DocumentCode
1818186
Title
Low Complexity Hierarchical Prediction Algorithm for H.264/SVC
Author
Abdelazim, Abdelrahman ; Mein, Stephen ; Varley, Martin ; Ait-Boudaoud, Djamel
Author_Institution
Sch. of Comput., Eng. & Phys. Sci., Univ. of Central Lancashire, Preston, UK
fYear
2010
fDate
14-17 Nov. 2010
Firstpage
252
Lastpage
257
Abstract
In the scalable video coding extension of the H.264/AVC standard, an exhaustive search technique is used to select the best coding mode for each macroblock. This technique achieves the highest possible coding efficiency, but it demands a higher video encoding computational complexity which constrains its use in many practical applications. This paper proposes combined fast sub-pixel motion estimation and a fast mode decision algorithm for inter-frame coding for temporal, spatial, and coarse grain signal-to-noise ratio scalability. It makes use of correlation between the macroblock and its enclosed partitions at different layers. Experimental results show that the scheme reduces the computational complexity significantly with negligible coding loss and bit-rate increases when compared to JSVM 9.15 and recently reported fast mode decision algorithms.
Keywords
computational complexity; correlation methods; error statistics; motion estimation; search problems; video coding; H.264/AVC standard; H.264/SVC; JSVM 9.15; bit-rate; coding efficiency; coding loss; coding mode; correlation; exhaustive search technique; fast mode decision algorithm; inter-frame coding; low complexity hierarchical prediction algorithm; macroblock; scalable video coding extension; signal-to-noise ratio scalability; sub-pixel motion estimation; video encoding computational complexity; Encoding; Motion estimation; Pixel; Probability; Scalability; Signal to noise ratio; Static VAr compensators; Fast Mode Decision; Fast Motion Estimation; GOP; H264; SVC; Sub-Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Video Technology (PSIVT), 2010 Fourth Pacific-Rim Symposium on
Conference_Location
Singapore
Print_ISBN
978-1-4244-8890-2
Type
conf
DOI
10.1109/PSIVT.2010.49
Filename
5673869
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