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Modified adaptive extended bilateral motion estimation with scene change detection for motion compensated frame rate up-conversion

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dc.contributor.authorPark, Daejun-
dc.contributor.authorJeong, Jechang-
dc.date.accessioned2022-07-16T01:30:39Z-
dc.date.available2022-07-16T01:30:39Z-
dc.date.created2021-05-13-
dc.date.issued2014-12-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/158409-
dc.description.abstractIn this paper, a novel frame rate up conversion (FRUC) algorithm using modified adaptive extended bilateral motion estimation (MAEBME) with scene change detection is proposed. Conventionally, extended bilateral motion estimation (EBME) carries out bilateral motion estimation (BME) twice on the same region, therefore involves high complexity. Adaptive extended bilateral motion estimation (AEBME) is proposed to reduce complexity and increase visual quality by using block type matching process and considering frame motion activity. In MAEBME algorithm, calculated edge information is used to detect a global scene cut change, and then is used in block type matching process whether to use EBME. Finally, overlapped block motion compensation (OBMC) and motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which OBMC is employed adaptively by considering frame motion activity. Experimental results show that this proposed algorithm has outstanding performance and fast computation comparing with the anchor algorithms.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer Verlag-
dc.titleModified adaptive extended bilateral motion estimation with scene change detection for motion compensated frame rate up-conversion-
dc.typeArticle-
dc.contributor.affiliatedAuthorJeong, Jechang-
dc.identifier.doi10.1007/978-3-319-14364-4_54-
dc.identifier.scopusid2-s2.0-84916605088-
dc.identifier.bibliographicCitationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp.559 - 567-
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.startPage559-
dc.citation.endPage567-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusDecoding-
dc.subject.keywordPlusImage coding-
dc.subject.keywordPlusMotion compensation-
dc.subject.keywordPlusBilateral motion estimations-
dc.subject.keywordPlusEdge information-
dc.subject.keywordPlusFast computation-
dc.subject.keywordPlusFrame rate up conversion-
dc.subject.keywordPlusMatching process-
dc.subject.keywordPlusMotion-compensated frame interpolations-
dc.subject.keywordPlusOverlapped block motion compensations-
dc.subject.keywordPlusScene change detection-
dc.subject.keywordPlusMotion estimation-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-319-14364-4_54-
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