Sparse representation based down-sampling image compression

Authors:
Jin Wang;Yunhui Shi;Dehui Kong;Wenpeng Ding;Chunjing Li;Baocai Yin
Affiliations:
Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;Department of Mathematics, Tongji University, Shanghai 200092, China;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
Venue:
Journal of Computational and Applied Mathematics
Year:
2011

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Abstract

In this paper, we give an analytical model of the compression error of down-sampled compression based on wavelet transform, which explains why down-sampling before compression can improve coding performance. And we approximate the missing details due to down-sampling and compression by using the linear combination of a set of basis vectors with L"1 norm. Then we propose a down-sampled and high frequency information approximated coding scheme and apply it to natural images, and achieve gains of both subjective quality and objective quality compared with JPEG2000.