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Exploiting patch similarity for SAR image processing: the nonlocal paradigm

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDELEDALLE, Charles-Alban
hal.structure.identifierLaboratoire Hubert Curien [LHC]
dc.contributor.authorDENIS, Loïc
hal.structure.identifierDipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione [Napoli] [DIETI]
dc.contributor.authorPOGGI, Giovanni
hal.structure.identifierLaboratoire Traitement et Communication de l'Information [LTCI]
hal.structure.identifierTélécom ParisTech
dc.contributor.authorTUPIN, Florence
hal.structure.identifierDipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione [Napoli] [DIETI]
dc.contributor.authorVERDOLIVA, Luisa
dc.date.accessioned2024-04-04T02:19:11Z
dc.date.available2024-04-04T02:19:11Z
dc.date.created2014-02-18
dc.date.issued2014-07
dc.identifier.issn1053-5888
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/189379
dc.description.abstractEnMost current SAR systems offer high-resolution images featuring polarimetric, interferometric, multi-frequency, multi-angle, or multi-date information. SAR images however suffer from strong fluctuations due to the speckle phenomenon inherent to coherent imagery. Hence, all derived parameters display strong signal-dependent variance, preventing the full exploitation of such a wealth of information. Even with the abundance of despeckling techniques proposed these last three decades, there is still a pressing need for new methods that can handle this variety of SAR products and efficiently eliminate speckle without sacrificing the spatial resolution. Recently, patch-based filtering has emerged as a highly successful concept in image processing. By exploiting the redundancy between similar patches, it succeeds in suppressing most of the noise with good preservation of texture and thin structures. Extensions of patch-based methods to speckle reduction and joint exploitation of multi-channel SAR images (interferometric, polarimetric, or PolInSAR data) have led to the best denoising performance in radar imaging to date. We give a comprehensive survey of patch-based nonlocal filtering of SAR images, focusing on the two main ingredients of the methods: measuring patch similarity, and estimating the parameters of interest from a collection of similar patches.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.title.enExploiting patch similarity for SAR image processing: the nonlocal paradigm
dc.typeArticle de revue
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.journalIEEE Signal Processing Magazine
bordeaux.pageSpecial issue: Recent Advances in Synthetic Aperture Radar Imaging
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierujm-00957334
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//ujm-00957334v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=IEEE%20Signal%20Processing%20Magazine&rft.date=2014-07&rft.spage=Special%20issue:%20Recent%20Advances%20in%20Synthetic%20Aperture%20Radar%20Imaging&rft.epage=Special%20issue:%20Recent%20Advances%20in%20Synthetic%20Aperture%20Radar%20Imaging&rft.eissn=1053-5888&rft.issn=1053-5888&rft.au=DELEDALLE,%20Charles-Alban&DENIS,%20Lo%C3%AFc&POGGI,%20Giovanni&TUPIN,%20Florence&VERDOLIVA,%20Luisa&rft.genre=article


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