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Author:

Zhang, Ruyi (Zhang, Ruyi.) | Jia, Kebin (Jia, Kebin.) (Scholars:贾克斌) | Liu, Pengyu (Liu, Pengyu.) | Sun, Zhonghua (Sun, Zhonghua.)

Indexed by:

EI

Abstract:

3D-High Efficiency Video Coding (3D-HEVC) contains more encoding viewpoints than traditional HEVC, resulting in a significant increase of coding complexity. In this paper, we propose a low complexity intra-mode selection algorithm to reduce the number of intra-modes by detecting the flat area and texture direction of the depth map. The corresponding intra-prediction modes are skipped when the flat region condition is satisfied. Otherwise, the direction of the edge is detected to decrease the number of angle modes in RMD, which can reduce the intra-coding complexity and coding time cost. Experimental results demonstrate that the proposed algorithm achieves on average 36.48% time saving with negligible degradation of coding performance. © 2019 IEEE.

Keyword:

Visual communication Textures Edge detection Video signal processing Image coding

Author Community:

  • [ 1 ] [Zhang, Ruyi]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 2 ] [Zhang, Ruyi]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 3 ] [Jia, Kebin]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 4 ] [Jia, Kebin]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 5 ] [Liu, Pengyu]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 6 ] [Liu, Pengyu]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China
  • [ 7 ] [Sun, Zhonghua]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 8 ] [Sun, Zhonghua]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • 贾克斌

    [jia, kebin]beijing university of technology, faculty of information technology, beijing, china;;[jia, kebin]beijing key laboratory of computational intelligence and intelligent system, beijing university of technology, beijing, china

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Year: 2019

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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