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dc.contributor.authorTseng, Chen-Yuen_US
dc.contributor.authorWang, Sheng-Jyhen_US
dc.date.accessioned2014-12-08T15:30:53Z-
dc.date.available2014-12-08T15:30:53Z-
dc.date.issued2012en_US
dc.identifier.isbn978-1-4673-2533-2en_US
dc.identifier.issn1522-4880en_US
dc.identifier.urihttp://hdl.handle.net/11536/22058-
dc.description.abstractWhile various kinds of local tone mapping approaches have been proposed for contrast enhancement, how to automatically recovering overly bright and/or overly dark regions in an image without introducing extra artifacts still remains a challenging problem. Conventional approaches usually apply a translation-invariant filter to decompose the contrast information of an image into a global component and a detailed component and then adjust the contrast components according to some preselected criteria. However, the use of translation-invariant filter makes it hard to adaptively decompose the contrast information based on local image contents. To overcome this problem, we derive a global optimization approach with the use of cell-based matting Laplacian matrix to obtain more accurate decomposition. Besides, for the adjustment of contrast component, we present a spatially varying gamma adjustment approach that can locally recover poorly exposed regions and properly enhance contrast detail. This translation-varying approach can successfully suppress the halo artifacts without the loss of image details.en_US
dc.language.isoen_USen_US
dc.subjectcontrast enhancementen_US
dc.subjectgamma adjustmenten_US
dc.subjectmatting Laplacianen_US
dc.titleA CELL-BASED MATTING LAPLACIAN FOR CONTRAST ENHANCEMENTen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012)en_US
dc.citation.spage945en_US
dc.citation.epage948en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000319334901006-
Appears in Collections:Conferences Paper