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Macroblock mode decision scheme for fast encoding in H.264/AVC

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dc.contributor.authorKim, Do Hwan-
dc.contributor.authorLee, Joohyun-
dc.contributor.authorJeon, Kicheol-
dc.contributor.authorJeong, Jechang-
dc.date.accessioned2022-12-21T09:52:35Z-
dc.date.available2022-12-21T09:52:35Z-
dc.date.created2022-09-16-
dc.date.issued2006-11-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180755-
dc.description.abstractTo improve coding efficiency, the H.264/AVC video coding standard uses new coding tools, such as variable block size, quarter-pixel-accuracy motion estimation, multiple reference frames, intra prediction and a loop filter. Using these coding tools, H.264/AVC achieves significant improvement in coding efficiency compared with existing standards. However, the encoder complexity also increases tremendously. Among the tools, macroblock mode decision and motion estimation contribute most to total encoder complexity. This paper focuses on complexity reduction in macroblock mode decision. Of the macroblock modes which can be selected, inter8×8 and intra4×4 have the highest complexity. We propose three methods for complexity reduction, one for intra4×4 in intra-frames, one for inter8×8 in inter-frames, and one for intra4×4 in inter-frames. Simulation results show that the proposed methods save about 56.5% of total encoding time compared with the H.264/AVC reference implementation.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.titleMacroblock mode decision scheme for fast encoding in H.264/AVC-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Do Hwan-
dc.contributor.affiliatedAuthorJeong, Jechang-
dc.identifier.doi10.1007/11922162_43-
dc.identifier.scopusid2-s2.0-33845256038-
dc.identifier.bibliographicCitationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.4261 LNCS, pp.365 - 374-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.citation.volume4261 LNCS-
dc.citation.startPage365-
dc.citation.endPage374-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusComputational complexity-
dc.subject.keywordPlusComputational methods-
dc.subject.keywordPlusComputer simulation-
dc.subject.keywordPlusImage analysis-
dc.subject.keywordPlusMotion estimation-
dc.subject.keywordPlusCoding tools-
dc.subject.keywordPlusEncoding time-
dc.subject.keywordPlusMacroblock mode decision-
dc.subject.keywordPlusPixels-
dc.subject.keywordPlusImage coding-
dc.subject.keywordAuthorFast mode decision-
dc.subject.keywordAuthorH.264/AVC video coding-
dc.subject.keywordAuthorMacroblock mode decision-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/11922162_43-
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서울 의과대학 > 서울 의학교육학교실 > 1. Journal Articles

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