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Proceedings Paper

Image compression by parameterized-model coding of wavelet packet near-best bases
Author(s): Carl Taswell
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Paper Abstract

Top-down tree search algorithms with non-additive information cost comparisons as decision criteria have recently been proposed by Taswell for the selection of near-best bases in wavelet packet transforms. Advantages of top-down non-additive near-best bases include faster computation speed, smaller memory requirement, and extensibility to biorthogonal wavelets in addition to orthogonal wavelets. A new compression scheme called parameterized-model coding was also proposed and demonstrated for one-dimensional signals. These methods are extended here to two-dimensional signals and applied to the compression of images. Significant improvement in compression while maintaining comparable distortion is demonstrated for parameterized-model coding relative to quantized-scalar coding. In general, the lossy compression scheme is applicable for low bit rate coding of the M largest packets of wavelet packet decompositions with wavelet packet basis libraries and the M atoms of matching pursuit decompositions with time-frequency atom dictionaries.

Paper Details

Date Published: 6 April 1995
PDF: 9 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205382
Show Author Affiliations
Carl Taswell, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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