A Novel Rate and Distortion Estimation Method using Particle Filtering based Prediction for Intra-Predictive Coding of Deep Block Partitioning Structures

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dc.contributor.authorHyun, Myung Hanko
dc.contributor.authorLee, Bumshikko
dc.contributor.authorKim, Munchurlko
dc.date.accessioned2021-03-02T07:10:07Z-
dc.date.available2021-03-02T07:10:07Z-
dc.date.created2020-05-19-
dc.date.created2020-05-19-
dc.date.created2020-05-19-
dc.date.issued2021-02-
dc.identifier.citationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, v.31, no.2, pp.782 - 797-
dc.identifier.issn1051-8215-
dc.identifier.urihttp://hdl.handle.net/10203/281098-
dc.description.abstractIn this paper, we propose a new R/D estimation method for intra-predictive coding with deep block partitioning structures. In our proposed R/D prediction, we adopt a particle filtering based prediction (PFP) to precisely predict intermediate R/D estimates for the next frame in a stochastic manner, which helps increasing the prediction accuracy of fast changing R/D values. Then, based on the intermediate R/D estimates by PFP, we infer an optimal model parameter of the TC’s probability density function (pdf) via convex optimization. We found that the proposed method brings about more stable R/D estimation performance thanks to both the improved prediction accuracy using the PFP for abrupt changes in true R/D values and the precise estimation of the optimal model parameter. Experimental results show that our method significantly reduces the normalized root mean square error from average 3.17 to 0.79 (74.90% reduction) for rate and from average 2.32 to 0.82 (64.61% reduction) for distortion, compared to the state-of-the art method.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleA Novel Rate and Distortion Estimation Method using Particle Filtering based Prediction for Intra-Predictive Coding of Deep Block Partitioning Structures-
dc.typeArticle-
dc.identifier.wosid000615044400028-
dc.identifier.scopusid2-s2.0-85100543007-
dc.type.rimsART-
dc.citation.volume31-
dc.citation.issue2-
dc.citation.beginningpage782-
dc.citation.endingpage797-
dc.citation.publicationnameIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY-
dc.identifier.doi10.1109/TCSVT.2020.2989185-
dc.contributor.localauthorKim, Munchurl-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorEncoding-
dc.subject.keywordAuthorTransforms-
dc.subject.keywordAuthorEstimation-
dc.subject.keywordAuthorDistortion-
dc.subject.keywordAuthorCopper-
dc.subject.keywordAuthorRate distortion theory-
dc.subject.keywordAuthorFiltering-
dc.subject.keywordAuthorRate and distortion estimation-
dc.subject.keywordAuthorparticle filtering-
dc.subject.keywordAuthorversatile video coding (VVC)-
dc.subject.keywordAuthorVVC test model (VTM)-
dc.subject.keywordAuthormulti-type tree (MTT)-
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