Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77658
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dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorZhang, HBen_US
dc.creatorFu, CHen_US
dc.creatorChan, YLen_US
dc.creatorTsang, SHen_US
dc.creatorSiu, WCen_US
dc.date.accessioned2018-08-28T01:33:53Z-
dc.date.available2018-08-28T01:33:53Z-
dc.identifier.issn1051-8215en_US
dc.identifier.urihttp://hdl.handle.net/10397/77658-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2016 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 H. Zhang, C. Fu, Y. Chan, S. Tsang and W. Siu, "Probability-Based Depth Intra-Mode Skipping Strategy and Novel VSO Metric for DMM Decision in 3D-HEVC," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 2, pp. 513-527, Feb. 2018 is available at https://doi.org/10.1109/TCSVT.2016.2612693.en_US
dc.titleProbability-based depth intra-mode skipping strategy and novel VSO metric for DMM decision in 3D-HEVCen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage513en_US
dc.identifier.epage527en_US
dc.identifier.volume28en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1109/TCSVT.2016.2612693en_US
dcterms.abstractMultiview video plus depth format has been adopted as the emerging 3D video representation recently. It includes a limited number of textures and depth maps to synthesize additional virtual views. Since the quality of depth maps influences the view synthesis process, their sharp edges should be well preserved to avoid mixing foreground with background. To address this issue, 3D-High Efficiency Video Coding (HEVC) introduces new coding tools, a partition-based intra mode [depth modeling mode (DMM)], a residual description technique [segmentwise depth coding (SDC)], and a more complex rate-distortion (RD) evaluation with view synthesis optimization (VSO), to provide more accurate predictions and achieve higher compression rate. However, these new techniques introduce a lot of possible candidates, and each of them requires complicated RD calculation in the process of intra-mode decision. They lead to unacceptable computational burden in a 3D-HEVC encoder. Therefore, in this paper, we raise two efficient techniques for depth intra-mode decision. First, by investigating the statistical characteristics of variance distributions in the two partitions of DMM, a simple but efficient criterion based on the squared Euclidean distance of variances (SEDV) is suggested to evaluate RD costs of the DMM candidates instead of the time-consuming VSO process. Second, a probability-based early depth intra-mode decision is proposed to select only the most promising mode and make the early determination of using SDC based on the low-complexity RD cost in rough mode decision. Experimental results show that the proposed algorithm with these two new techniques provides 33%-48% time reduction with little drop in the coding performance compared with the state-of-the-art algorithms.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on circuits and systems for video technology, Feb. 2018, v. 28, no. 2, 7574331, p. 513-527en_US
dcterms.isPartOfIEEE transactions on circuits and systems for video technologyen_US
dcterms.issued2018-02-
dc.identifier.isiWOS:000425036400019-
dc.identifier.scopus2-s2.0-85041957202-
dc.identifier.eissn1558-2205en_US
dc.identifier.artn7574331en_US
dc.identifier.rosgroupid2017006084-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journalen_US
dc.description.validate201808 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEIE-0587-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China (No. 61301109)en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6819403-
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