Search results for "Spectral"

showing 10 items of 3116 documents

Machine learning in remote sensing data processing

2009

Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.

Data processingContextual image classificationFire detectionbusiness.industryComputer scienceMultispectral imageMachine learningcomputer.software_genreField (computer science)Support vector machineRemote sensing (archaeology)Radar imagingArtificial intelligencebusinesscomputerRemote sensing2009 IEEE International Workshop on Machine Learning for Signal Processing
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Dimensionality Reduction Techniques: An Operational Comparison On Multispectral Satellite Images Using Unsupervised Clustering

2006

Multispectral satellite imagery provides us with useful but redundant datasets. Using Dimensionality Reduction (DR) algorithms, these datasets can be made easier to explore and to use. We present in this study an objective comparison of five DR methods, by evaluating their capacity to provide a usable input to the K-means clustering algorithm. We also suggest a method to automatically find a suitable number of classes K, using objective "cluster validity indexes" over a range of values for K. Ten Landsat images have been processed, yielding a classification rate in the 70-80% range. Our results also show that classical linear methods, though slightly outperformed by more recent nonlinear al…

Data processingContextual image classificationPixelbusiness.industryComputer scienceDimensionality reductionMultispectral imagek-means clusteringUnsupervised learningPattern recognitionArtificial intelligencebusinessCluster analysisProceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006
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A new fast and fault-tolerant identification algorithm for spectral databases

1995

A new method for an automatic, computer and database driven identification of UV/VIS spectra is described. It is shown that an identification algorithm must consider the spectral differences as well as their common features. The described identification method allows identifications, even if the spectra are distorted or shifted.

Data processingDatabaseComputer sciencePattern analysisFault toleranceVis spectraFuzzy control systemcomputer.software_genreBiochemistrySpectral lineAnalyse qualitativeAnalytical ChemistryIdentification (information)ComputingMethodologies_PATTERNRECOGNITIONcomputerAlgorithmAnalytical and Bioanalytical Chemistry
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HICO L1 and L2 data processing: Radiometric recalibration, atmospheric correction and retrieval of water quality parameters

2015

The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer designed with a very high signal-to-noise ratio to monitor coastal ocean and inland waters. The processing of Top-Of-Atmosphere radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This paper describes the algorithms implemented within an HICO data processing chain that includes image pre-processing, atmospheric correction and the retrieval of water quality parameters. The implemented algorithms have been validated over a set of HICO ima…

Data processingMeteorologyAtmospheric correctionImaging spectrometerRadianceEnvironmental scienceRadiometryHyperspectral imagingAtmospheric modelWater qualityRemote sensing2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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HICO level-2 data processing toolbox for the atmospheric correction and the retrieval of water quality parameters

2014

The Hyperspectral Imager for the Coastal Ocean (HICO) is an imaging spectrometer specifically designed to monitor the coastal ocean. The processing of Top-Of-Atmosphere (TOA) radiance data down to surface reflectance is fundamental for the retrieval of water quality products. However, the current HICO processing chain does not provide atmospheric corrected data nor higher-level water quality products. This work describes a toolbox for the atmospheric correction of HICO data and the retrieval of water quality products. The HICO toolbox, consisting on three main modules (image pre-processing, atmospheric correction and retrieval of water quality products), has been used over a set of HICO ima…

Data processingMeteorologyRadianceAtmospheric correctionImaging spectrometerEnvironmental scienceHyperspectral imagingRadiometryWater qualityAtmospheric modelRemote sensing2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
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Noise reduction in asteroid imaging using a miniaturized spectral imager

2021

In October 2024, European Space Agency’s Hera mission will be launched, targeting the binary asteroid Didymos. Hera will host the Juventas and Milani CubeSats, the first CubeSats to orbit close to a small celestial body performing scientific and technological operations. The primary scientific payload of the Milani CubeSat is the SWIR, NIR, and VIS imaging spectrometer ASPECT. The Milani mission objectives include mapping the global composition and the characterization of the binary asteroid surface. Onboard data processing and evaluation steps will be applied due to the limited data budget for the downlink to Earth and to perform the technological demonstration of a novel semi-autonomous h…

