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Fast intra prediction algorithm with enhanced sampling decision for H.265/HEVC

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

H.265/HEVC is the latest video coding standard, which offers superior compression performance against H.264/AVC at the cost of greater complexity in its encoding process. In the intra coding of HEVC, a Coding Unit (CU) is recursively divided into a quad-tree-based structure from the Largest Coding Unit (LCU). At each level, up to 35 potential intra modes should be checked. However, examining all these modes is very timeconsuming. In this paper, an intra mode decision algorithm is proposed that reduces the required computations while having negligible effect on Rate-Distortion (RD) performance. A rough mode decision method based on image component sampling is proposed to reduce the number of candidate modes for rough mode decision and RD optimization. To balance the quality and performance, the decision to reduce the full search is made with a thresholds that is dynamically updated based on the Quantization Parameter (QP) and CU size of each recursive step. Experiments show that our algorithm can achieve a reasonable trade-off between encoding quality and efficiency. The saving in encoding time is between 30.0% to 45.0% while BD-RATE may increase by up to 0.5% for H.265/HEVC reference software HM 16.9 under all-intra configuration.

原文English
主出版物標題VISAPP
編輯Francisco Imai, Alain Tremeau, Jose Braz
發行者SciTePress
頁面60-67
頁數8
ISBN(電子)9789897582257
DOIs
出版狀態Published - 2017
事件12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 - Porto, Portugal
持續時間: 27 2月 20171 3月 2017

出版系列

名字VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
4

Conference

Conference12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017
國家/地區Portugal
城市Porto
期間27/02/171/03/17

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