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Geometric Estimation with Orthogonal Bandlet Bases

dc.contributor.authorMallat, Stéphane
dc.contributor.authorDossal, Charles
dc.contributor.authorLe Pennec, Erwan
dc.contributor.authorPeyré, Gabriel
HAL ID: 1211
dc.date.accessioned2009-07-08T12:29:56Z
dc.date.available2009-07-08T12:29:56Z
dc.date.issued2007-09
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/972
dc.language.isoenen
dc.subjectminimaxen
dc.subjectestimationen
dc.subjectwaveletsen
dc.subjectgeometric estimationen
dc.subjectdenoisingen
dc.subjectBandletsen
dc.subject.ddc519en
dc.titleGeometric Estimation with Orthogonal Bandlet Basesen
dc.typeCommunication / Conférence
dc.contributor.editoruniversityotherCNRS - Université de Versailles-Saint Quentin en Yvelines - Polytechnique X;France
dc.contributor.editoruniversityotherCNRS - Université Pierre et Marie Curie - Paris VI - Université Denis Diderot - Paris VII;France
dc.contributor.editoruniversityotherCNRS - Université de Sciences et Technologies - Bordeaux I;France
dc.description.abstractenThis article presents the first adaptive quasi minimax estimator for geometrically regular images in the white noise model. This estimator is computed using a thresholding in an adapted orthogonal bandlet basis optimized for the noisy observed image. In order to analyze the quadratic risk of this best basis denoising, the thresholding in an orthogonal bandlets basis is recasted as a model selection process. The resulting estimator is computed with a fast algorithm whose theoretical performance can be derived. This efficiency is confirmed through numerical experiments on natural images.en
dc.identifier.urlsitehttp://hal.archives-ouvertes.fr/hal-00365606/en/en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.conftitleSPIE Wavelets XIIen
dc.relation.confdate2007-08
dc.relation.confcitySan Diego, CAen
dc.relation.confcountryEtats-Unis


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