Fast intra mode decision algorithm for HEVC based on dominant edge assent distribution

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• 作者：Yingbiao Yao ; Xiaojuan Li ; Yu Lu
• 关键词：HEVC ; Mode decision ; Intra prediction ; Dominant edge assent distribution
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：75
• 期：4
• 页码：1963-1981
• 全文大小：840 KB
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• 作者单位：Yingbiao Yao (1)
  Xiaojuan Li (1)
  Yu Lu (1)
  
  1. College of Communication Engineering, Hangzhou Dianzi University, Hangzhou, 310018, People’s Republic of China
  
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721

文摘

As the latest video coding standard, high efficiency video coding (HEVC) is a successor to H.264/AVC. To improve the coding efficiency of intra coding, HEVC employs a flexible quad-tree coding block partitioning structure and 35 intra prediction modes. The optimal prediction mode is selected through rough mode decision (RMD) and rate distortion optimisation (RDO) process. Due to the huge search space of all of the possible depth levels (CU sizes) and intra prediction modes, intra coding of HEVC is a very time-consuming and complicated process, which limits the application of HEVC. In order to reduce the intra coding complexity, we propose a fast mode decision algorithm for HEVC intra prediction which is based on dominant edge assent (DEA) and its distribution. The four DEAs in the directions of degree 0, 45, 90 and 135 are computed first; then, the dominant edge is decided according to the minimum DEA. Next, a subset of prediction modes in accordance with the dominant edge is chosen for the RMD process. The rule is as follows: When the standard deviation of DEA is distinctly small, we skip the RMD process and take the direct current (DC) mode and planar modes as the candidate modes for the RDO process; when the minimum DEA is distinctly small, we select seven modes as the candidate modes for the RMD process; otherwise, we select 11 modes for the RMD process. Lastly, the prediction unit (PU) size-based number of RDO candidate modes (3 for PU size 4 × 4 and 8 × 8 and 1 for the other PU sizes) is modified according to experimental analysis. Compared with HM 9.1, Shen’s proposal and da Silva’s proposal, which are two state-of-the-art fast intra mode decision algorithms, the experimental results reveal that the proposed algorithm can save 36.26, 13.85 and 20.81 % coding time on average with a negligible loss of coding efficiency, respectively.