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MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?

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.identifierEquipe Image - Laboratoire GREYC - UMR6072
hal.structure.identifierLaboratoire Traitement et Communication de l'Information [LTCI]
dc.contributor.authorTABTI, Sonia
hal.structure.identifierLaboratoire Traitement et Communication de l'Information [LTCI]
dc.contributor.authorTUPIN, Florence
dc.date.accessioned2024-04-04T03:10:23Z
dc.date.available2024-04-04T03:10:23Z
dc.date.created2016-10-26
dc.date.issued2017-09
dc.identifier.issn1057-7149
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193685
dc.description.abstractEnSpeckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.
dc.description.sponsorshipAnalyse de surfaces urbaines par tomographie SAR - ANR-15-ASTR-0002
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.subject.envariance stabilization
dc.subject.enspeckle
dc.subject.enSAR
dc.subject.enWishart distribution
dc.subject.enADMM
dc.title.enMuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?
dc.typeArticle de revue
dc.identifier.doi10.1109/TIP.2017.2713946
dc.subject.halInformatique [cs]/Traitement des images
dc.subject.halSciences de l'ingénieur [physics]/Traitement du signal et de l'image
dc.subject.halMathématiques [math]/Statistiques [math.ST]
dc.subject.halStatistiques [stat]/Applications [stat.AP]
dc.identifier.arxiv1704.05335
bordeaux.journalIEEE Transactions on Image Processing
bordeaux.page4389-4403
bordeaux.volume26
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue9
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01388858
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01388858v1
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