Image compression algorithm using image restoration based on wavelet analysis

Zhao Cheng; Tianxu Zhang; Haifeng Lu

doi:10.1117/12.832555

30 October 2009 Image compression algorithm using image restoration based on wavelet analysis

Zhao Cheng, Tianxu Zhang, Haifeng Lu

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 749852 (2009) https://doi.org/10.1117/12.832555
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

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.

Citation Download Citation

Zhao Cheng, Tianxu Zhang, and Haifeng Lu "Image compression algorithm using image restoration based on wavelet analysis", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 749852 (30 October 2009); https://doi.org/10.1117/12.832555

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