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Bit Allocation Algorithm With Novel View Synthesis Distortion Model for Multiview Video Plus Depth Coding

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dc.contributor.authorChung, Tae-Young-
dc.contributor.authorSim, Jae-Young-
dc.contributor.authorKim, Chang-Su-
dc.date.accessioned2021-09-05T06:23:59Z-
dc.date.available2021-09-05T06:23:59Z-
dc.date.created2021-06-15-
dc.date.issued2014-08-
dc.identifier.issn1057-7149-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/97791-
dc.description.abstractAn efficient bit allocation algorithm based on a novel view synthesis distortion model is proposed for the rate-distortion optimized coding of multiview video plus depth sequences in this paper. We decompose an input frame into nonedge blocks and edge blocks. For each nonedge block, we linearly approximate its texture and disparity values, and derive a view synthesis distortion model, which quantifies the impacts of the texture and depth distortions on the qualities of synthesized virtual views. On the other hand, for each edge block, we use its texture and disparity gradients for the distortion model. In addition, we formulate a bit-rate allocation problem in terms of the quantization parameters for texture and depth data. By solving the problem, we can optimally divide a limited bit budget between the texture and depth data, in order to maximize the qualities of synthesized virtual views, as well as those of encoded real views. Experimental results demonstrate that the proposed algorithm yields the average PSNR gains of 1.98 and 2.04 dB in two-view and three-view scenarios, respectively, as compared with a benchmark conventional algorithm.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectOPTIMIZATION-
dc.subject3DTV-
dc.titleBit Allocation Algorithm With Novel View Synthesis Distortion Model for Multiview Video Plus Depth Coding-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Chang-Su-
dc.identifier.doi10.1109/TIP.2014.2327801-
dc.identifier.scopusid2-s2.0-84903289321-
dc.identifier.wosid000338354600003-
dc.identifier.bibliographicCitationIEEE TRANSACTIONS ON IMAGE PROCESSING, v.23, no.8, pp.3254 - 3267-
dc.relation.isPartOfIEEE TRANSACTIONS ON IMAGE PROCESSING-
dc.citation.titleIEEE TRANSACTIONS ON IMAGE PROCESSING-
dc.citation.volume23-
dc.citation.number8-
dc.citation.startPage3254-
dc.citation.endPage3267-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlus3DTV-
dc.subject.keywordAuthorMulti-view video plus depth-
dc.subject.keywordAuthorvirtual view synthesis-
dc.subject.keywordAuthorview synthesis distortion-
dc.subject.keywordAuthorbit allocation-
dc.subject.keywordAuthorand rate-distortion optimization-
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