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Context-based entropy coding in AVS video coding standard

delete2009-04-01
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PRE
AI
L
Li Zhang *
王
王强 (Qiang Wang)
N
Ning Zhang
D
Debin Zhao
X
Xiaolin Wu
高
高雯 (Wen Gao)
DOI:10.1016/j.image.2008.12.001delete
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摘要

摘要

En 中文
In this paper, two context-based entropy coding schemes for AVS Part-2 video coding standard are presented. One is Context-based 2D Variable Length Coding (C2DVLC) as a low complexity entropy coding scheme for AVS Part-2 Jizhun profile. C2DVLC uses Multiple 2D-VLC tables to exploit the statistical features of DCT coefficients for higher coding efficiency. Exponential-Golomb codes are applied in C2DVLC to code the pairs of the run-length of zero coefficients and the non-zero coefficients for lower storage requirement. The other is Context-based Binary Arithmetic Coding (CBAC) as an enhanced entropy coding scheme for AVS Part-2 Jiaqiang profile. CBAC utilizes all previously coded coefficient magnitudes in a DCT block for context modeling. This enables adaptive arithmetic coding to exploit the redundancy of the high-order Markov process in DCT domain with a few contexts. In addition, a context weighting technique is used to further improve CBAC's coding efficiency. Moreover, CBAC is designed to be compatible to C2DVLC in coding elements which simplifies the implementations. The experimental results demonstrate that both C2DVLC and CBAC can achieve comparable or even slightly higher coding performance when compared to Context-Adaptive Variable Length Coding (CAVLC) in H.264/AVC baseline profile and Context-Based Adaptive Binary Arithmetic Coding (CABAC) in H.264/AVC main profile respectively. (C) 2009 Elsevier B.V. All rights reserved.
Keyword:
AVS
DCT video coding
Entropy coding
Context modeling
Variable length coding
Arithmetic coding
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期刊

S
Signal Processing and Image Communication
IF:
2.7
论文数:
2.8K
被引数:
4.2K

机构

H
harbin institute of technology
学者数:
8.0W
论文数: 6.6W
被引数: 66
I
institute of computing technology, cas
学者数:
1.0K
论文数: 878
被引数: 1
M
McMaster University
学者数:
3.6W
论文数: 3.3W
被引数: 4.4W
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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