A New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting

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dc.creatorValiollahzadeh, SeyyedMajid
dc.creatorNazari, Mohammad
dc.creatorBabaie-Zadeh, Massoud
dc.creatorJutten, Christian
dc.date2008-12-12
dc.date.accessioned2026-07-07T12:12:27Z
dc.date.available2026-07-07T12:12:27Z
dc.descriptionRecently, great attention was intended toward overcomplete dictionaries and the sparse representations they can provide. In a wide variety of signal processing problems, sparsity serves a crucial property leading to high performance. Inpainting, the process of reconstructing lost or deteriorated parts of images or videos, is an interesting application which can be handled by suitably decomposition of an image through combination of overcomplete dictionaries. This paper addresses a novel technique of such a decomposition and investigate that through inpainting of images. Simulations are presented to demonstrate the validation of our approach.
dc.description4 pages
dc.identifierhttps://arxiv.org/abs/0812.2405
dc.identifierhttp://arxiv.org/abs/0812.2405
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/210546
dc.subjectMultimedia
dc.subjectArtificial Intelligence
dc.titleA New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting
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