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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorKuang, Wen_US
dc.creatorTsang, SHen_US
dc.creatorChan, YLen_US
dc.creatorSiu, WCen_US
dc.date.accessioned2024-06-13T01:04:37Z-
dc.date.available2024-06-13T01:04:37Z-
dc.identifier.isbn978-1-5090-2175-8 (Electronic)en_US
dc.identifier.isbn978-1-5090-2176-5 (Print on Demand(PoD))en_US
dc.identifier.urihttp://hdl.handle.net/10397/107212-
dc.description2017 IEEE International Conference on Image Processing (ICIP), 17-20 September 2017, Beijing, Chinaen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication W. Kuang, S. -H. Tsang, Y. -L. Chan and W. -C. Siu, "Fast mode decision algorithm for HEVC screen content intra coding," 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, 2017, pp. 2473-2477 is available at https://doi.org/10.1109/ICIP.2017.8296727.en_US
dc.subjectBayesian decision ruleen_US
dc.subjectFast mode decisionen_US
dc.subjectHigh Efficiency Video Coding (HEVC)en_US
dc.subjectScreen content coding (SCC)en_US
dc.titleFast mode decision algorithm for HEVC screen content intra codingen_US
dc.typeConference Paperen_US
dc.identifier.spage2473en_US
dc.identifier.epage2477en_US
dc.identifier.doi10.1109/ICIP.2017.8296727en_US
dcterms.abstractScreen Content coding (SCC) is one of an extension to High Efficiency Video Coding (HEVC) developed by the Joint Collaborative Team on Video Coding (JCT-VC). It adopts two new coding tools, intra block copy (IBC) and palette (PLT) modes, to improve the compression performance for intra coding. Nevertheless, mode selection causes a substantial increase in encoding complexity. In this paper, a fast mode decision algorithm, which makes use of early mode skip decision based on the Bayesian decision rule using online learning, is proposed. The proposed algorithm is implemented in the SCC reference software SCM-7.0. Experimental results show that the proposed algorithm can achieve 23.2% complexity reduction on average with only 0.58% Bjontegaard delta bitrate loss in All Intra (AI) configurations.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Proceedings of 2017 IEEE International Conference on Image Processing (ICIP), 17-20 September 2017, Beijing, China, p. 2473-2477en_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85045292823-
dc.relation.conferenceIEEE International Conference on Image Processing [ICIP]-
dc.description.validate202404 bckw-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEIE-0576-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextCentre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS9613766-
dc.description.oaCategoryGreen (AAM)en_US
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