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dc.contributor.authorJian, Yin-Anen_US
dc.contributor.authorChen, Chun-Chien_US
dc.contributor.authorPeng, Wen-Hsiaoen_US
dc.date.accessioned2017-04-21T06:48:52Z-
dc.date.available2017-04-21T06:48:52Z-
dc.date.issued2014en_US
dc.identifier.isbn978-1-4799-5751-4en_US
dc.identifier.issn1522-4880en_US
dc.identifier.urihttp://hdl.handle.net/11536/134968-
dc.description.abstractThis paper presents a mode-dependent distortion model for H.264/SVC coarse grain SNR scalability. It estimates the base-layer and enhancement-layer\'s distortions with particular consideration of their prediction modes and inter-layer residual prediction. Based on a parametric signal model, the variances of the transformed prediction residual at both layers are first formulated analytically and approximated empirically. The results are then incorporated into the assumption that the transform coefficients are distributed according to the Laplacian distribution to obtain the final distortion estimates. Experimental results confirm its fairly good ability to predict the actual distortions in both the frame and macroblock levels.en_US
dc.language.isoen_USen_US
dc.subjectScalable video codingen_US
dc.subjectcoarse grain SNR scalabilityen_US
dc.subjectdistortion modelingen_US
dc.titleMODE-DEPENDENT DISTORTION MODELING FOR H.264/SVC COARSE GRAIN SNR SCALABILITYen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)en_US
dc.citation.spage3165en_US
dc.citation.epage3169en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000370063603068en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper