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Cited 24 time in webofscience Cited 26 time in scopus
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Simplified noise model parameter estimation for signal-dependent noise

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dc.contributor.authorJeong, Bo Gyu-
dc.contributor.authorKim, Byoung Chul-
dc.contributor.authorMoon, Yong Ho-
dc.contributor.authorEom, Il Kyu-
dc.date.accessioned2022-12-26T23:17:56Z-
dc.date.available2022-12-26T23:17:56Z-
dc.date.issued2014-03-
dc.identifier.issn0165-1684-
dc.identifier.issn1872-7557-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/19135-
dc.description.abstractIn this paper, we present a noise parameter estimation method using a simplified signal-dependent noise model. The generic Poisson-Gaussian noise model is simplified to a Gaussian-Gaussian noise model. From the simplified noise model, we experimentally verify that the value obtained by the robust median estimator is almost the same as the mean of the noise standard deviation. Based on this property, the noise model parameters are estimated by the least square method. Simulation results show that the estimation performance using our proposed algorithm is compatible with the performance of the existing method. Our method can generate good parameter estimation results with reduced computational complexity. (C) 2013 Elsevier B.V. All rights reserved.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherELSEVIER SCIENCE BV-
dc.titleSimplified noise model parameter estimation for signal-dependent noise-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.sigpro.2013.10.002-
dc.identifier.scopusid2-s2.0-84887291721-
dc.identifier.wosid000330203500013-
dc.identifier.bibliographicCitationSIGNAL PROCESSING, v.96, pp 266 - 273-
dc.citation.titleSIGNAL PROCESSING-
dc.citation.volume96-
dc.citation.startPage266-
dc.citation.endPage273-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusPOISSON INTENSITY ESTIMATION-
dc.subject.keywordPlusWAVELET-DOMAIN-
dc.subject.keywordPlusHYPERSPECTRAL IMAGES-
dc.subject.keywordPlusGAUSSIAN NOISE-
dc.subject.keywordAuthorSignal dependent noise model-
dc.subject.keywordAuthorNoise parameter estimation-
dc.subject.keywordAuthorRobust median estimator-
dc.subject.keywordAuthorDenoising-
dc.subject.keywordAuthorMean of noise standard deviation-
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