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Proceedings Paper

New remote-sensing data compression technique using wavelet decomposition and related procedures
Author(s): Chi Hau Chen; Tzu-Hung Cheng
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Paper Abstract

Many image compression techniques have been developed for remote sensing imagery over the last thirty years. What are considered as standard techniques such as the use of principal component analysis, discrete cosine transform, predictive coding, etc. have shown their limitations. Wavelet transform techniques have been increasingly used in recent years. In this paper a new and efficient technique is presented that provides a nearly lossless compression of the multichannel remote sensing imagery by combining the use of wavelet decomposition, non-uniform quantization, arithmetic coding, and geometric vector quantizer (GVQ) to achieve the compression task with very minimal loss. The detailed procedures will be illustrated with real remote sensing images.

Paper Details

Date Published: 4 December 1998
PDF: 4 pages
Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); doi: 10.1117/12.331880
Show Author Affiliations
Chi Hau Chen, Univ. of Massachusetts/Dartmouth (United States)
Tzu-Hung Cheng, Univ. of Massachusetts/Dartmouth (United States)


Published in SPIE Proceedings Vol. 3500:
Image and Signal Processing for Remote Sensing IV
Sebastiano Bruno Serpico, Editor(s)

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