On pixel-based texture synthesis by non-parametric sampling

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dc.contributor.authorShin, Sko
dc.contributor.authorNishita, Tko
dc.contributor.authorShin, Sung-Yongko
dc.date.accessioned2013-03-06T08:41:15Z-
dc.date.available2013-03-06T08:41:15Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2006-10-
dc.identifier.citationCOMPUTERS & GRAPHICS-UK, v.30, no.5, pp.767 - 778-
dc.identifier.issn0097-8493-
dc.identifier.urihttp://hdl.handle.net/10203/86473-
dc.description.abstractIn this paper, we propose a pixel-based method for texture synthesis with non-parametric sampling. On top of the general framework of pixel-based approaches, our method has three distinguishing features: window size estimation, seed point planting, and iterative refinement. The size of a window is estimated to capture the structural components of the dominant scale embedded in the texture sample. To guide the pixel sampling process at the initial iteration, a grid of seed points are sampled from the example texture. Finally, an iterative refinement scheme is adopted to diffuse the non-stationarity artifact over the entire texture. Our objective is to enhance texture quality as much as possible with a minor sacrifice in efficiency in order to support our conjecture that the pixel-based approach would yield high quality images. (c) 2006 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleOn pixel-based texture synthesis by non-parametric sampling-
dc.typeArticle-
dc.identifier.wosid000242334800009-
dc.identifier.scopusid2-s2.0-33750024214-
dc.type.rimsART-
dc.citation.volume30-
dc.citation.issue5-
dc.citation.beginningpage767-
dc.citation.endingpage778-
dc.citation.publicationnameCOMPUTERS & GRAPHICS-UK-
dc.identifier.doi10.1016/j.cag.2006.07.023-
dc.contributor.localauthorShin, Sung-Yong-
dc.contributor.nonIdAuthorShin, S-
dc.contributor.nonIdAuthorNishita, T-
dc.type.journalArticleArticle-
dc.subject.keywordAuthortexture synthesis-
dc.subject.keywordAuthorimage processing-
dc.subject.keywordAuthornon-parametric sampling-
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