DocumentCode :
2991174
Title :
Fast Mode Decision Algorithm for Spatial and Coarse Grain Quality Scalable Video Coding
Author :
Huang, Aiai ; Lin, Xiangyu ; Chen, Yaowu
Author_Institution :
Inst. of Adv. Digital Technol. & Instrum., Zhejiang Univ., Hangzhou, China
fYear :
2009
fDate :
18-20 Jan. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In the current scalable video coding (SVC) extension of the H.264/AVC standard, an exhaustive search method is employed to achieve the optimal rate-distortion (RD) cost, but it results in an extremely heavy computational burden. In this paper, an improved fast mode decision algorithm is proposed for spatial and coarse grain quality (CGS) scalable video coding. It makes use of the mode correlation between the base layer and the enhancement layer as well as the mode correlations between macroblocks (MBs) in spatial neighborhood. Specifically, the prediction mode candidates include the mode predicted from the co-located MB in the base layer, the best modes of spatial neighboring MBs, and the SKIP mode. Combined with an early termination check and a refinement search, the coding complexity can be reduced while preserving good quality. From the experimental results, the proposed method can reduce the total encoding time by up to 52.25% with negligible quality degradation.
Keywords :
rate distortion theory; video coding; H.264/AVC standard; SKIP mode; base layer; coarse grain quality scalable video coding; enhancement layer; exhaustive search method; fast mode decision algorithm; optimal rate-distortion cost; spatial grain quality scalable video coding; Automatic voltage control; Degradation; IEC standards; ISO standards; Instruments; Rate-distortion; Scalability; Spatial resolution; Static VAr compensators; Video coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5272-9
Type :
conf
DOI :
10.1109/CNMT.2009.5374778
Filename :
5374778
Link To Document :
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