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hal.structure.identifierDépartement Traitement du Signal et des Images [TSI]
dc.contributor.authorSU, Xin
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDELEDALLE, Charles-Alban
hal.structure.identifierDépartement Traitement du Signal et des Images [TSI]
dc.contributor.authorTUPIN, Florence
hal.structure.identifierSchool of Electronic Information [Wuhan]
dc.contributor.authorSUN, Hong
dc.date.accessioned2024-04-04T02:17:07Z
dc.date.available2024-04-04T02:17:07Z
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/189199
dc.description.abstractEnThis paper presents a likelihood ratio test based method of change detection and classification for synthetic aperture radar (SAR) time series, namely NORmalized Cut on chAnge criterion MAtrix (NORCAMA). This method involves three steps: 1) multi-temporal pre-denoising step over the whole image series to reduce the effect of the speckle noise; 2) likelihood ratio test based change criteria between two images using both the original noisy images and the denoised images; 3) change classification by a normalized cut based clustering-and-recognizing method on change criterion matrix (CCM). The experiments on both synthetic and real SAR image series show the effective performance of the proposed framework.
dc.language.isoen
dc.title.enNORCAMA: Change Analysis in SAR Time Series by Likelihood Ratio Change Matrix Clustering
dc.typeRapport
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
hal.identifierhal-00997786
hal.version1
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00997786v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=SU,%20Xin&DELEDALLE,%20Charles-Alban&TUPIN,%20Florence&SUN,%20Hong&rft.genre=unknown


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