Data processingNoise (signal processing)Computer sciencePayloadReal-time computingImaging spectrometerHyperspectral imaging02 engineering and technologyFilter (signal processing)7. Clean energy030218 nuclear medicine & medical imaging03 medical and health sciences020210 optoelectronics & photonics0302 clinical medicine13. Climate actionDigital image processing0202 electrical engineering electronic engineering information engineeringCubeSatSensors, Systems, and Next-Generation Satellites XXV
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Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed …

Data records010504 meteorology & atmospheric sciencesData productsSciencemeteosat second generation (MSG); biophysical parameters (LAI; FVC; FAPAR); SEVIRI; climate data records (CDR); stochastic spectral mixture model (SSMM); Satellite Application Facility for Land Surface Analysis (LSA SAF)0211 other engineering and technologiesstochastic spectral mixture model (SSMM)02 engineering and technology01 natural sciencesFAPAR)climate data records (CDR)Leaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesQVegetationSEVIRIMixture modelSatellite Application Facility for Land Surface Analysis (LSA SAF)FVCbiophysical parameters (LAIPhotosynthetically active radiationGeostationary orbitGeneral Earth and Planetary SciencesEnvironmental sciencemeteosat second generation (MSG)SatelliteAlgorithmRemote Sensing; Volume 11; Issue 18; Pages: 2103
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Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments

1998

Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…

Data setMultivariate statisticsFuzzy classificationTemporal resolutionSoil ScienceEnvironmental scienceGeologyRegression analysisComputers in Earth SciencesImage resolutionMultispectral ScannerNormalized Difference Vegetation IndexRemote sensing
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Etude numérique d'équations aux dérivées partielles non linéaires et dispersives

2011

Numerical analysis becomes a powerful resource in the study of partial differential equations (PDEs), allowing to illustrate existing theorems and find conjectures. By using sophisticated methods, questions which seem inaccessible before, like rapid oscillations or blow-up of solutions can be addressed in an approached way. Rapid oscillations in solutions are observed in dispersive PDEs without dissipation where solutions of the corresponding PDEs without dispersion present shocks. To solve numerically these oscillations, the use of efficient methods without using artificial numerical dissipation is necessary, in particular in the study of PDEs in some dimensions, done in this work. As stud…

Davey-Stewartson systems[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]equations dispersivesdispersive shocksexponential time-differencing[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM][MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]spectral methodschocs dispersifsnumerical methodsdispersive equationsNo english keywordssplit stepschemas de decomposition d'operateursmethodes spectrales[MATH.MATH-MP] Mathematics [math]/Mathematical Physics [math-ph]Kadomtsev-Petviashvili equationintegrating factor methodparallel computing[ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph]Pas de mot clé en français[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]methodes numeriquesblow upequation de Kadomtsev-PetviashviliIntegrateurs exponentielssystemes de Davey-Stewartsoncalcul parallele
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Optical calibration of a multispectral imaging system based on interference filters

2005

We present a new approach to optically calibrate a multispectral imaging system based on interference filters. Such a system typically suffers from some blurring of its channel images. Because the effectiveness of spectrum reconstruction depends heavily on the quality of the acquired channel images, and because this blurring negatively affects them, a method for deblurring and denoising them is required. The blur is modeled as a uniform intensity distribution within a circular disk. It allows us to characterize, quantitatively, the degradation for each channel image. In terms of global reduction of the blur, it consists of the choice of the best channel for the focus adjustment according to…

DeblurringComputer sciencebusiness.industryNoise reductionWiener filterMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage processingReal imageAtomic and Molecular Physics and OpticsMultispectral pattern recognitionsymbols.namesakeComputer Science::GraphicsInterference (communication)Computer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceOptical filterFocus (optics)businessImage restorationOptical Engineering
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