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Proceedings Paper

Feature-coding-based algorithm for high-fidelity image compression
Author(s): Tianxu Zhang; Kai Lin; Zhen C. Zuo; Yiu Sang Moon
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Paper Abstract

Lossless or high fidelity compression of images is a critical problem yet to be solved in a number of areas such as satellite remote sensing, medical imaging and color image printing. Now the requirement for preservation of image details has rendered the compression method that preserves important information inapplicable. Limited by the storage capacity and transmitting capability, it is very important to enhance the compression ratio of satellite remotely sensed images at high fidelity. Based on wavelet transform and image reconstruction, a feature coding based image compressing algorithm is studied and proposed. This algorithm makes use of the correlativity between the positions of extrema of wavelet transform coefficients as well as the higher-order correlativity between amplitudes of the extrema to perform compression coding, decoding and reconstruction, achieving the result of a compression ratio greater than or equal to 4 at PSNR greater than or equal to 40 db.

Paper Details

Date Published: 18 October 1999
PDF: 9 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365889
Show Author Affiliations
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
Kai Lin, Huazhong Univ. of Science and Technology (China)
Zhen C. Zuo, Huazhong Univ. of Science and Technology (China)
Yiu Sang Moon, Chinese Univ. of Hong Kong (Hong Kong)


Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

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