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Extension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration / Karmon Vongsy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 6 (June 2015) . - pp 3005 - 3021 Titre : Extension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration Type de document : Article/Communication Auteurs : Karmon Vongsy, Auteur ; Michael T. Eismann, Auteur ; Michael J. Mendenhall, Auteur Année de publication : 2015 Article en page(s) : pp 3005 - 3021 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] approximation [Termes IGN] détection de changement [Termes IGN] distribution de Gauss [Termes IGN] image hyperspectrale [Termes IGN] modèle linéaire [Termes IGN] résidu Résumé : (Auteur) A generalized likelihood ratio test (GLRT) statistic for spectral change detection based on the linear chromodynamics model is extended to accommodate unknown residual misregistration between imagery described by a prior probability density function for the spatial misregistration. Using a normal prior distribution leads to a fourth-order polynomial that can be numerically minimized over the unknown misregistration parameters. A more computationally efficient closed-form solution is developed based on a quadratic approximation and provides comparable results to the numerical minimization for the investigated test cases while running 30 times faster. The results applying the method to hyperspectral imagery indicate up to an order of magnitude reduction in false alarms at the same detection rate relative to baseline change detection methods for synthetically misregistered test data particularly in image regions containing edges and fine spatial features. Sensitivity to model parameters is assessed, and the method is compared with a previously published misregistration compensation approach yielding comparable results. Although the GLRT approach appears to exhibit comparable change detection performance, it offers the possibility of tailoring the algorithm to a priori knowledge of expected misregistration errors or to compensate structured misregistration as would occur due to parallax errors due to perspective variations (e.g., image parallax). Numéro de notice : A2015-281 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2367471 Date de publication en ligne : 18/12/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2367471 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76398 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2015061	SL	Revue	Centre de documentation	Revues en salle	Disponible

Hyperspectral-based adaptive matched filter detector error as a function of atmospheric water vapor estimation / Allan W. Yarbrough in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 52 n° 4 (April 2014) . - pp 2029 - 2039 Titre : Hyperspectral-based adaptive matched filter detector error as a function of atmospheric water vapor estimation Type de document : Article/Communication Auteurs : Allan W. Yarbrough, Auteur ; Michael J. Mendenhall, Auteur ; Richard K. Martin, Auteur ; Steven T. Fiorino, Auteur Année de publication : 2014 Article en page(s) : pp 2029 - 2039 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection d'erreur [Termes IGN] données météorologiques [Termes IGN] erreur de classification [Termes IGN] estimation statistique [Termes IGN] filtrage numérique d'image [Termes IGN] filtre spectral [Termes IGN] humidité de l'air [Termes IGN] image hyperspectrale [Termes IGN] transfert radiatif [Termes IGN] vapeur d'eau Résumé : (Auteur) Accurate target detection and classification in hyperspectral imagery require that the spectral measurements by the imager match as closely as possible the known “true” target as collected under controlled conditions and stored in a target database. Therefore, the effect of the radiation source and the atmosphere must be factored out of the result before detection is attempted. Our objective is to evaluate detection error due to the error in estimating the atmospherics. We apply a range of atmospheric water vapor profiles, corresponding to different relative humidities, to a model-based prediction of the radiative transfer to examine the effect of water vapor on simulated hyperspectral imagery. These profiles are taken from known distribution percentiles as obtained from historic meteorological measurements close to the sites being simulated. We quantify the expected detection error for the adaptive matched filter, as measured by the receiver operating characteristic (ROC) and the area under the ROC curve, given the range of atmospheric conditions in the historic profile. We discover that, depending on the target, and given the uncertainty as to the true atmospheric conditions, detection rates improve on average across the historic range when we assume the atmospheric profile is at the 35th percentile of atmospheric relative humidity instead of the 50th percentile. Numéro de notice : A2014-269 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2257797 En ligne : https://doi.org/10.1109/TGRS.2013.2257797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33172 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2014041	RAB	Revue	Centre de documentation	En réserve L003	Disponible