Show simple item record

Global Total Variation Minimization

dc.contributor.authorDibos, Françoise
dc.contributor.authorKoepfler, Georges
dc.date.accessioned2011-06-07T08:40:39Z
dc.date.available2011-06-07T08:40:39Z
dc.date.issued2000
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6436
dc.language.isoenen
dc.subjecttotal variationen
dc.subjectimage denoisingen
dc.subjectminimizationen
dc.subjectlevel seten
dc.subject.ddc519en
dc.titleGlobal Total Variation Minimizationen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenThe minimization of the total variation is an important tool of image processing. A lot of authors have addressed the problem and developed algorithms for image denoising. In this paper we present an alternative approach of the total variation minimization problem. After an introduction to the topic and a review of related work, we give a short development of the bounded variation (BV) background. Then we present our global total variation minimization model and proof its validity. Furthermore we introduce a practical algorithm which handles digital image data and we give experimental results.en
dc.relation.isversionofjnlnameSIAM Journal on Numerical Analysis
dc.relation.isversionofjnlvol37en
dc.relation.isversionofjnlissue2en
dc.relation.isversionofjnldate2000
dc.relation.isversionofjnlpages646-664en
dc.relation.isversionofdoihttp://dx.doi.org/10.1137/S0036142998334838en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSIAMen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


Files in this item

Thumbnail
Name:
dibos.pdf
Size:
63.20Kb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record