DocumentCode :
2822633
Title :
A parallel context model for level information in CABAC
Author :
Gao, Min ; Fan, Xiaopeng ; Wang, Qiang ; Zhao, Debin ; Gao, Wen
Author_Institution :
Dept. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
fYear :
2011
fDate :
6-9 Nov. 2011
Firstpage :
1
Lastpage :
4
Abstract :
Context-adaptive binary arithmetic coding (CABAC) is one of the most time-consuming modules in H.264/AVC decoder. A potential way to accelerate CABAC is by parallelization. However, the context modeling process for level information in CABAC is highly serial in nature and can not be parallelized in the coefficient level. In order to improve the throughput of CABAC, in this paper we present a parallel context model for level information. The key feature of the model is to use the total number of the significant coefficients and the scanned position of the current significant coefficient in the quantized transform coefficient block as the context information. Since the context information is independent of the previously decoded significant coefficients, parallel decoding in coefficient level is achieved. In experiments, the proposed context model achieves the similar compression efficiency as the CABAC.
Keywords :
adaptive codes; arithmetic codes; binary codes; decoding; transforms; video coding; H.264-AVC decoder; context modeling process; context-adaptive binary arithmetic coding; level information; parallel context model; parallel decoding; quantized transform coefficient; significant coefficient; Context; Context modeling; Decoding; Encoding; Indexes; Probability distribution; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Communications and Image Processing (VCIP), 2011 IEEE
Conference_Location :
Tainan
Print_ISBN :
978-1-4577-1321-7
Electronic_ISBN :
978-1-4577-1320-0
Type :
conf
DOI :
10.1109/VCIP.2011.6115996
Filename :
6115996
Link To Document :
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