Search results for " Images."

showing 10 items of 193 documents

Cloud screening and multitemporal unmixing of MERIS FR data

2007

The operational use of MERIS images can be hampered by the presence of clouds. This work presents a cloud screening algorithm that takes advantage of the high spectral and radiometric resolutions of MERIS and the specific location of some of its bands to increase the cloud detection accuracy. Moreover, the proposed algorithm provides a per-pixel probabilistic map of cloud abundance rather than a binary cloud presence flag. In order to test the proposed algorithm we propose a cloud screening validation method based on temporal series. In addition, we evaluate the impact of the cloud screening in a multitemporal unmixing application, where a temporal series of MERIS FR images acquired over Th…

ComputingMilieux_GENERALMERISLaboratory of Geo-information Science and Remote SensingCloud screeningMultispectral images550 - Earth sciencesLaboratorium voor Geo-informatiekunde en Remote SensingSub-pixel classificationPE&RCAstrophysics::Galaxy AstrophysicsSpectral unmixing
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Graph cut-based method for segmenting the left ventricle from MRI or echocardiographic images

2017

International audience; In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) adapted to work on two of the most widely used modalities: magnetic resonance imaging (MRI) and echocardiography. Our method accounts for the fundamentally different nature of both modalities: 3D echocardiographic images have a low contrast, a poor signal-to-noise ratio and frequent signal drop, while MR images are more detailed but also cluttered and contain highly anisotropic voxels. The main characteristic of our method is to work in a 3D Bezier coordinate system instead of the original Euclidean space. This comes with several ad…

Convex hullHeart VentriclesEnergy MinimizationCoordinate systemEchocardiography Three-DimensionalHealth InformaticsBézier curve02 engineering and technology[SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicinecomputer.software_genreAutomated Segmentation030218 nuclear medicine & medical imaging[ SDV.IB.MN ] Life Sciences [q-bio]/Bioengineering/Nuclear medicine03 medical and health sciences0302 clinical medicineVoxelCut0202 electrical engineering electronic engineering information engineering[INFO.INFO-IM]Computer Science [cs]/Medical ImagingMagnetic-Resonance ImagesHumansRadiology Nuclear Medicine and imagingComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac MriImage gradientMathematicsWhole MyocardiumLeft ventricular 3-D segmentationRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingEuclidean spacebusiness.industryComputer Graphics and Computer-Aided DesignMagnetic Resonance ImagingEchocardiographyConstrained Level-SetGraph (abstract data type)020201 artificial intelligence & image processing[SDV.IB]Life Sciences [q-bio]/BioengineeringComputer Vision and Pattern RecognitionArtificial intelligencebusiness2d-EchocardiographycomputerAlgorithmsGraph cutMRI
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Segmentation Integrating Watershed and Shape Priors Applied to Cardiac Delayed Enhancement MR Images

2017

International audience; Background: In recent years, there has been a rapid rise in the use of shape priors applied to segmentation process of medical images. Previous approaches on left ventricle segmentation from Delayed-Enhancement Magnetic Resonance Imaging (DE-MRI) have focused on the extraction of myocardium or just diseased region in short axis orientation. However these studies did not take into account the segmentation of non-diseased myocardium from DE-MRI. The segmentation of non-diseased myocardium from DE-MRI, has some useful applications. For instance it can simplify the PET-MR registration process.Methods: This paper presents a novel semi-automatic segmentation method of non-…

DE-MRIComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingBiomedical EngineeringBiophysicsScale-space segmentation030204 cardiovascular system & hematology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSegmentationSørensen–Dice coefficientInformationMagnetic-Resonance ImagesSegmentationComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac imaging[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingOrientation (computer vision)business.industryImage segmentationGold standard (test)Computer aided diagnosisComputer-aided diagnosisGraph Cuts[SDV.IB]Life Sciences [q-bio]/BioengineeringArtificial intelligencebusinessShape priorsCardiac imaging
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FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Databases FactualComputer scienceFeature vectorFeature extractionNormal DistributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingModels BiologicalEdge detectionArtificial IntelligenceImage Processing Computer-AssistedHumansSegmentationComputer visionAdaBoostFluorescein AngiographyElectrical and Electronic EngineeringTraining setPixelContextual image classificationSettore INF/01 - Informaticabusiness.industryReproducibility of ResultsRetinal VesselsWavelet transformBayes TheoremPattern recognitionGeneral MedicineImage segmentationComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONROC CurveTest setAdaBoost classifier retinal images vessel segmentationArtificial intelligencebusinessAlgorithmsBiotechnology
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Optimal extension of multispectral image demosaicking algorithms for setting up a one-shot camera video acquisition system

