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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Special Section on Smart Multimedia & Communication Systems
Spatio-Temporal Prediction Based Algorithm for Parallel Improvement of HEVC
Xiantao JIANGTian SONGTakashi SHIMAMOTOWen SHILisheng WANG
Author information
  • Xiantao JIANG

    Department of Electronics and Information Engineering, Tongji University
    Department of Electrical and Electronics Engineering, Tokushima University

  • Tian SONG

    Department of Electrical and Electronics Engineering, Tokushima University

  • Takashi SHIMAMOTO

    Department of Electrical and Electronics Engineering, Tokushima University

  • Wen SHI

    Department of Electrical and Electronics Engineering, Tokushima University

  • Lisheng WANG

    Department of Electronics and Information Engineering, Tongji University

Corresponding author

ORCID
Keywords:HEVC,spatio-temporal prediction,parallel processing,complexity
JOURNALRESTRICTED ACCESS

2015 Volume E98.AIssue 11Pages 2229-2237

DOIhttps://doi.org/10.1587/transfun.E98.A.2229
Details
  • Published: November 01, 2015Manuscript Received: December 22, 2014Released on J-STAGE: November 01, 2015Accepted: -Advance online publication: -Manuscript Revised: June 03, 2015
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Abstract
The next generation high efficiency video coding (HEVC) standard achieves high performance by extending the encoding block to 64×64. There are some parallel tools to improve the efficiency for encoder and decoder. However, owing to the dependence of the current prediction block and surrounding block, parallel processing at CU level and Sub-CU level are hard to achieve. In this paper, focusing on the spatial motion vector prediction (SMVP) and temporal motion vector prediction (TMVP), parallel improvement for spatio-temporal prediction algorithms are presented, which can remove the dependency between prediction coding units and neighboring coding units. Using this proposal, it is convenient to process motion estimation in parallel, which is suitable for different parallel platforms such as multi-core platform, compute unified device architecture (CUDA) and so on. The simulation experiment results demonstrate that based on HM12.0 test model for different test sequences, the proposed algorithm can improve the advanced motion vector prediction with only 0.01% BD-rate increase that result is better than previous work, and the BDPSNR is almost the same as the HEVC reference software.
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© 2015 The Institute of Electronics, Information and Communication Engineers
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