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dc.contributor.authorJung, Miyoun
dc.contributor.authorBresson, Xavier
dc.contributor.authorChan, Tony F.
dc.contributor.authorVese, Luminita A.
dc.date.accessioned2013-10-15T14:44:31Z
dc.date.available2013-10-15T14:44:31Z
dc.date.issued2011
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/11845
dc.language.isoenen
dc.subjectAmbrosio-Tortorelli elliptic approximationsen
dc.subjectMumford-Shah (MS) regularizeren
dc.subjectdeblurringen
dc.subjectdemosaicingen
dc.subjectdenoisingen
dc.subjectimpulse noiseen
dc.subjectinpaintingen
dc.subjectnonlocal operatorsen
dc.subjectsuper-resolutionen
dc.subject.ddc3en
dc.titleNonlocal Mumford-Shah Regularizers for Color Image Restorationen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose here a class of restoration algorithms for color images, based upon the Mumford-Shah (MS) model and nonlocal image information. The Ambrosio-Tortorelli and Shah elliptic approximations are defined to work in a small local neighborhood, which are sufficient to denoise smooth regions with sharp boundaries. However, texture is nonlocal in nature and requires semilocal/non-local information for efficient image denoising and restoration. Inspired from recent works (nonlocal means of Buades, Coll, Morel, and nonlocal total variation of Gilboa, Osher), we extend the local Ambrosio-Tortorelli and Shah approximations to MS functional (MS) to novel nonlocal formulations, for better restoration of fine structures and texture. We present several applications of the proposed nonlocal MS regularizers in image processing such as color image denoising, color image deblurring in the presence of Gaussian or impulse noise, color image inpainting, color image super-resolution, and color filter array demosaicing. In all the applications, the proposed nonlocal regularizers produce superior results over the local ones, especially in image inpainting with large missing regions. We also prove several characterizations of minimizers based upon dual norm formulations.en
dc.relation.isversionofjnlnameIEEE Transactions on Image Processing
dc.relation.isversionofjnlvol20en
dc.relation.isversionofjnlissue6en
dc.relation.isversionofjnldate2011
dc.relation.isversionofjnlpages1583-1598en
dc.relation.isversionofdoihttp://dx.doi.org/10.1109/TIP.2010.2092433en
dc.relation.isversionofjnlpublisherIEEEen
dc.subject.ddclabelRecherche opérationnelleen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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