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author:

Wei, H. (Wei, H..) [1] | Wang, M. (Wang, M..) [2] | Xu, Y. (Xu, Y..) [3] | Liu, Y. (Liu, Y..) [4] | Zhao, T. (Zhao, T..) [5]

Indexed by:

Scopus

Abstract:

The High Efficiency Video Coding (HEVC) adopts increasing number of intra prediction modes and Coding Unit (CU) partitions, in order to diminish its cost at required bitrates. However, its attendant computational complexity is unfavorable in lots of real-world applications. In this paper, we propose a probability-based strategy that benefits a lowcomplexity HEVC intra-encoder and also provides guidance to design low-complexity framework of next generation encoder. The proposed strategy comprises three steps: a candidate mode list initialization based on the estimated winning probabilities of all intra modes, an early termination of intra prediction based on the estimated probability of obtaining the best intra mode, and a pre-decision of Coding Unit (CU) split based on the estimated distributions of the Rate-Distortion (RD) costs. Comprehensive experiments have validated the effectiveness of the proposed algorithm, with a promising simulation performance under Common Test Conditions (CTC). © 2018 IEEE.

Keyword:

Coding Unit (CU); High Efficiency Video Coding (HEVC); Intra prediction; Low-complexity encoder; Video coding

Community:

  • [ 1 ] [Wei, H.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 2 ] [Wang, M.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 3 ] [Xu, Y.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 4 ] [Liu, Y.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 5 ] [Zhao, T.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [Zhao, T.]College of Physics and Information Engineering, Fuzhou UniversityChina

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Source :

VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing

Year: 2018

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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