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Proceedings Paper

Image data compression methodologies using discrete wavelets
Author(s): Jun Tian; Chih-Zen Chen; Chih-Chung Chen; Gunasekaran Seetharaman
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Paper Abstract

An image data compression system using discrete wavelets is described and implemented. The two dimensional discrete wavelet transform is computed via subband coding by repeating a three step procedure explained in this paper. The procedure essentially decomposes an image at some resolution and produces four new images which are characterized as low-low, low- high, high-low, and high-high spatial frequency components along the x and y directions. The first component is passed as the input for the next iteration; the second and third components were stored in memory for later processing; and, the fourth component is truncated and reset to zero for a simple codec design. In essence, the compression is accomplished by discarding roughly 25% of the wavelet coefficients at every iteration. The inverse wavelet transform has been applied in a similar fashion, by inserting zeros in place of the discarded values. The results are illustrated using the simplest wavelets called Haar(1910), which is known to be not optimal for image compression but is available in hardware and is inexpensive. The nature of the artifacts introduced by the truncation of high frequency coefficients of Haar transform is also discussed.

Paper Details

Date Published: 22 March 1996
PDF: 12 pages
Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); doi: 10.1117/12.235992
Show Author Affiliations
Jun Tian, Univ. of Southwestern Louisiana (United States)
Chih-Zen Chen, Univ. of Southwestern Louisiana (United States)
Chih-Chung Chen, Univ. of Southwestern Louisiana (United States)
Gunasekaran Seetharaman, Univ. of Southwestern Louisiana (United States)

Published in SPIE Proceedings Vol. 2762:
Wavelet Applications III
Harold H. Szu, Editor(s)

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