An edge-based algorithm for discontinuity adaptive color image smoothing

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dc.contributor.authorKang, DJko
dc.contributor.authorKweon, In-Soko
dc.date.accessioned2010-11-29T05:16:49Z-
dc.date.available2010-11-29T05:16:49Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2001-02-
dc.identifier.citationPATTERN RECOGNITION, v.34, no.2, pp.333 - 342-
dc.identifier.issn0031-3203-
dc.identifier.urihttp://hdl.handle.net/10203/20467-
dc.description.abstractWe present a new scheme to increase the performance of edge-preserving image smoothing algorithm from the parameter tuning of a Markov random field (MRF) function. This method is based on an automatic control of the image-smoothing strength in the MRF function in which the parameter control of the function depends on edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, direct use of full edge magnitude could improve the performance of discontinuity-preserving image smoothing technique. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.-
dc.description.sponsorshipAuthors thank to Dr. Heui-Keun Choh in Signal Processing Lab. for his careful correction about English, spells, and written styles.en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectSEGMENTATION-
dc.subjectVISION-
dc.titleAn edge-based algorithm for discontinuity adaptive color image smoothing-
dc.typeArticle-
dc.identifier.wosid000165917300012-
dc.identifier.scopusid2-s2.0-0034823553-
dc.type.rimsART-
dc.citation.volume34-
dc.citation.issue2-
dc.citation.beginningpage333-
dc.citation.endingpage342-
dc.citation.publicationnamePATTERN RECOGNITION-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKweon, In-So-
dc.contributor.nonIdAuthorKang, DJ-
dc.type.journalArticleArticle-
dc.subject.keywordAuthordiscontinuities-
dc.subject.keywordAuthorimage edges-
dc.subject.keywordAuthorimage smoothing-
dc.subject.keywordAuthorcolor segmentation-
dc.subject.keywordAuthorMarkov random fields-
dc.subject.keywordPlusSEGMENTATION-
dc.subject.keywordPlusVISION-
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