An approach to the compression of residual data with GPCA in video coding

Authors:
Lei Yao;Jian Liu;Jiangqin Wu
Affiliations:
College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China
Venue:
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Year:
2006

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Abstract

Generalized Principle Component Analysis (GPCA) is a global solution to identify a mixture of linear models for signals. This method has been proved to be efficient in compressing natural images. In this paper we try to introduce GPCA into video coding. We focus on encoding residual frames with GPCA in place of classical DCT, and also propose to use it in MCTF based scalable video coding. Experiments show that GPCA really gets better PSNR with the same amount of data components as DCT, and this method is promising in our scalable video coding scheme.