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Integrated noise modeling for image sensor using bayer domain images

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dc.contributor.authorBaek, Yeul-Min-
dc.contributor.authorKim, Joong-Geun-
dc.contributor.authorCho, Dong-Chan-
dc.contributor.authorLee, Jin-Aeon-
dc.contributor.authorKim, Whoi Yul-
dc.date.accessioned2022-12-20T22:19:52Z-
dc.date.available2022-12-20T22:19:52Z-
dc.date.issued2009-05-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/176802-
dc.description.abstractMost of image processing algorithms assume that an image has an additive white Gaussian noise (AWGN). However, since the real noise is not AWGN, such algorithms are not effective with real images acquired by image sensors for digital camera. In this paper, we present an integrated noise model for image sensors that can handle shot noise, dark-current noise and fixedpattern noise together. In addition, unlike most noise modeling methods, parameters for the model do not need to be re-configured depending on input images once it is made. Thus the proposed noise model is best suitable for various imaging devices. We introduce two applications of our noise model: edge detection and noise reduction in image sensors. The experimental results show how effective our noise model is for both applications.-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleIntegrated noise modeling for image sensor using bayer domain images-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/978-3-642-01811-4_37-
dc.identifier.scopusid2-s2.0-67650263815-
dc.identifier.bibliographicCitationLecture Notes in Computer Science, v.5496 LNCS, pp 413 - 424-
dc.citation.titleLecture Notes in Computer Science-
dc.citation.volume5496 LNCS-
dc.citation.startPage413-
dc.citation.endPage424-
dc.type.docTypeConference Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusAdditive White Gaussian noise-
dc.subject.keywordPlusFixed pattern noise-
dc.subject.keywordPlusImage processing algorithm-
dc.subject.keywordPlusImaging device-
dc.subject.keywordPlusInput image-
dc.subject.keywordPlusIntegrated noise models-
dc.subject.keywordPlusNoise modeling-
dc.subject.keywordPlusNoise models-
dc.subject.keywordPlusNoise reductions-
dc.subject.keywordPlusReal images-
dc.subject.keywordPlusAdditive noise-
dc.subject.keywordPlusCameras-
dc.subject.keywordPlusDigital image storage-
dc.subject.keywordPlusGaussian noise (electronic)-
dc.subject.keywordPlusImage processing-
dc.subject.keywordPlusImage sensors-
dc.subject.keywordPlusNoise abatement-
dc.subject.keywordPlusWhite noise-
dc.subject.keywordPlusEdge detection-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-642-01811-4_37-
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서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles

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