampling intervals below…

Optics and Photonicsmedicine.medical_specialtyTime FactorsNormal Distribution550 - Earth sciencesAutomationOpticsImage Processing Computer-AssistedmedicineSpectral resolutionRadiometric calibrationRemote sensingPhysicsSpectral signatureSpectrometerAtmospherebusiness.industryBandwidth (signal processing)Hyperspectral imagingAtomic and Molecular Physics and OpticsSpectral imagingSpectrometry FluorescenceSpectrophotometryFull spectral imagingCalibrationbusiness
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Compressive single-pixel multispectral Stokes polarimeter

2014

We present a single-pixel system that performs polarimetric multispectral imaging with the aid of compressive sensing techniques. We experimentally obtain the full Stokes spatial distribution of a scene for different spectral channels.

Physicsmedicine.medical_specialtybusiness.industryMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPolarimetryHyperspectral imagingPolarimeterMultispectral pattern recognitionSpectral imagingComputer Science::GraphicsCompressed sensingOpticsComputer Science::Computer Vision and Pattern RecognitionFull spectral imagingComputer Science::MultimediamedicinebusinessPhysics::Atmospheric and Oceanic PhysicsComputingMethodologies_COMPUTERGRAPHICSRemote sensingLatin America Optics and Photonics Conference
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Spectral adaptation of hyperspectral flight lines using VHR contextual information

2014

Abstract: Due to technological constraints, hyperspectral earth observation imagery are often a mosaic of overlapping flight lines collected in different passes over the area of interest. This causes variations in aqcuisition conditions such that the reflected spectrum can vary significantly between these flight lines. Partly, this problem is solved by atmospherical correction, but residual spectral differences often remain. A probabilistic domain adaptation framework based on graph matching using Hidden Markov Random Fields was recently proposed for transforming hyperspectral data from one image to better correspond to the other. This paper investigates the use of scale and angle invariant…

VHR imageryHyperspectral imaginggraph matchingComputer sciencebusiness.industrydomain adaptationPhysicsHyperspectral imagingPattern recognitionFilter (signal processing)Rendering (computer graphics)Computer Science::Computer Vision and Pattern RecognitionFull spectral imagingtextural featuresComputer visionArtificial intelligenceHidden Markov random fieldHidden Markov modelbusiness
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Spectral calibration of hyperspectral imagery using atmospheric absorption features

2006

One of the initial steps in the preprocessing of remote sensing data is the atmospheric correction of the at-sensor radiance images, i.e., radiances recorded at the sensor aperture. Apart from the accuracy in the estimation of the concentrations of the main atmospheric species, the retrieved surface reflectance is also influenced by the spectral calibration of the sensor, especially in those wavelengths mostly affected by gaseous absorptions. In particular, errors in the surface reflectance appear when a systematic shift in the nominal channel positions occurs. A method to assess the spectral calibration of hyperspectral imaging spectrometers from the acquired imagery is presented in this p…

atmospheric absorptionMaterials sciencebusiness.industryhyperspectral sensorMaterials Science (miscellaneous)Diffuse sky radiationAtmospheric correctionHyperspectral imaging550 - Earth sciencesIndustrial and Manufacturing EngineeringOpticsspectral calibrationFull spectral imagingRadianceRadiative transferBusiness and International ManagementbusinessRadiometric calibrationWater vaporRemote sensing
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Multidimensional Optical Sensing and Imaging Systems (MOSIS): From Macro to Micro Scales

2017

Multidimensional optical imaging systems for information processing and visualization technologies have numerous applications in fields such as manufacturing, medical sciences, entertainment, robotics, surveillance, and defense. Among different three-dimensional (3-D) imaging methods, integral imaging is a promising multiperspective sensing and display technique. Compared with other 3-D imaging techniques, integral imaging can capture a scene using an incoherent light source and generate real 3-D images for observation without any special viewing devices. This review paper describes passive multidimensional imaging systems combined with different integral imaging configurations. One example…

medicine.medical_specialtyIntegral imagingbusiness.industryMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImaging spectrometerImage registrationImage sensorsOptical imagingSpectral imagingGeographyFull spectral imagingOptical sensorsmedicineThree-dimensional displaysComputer visionArtificial intelligenceImaging scienceElectrical and Electronic EngineeringImage sensorbusinessVisualization
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