DocumentCode :
465165
Title :
An Efficient Intra Mode Selection Algorithm For H.264 Based On Fast Edge Classification
Author :
Wei, Zhenyu ; Li, Hongliang ; Ngan, King Ngi
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Kowloon
fYear :
2007
fDate :
27-30 May 2007
Firstpage :
3630
Lastpage :
3633
Abstract :
The H.264/AVC is the newest video coding standard recommended by ITU-T and MPEG. Compared with all existing video coding standards, H.264 can achieve superior performance by using many advanced techniques. Intra mode selection is an important feature in H.264 standard and can reduce the spatial redundancy in intra frame significantly. An efficient rate distortion optimization (RDO) technique is employed in H.264 to choose the best mode for each MB, but the computational cost increases drastically. In this paper, a fast intra mode selection algorithm is introduced. By using a fast edge detection method which is based on non-normalized Haar transform (NHT), edge for each sub-block can be extracted. Based on the local edge information, only few intra modes are chosen as mode candidates. A fast RDO algorithm is also proposed in this paper. By combing these two methods, computational load is reduced remarkably. Experimental results show that this fast intra mode selection scheme can lessen about 80% encoding time with little loss of bit-rate and visual quality.
Keywords :
edge detection; rate distortion theory; video coding; H.264; fast edge classification; fast edge detection method; intra mode selection algorithm; non-normalized Haar transform; rate distortion optimization technique; video coding standard; Automatic voltage control; Computational efficiency; Data mining; Encoding; Histograms; Image edge detection; Lagrangian functions; Prediction algorithms; Rate-distortion; Video coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on
Conference_Location :
New Orleans, LA
Print_ISBN :
1-4244-0920-9
Electronic_ISBN :
1-4244-0921-7
Type :
conf
DOI :
10.1109/ISCAS.2007.378539
Filename :
4253467
Link To Document :
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