Title :
Joint learning for side information and correlation model based on linear regression model in distributed video coding
Author :
Liu, Xianming ; Zhao, Debin ; Zhang, Yongbing ; Ma, Siwei ; Huang, Qingming ; Gao, Wen
Author_Institution :
Dept. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
Abstract :
The coding efficiency of distributed video coding system is significantly determined by the side information quality and correlation model. Motivated by theoretical analysis of the maximum likelihood treatment for linear regression model, we propose a novel joint online learning model for side information generation and correlation model estimation in this paper. In our proposed scheme, each pixel in the side information is approximated as the linear weighted combination of samples within a local spatio-temporal neighboring space. Weights are trained in a self-feedback fashion, during which the correlation model parameters can also be achieved. The efficiency of the proposed joint learning model is confirmed experimentally.
Keywords :
correlation methods; maximum likelihood estimation; regression analysis; video coding; correlation model; distributed video coding system; linear regression model; maximum likelihood treatment; self-feedback fashion; side information quality; spatio-temporal neighboring space; Algorithm design and analysis; Computer science; Interpolation; Linear regression; Maximum likelihood decoding; Maximum likelihood estimation; Motion estimation; Statistical distributions; Vectors; Video coding; Side information; correlation model; distributed video coding; joint learning; linear regression model;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5413499