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Proceedings Paper

Image compression algorithm using image restoration based on wavelet analysis
Author(s): Zhao Cheng; Tianxu Zhang; Haifeng Lu
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Paper Abstract

In this paper, we consider lossy image compression, which is based on wavelet theory. We introduce image restoration technology into the wavelet compression. By applying image restoration to the low-frequency component obtained by entropy decoding in decompression process, we retrieve a gained high-frequency component, which is the expression of reconstructed image texture in frequency domain. As a benchmark, the algorithm we present is compared to the traditional wavelet compression. The results of comparative experiments show that our method performs better than traditional algorithms. The PSNR in our method is elevated generally, and the reconstructed image is more texture-richer than the traditional approach without restoration.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 749852 (30 October 2009); doi: 10.1117/12.832555
Show Author Affiliations
Zhao Cheng, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Haifeng Lu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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