DocumentCode
447553
Title
Improved best prediction mode(s) selection methods based on structural similarity in H.264 I-frame encoder
Author
Mai, Zhi-Yi ; Yang, Chun-Ling ; Xie, Sheng-Li
Author_Institution
School of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Volume
3
fYear
2005
fDate
10-12 Oct. 2005
Firstpage
2673
Abstract
In H.264 I-frame encoder, the best infra prediction modes are chosen by utilizing the rate-distortion (R-D) optimization whose distortion is the sum of the squared differences (SSD, means the same as MSE) between the reconstructed and the original blocks. Recently a new image measurement called structural similarity (SSIM) based on the degradation of structural information was brought forward. It is proved that the SSIM can provide a better approximation to the perceived image distortion than the currently used PSNR (or MSE). In this paper, we propose two improved prediction modes selection methods based on SSIM for H.264 I-frame encoder. The first one is the SSIM-based R-D optimization (SBRDO) method, the other is the fast mode selection method based on SSIM (FMSBS). Experiments show that both the proposed method can improve the coding efficiency while maintaining the same perceptual reconstructed image quality.
Keywords
image coding; image reconstruction; image resolution; optimisation; rate distortion theory; H.264 I-frame encoder; coding efficiency; fast mode selection method; image distortion; image quality; image reconstruction; prediction mode selection method; rate-distortion optimization; structural similarity image measurement; Degradation; Distortion measurement; Humans; Image coding; Image quality; Image reconstruction; Optimization methods; PSNR; Rate-distortion; Visual system; SSIM-based R-D optimization (SBRDO); Structural Similarity (SSIM); fast mode selection based on SSIM (FMSBS); intra prediction; rate-distortion optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN
0-7803-9298-1
Type
conf
DOI
10.1109/ICSMC.2005.1571553
Filename
1571553
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