2022

Multispectral images are acquired using multispectral cameras equipped with CCD or CMOS sensors which sample the visible or near infrared spectrum according to specific spectral bands. A mosaic of multispectral MSFA filters is superimposed on the surface of the sensors to acquire a raw image called an MSFA image. In the MSFA image, only one spectral band is available per pixel, the demosaicking process is necessary to estimate the multispectral image at full spatio-spectral resolution. Motivated by the success of single-sensor cameras capturing the image in a single exposure that use CFA filters, we performed a comparative study of a few recent color image demosaicking algorithms and experi…

Demosaicking algorithmAdaptive Kernel regressionInterpolation bilinéaire pondéréeMultispectral imagesnoyau adaptatif de régressionBiorthogonal waveletsMultispectral filter arrayRéseau de filtres multispectrauxImages multispectralesConvolutionComposante de luminance[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]LMMSEWeighted bilinear interpolationAlgorithme de démosaïquageLuminance componentOndelettes biorthogonales
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Ultra-fast intensified frame images from an electron cyclotron resonance hydrogen plasma at 2.45 GHz: some space distributions of visible and monochr…

2014

First results from an ultra-fast frame image acquisition diagnostic coupled to a 2.45 GHz microwave hydrogen discharge are presented. The plasma reactor has been modified to include a transparent doubled shielded quartz window allowing to viewing the full plasma volume. Pictures describing the breakdown process at 1μs exposure time have been obtained for integrated visible light signal, Balmer-alpha, Balmer-beta lines, and Fulcher-band. Several different plasma emission distributions are reported. The distribution depends on the magnetic field configuration, incident microwave power, and neutral gas pressure. peerReviewed

Dense plasma focusMaterials scienceta114business.industrymicrowave powerAstrophysics::Cosmology and Extragalactic AstrophysicsPlasmaElectron cyclotron resonancemagnetic field configurationPlasma windowOpticsPhysics::Plasma Physicsframe imagesgas pressurePlasma diagnosticsElectromagnetic electron waveAtomic physicsInductively coupled plasmabusinessInstrumentationMicrowaveThe Review of scientific instruments
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Finitary Representations and Images of Transitive Finitary Permutation Groups

1999

Abstract We characterize the point stabilizers and kernels of finitary permutation representations of infinite transitive groups of finitary permutations. Moreover, the number of such representations is determined.

Discrete mathematicshomomorphic imagesMathematics::CombinatoricsAlgebra and Number Theorypermutation groupsfinitary groupsBit-reversal permutationGeneralized permutation matrixPermutation groupCyclic permutationCombinatoricsMathematics::LogicPermutationwreath productsWreath productMathematics::Category TheoryComputer Science::Logic in Computer ScienceFinitaryPermutation graphMathematicsJournal of Algebra
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Discrete wavelet transform based multispectral filter array demosaicking

2013

International audience; The idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking.

Discrete wavelet transformDWT based demosaickingHyperspectral imagingComputer scienceMultispectralMultispectral image[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologymultispectral filter array demosaicking01 natural sciencesfilter array[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingimage colour analysis[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionOptical filterImage resolutionimage segmentationDemosaicingmultispectral image acquisitionHyperspectral imagingimagingspectral correlationCorrelationCFA demosaicking[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingImage color analysis010309 optics0103 physical sciencesoptical filtersArraysspatial images resolution[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingdiscrete wavelet transformbusiness.industryImage segmentationBinary treesDiscrete wavelet transformscolour filter arrayspectral analysisInterpolationdemosaickingFilter (video)Artificial intelligencebusinessimage resolution
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Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform

2021

Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…

Earth observation010504 meteorology & atmospheric sciencesComputer scienceNDVIScienceQvegetation types classification04 agricultural and veterinary sciences15. Life on landTime optimal01 natural sciencesNormalized Difference Vegetation IndexRandom forestIdentification (information)Vegetation typesmachine learning040103 agronomy & agriculturevegetation types classification; multi-temporal images; machine learning; Google Earth Engine; NDVI0401 agriculture forestry and fisheriesGeneral Earth and Planetary SciencesGoogle Earth EngineCartographymulti-temporal images0105 earth and related environmental sciencesRemote Sensing
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Batch Methods for Resolution Enhancement of TIR Image Sequences

2015

Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on appli…

Earth observationAtmospheric ScienceBayesian smoothing methodComputer scienceBayesian probabilityInterval (mathematics)Thermal imagecomputer.software_genreremote sensingComputers in Earth ScienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliComputer visionimage enhancementComputers in Earth SciencesImage resolutionThermal imagesbusiness.industrySettore ING-INF/03 - TelecomunicazioniSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaBayesian smoothing methodsinterpolationTemporal resolutioncloud detectionBatch processingBayesian smoothing methods; cloud detection; image enhancement; interpolation; remote sensing; Thermal images; Computers in Earth Sciences; Atmospheric ScienceData miningArtificial intelligencebusinessFocus (optics)computerSmoothingSettore ICAR/06 - Topografia E Cartografia
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