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Proceedings Paper

Multiwavelet-transform-based image compression techniques
Author(s): Sathyanarayana S. Rao; Sung H. Yoon; Deepak Shenoy
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Paper Abstract

Multiwavelet transforms are a new class of wavelet transforms that use more than one prototype scaling function and wavelet in the multiresolution analysis/synthesis. The popular Geronimo-Hardin-Massopust multiwavelet basis functions have properties of compact support, orthogonality, and symmetry which cannot be obtained simultaneously in scalar wavelets. The performance of multiwavelets in still image compression is studied using vector quantization of multiwavelet subbands with a multiresolution codebook. The coding gain of multiwavelets is compared with that of other well-known wavelet families using performance measures such as unified coding gain. Implementation aspects of multiwavelet transforms such as pre-filtering/post-filtering and symmetric extension are also considered in the context of image compression.

Paper Details

Date Published: 23 October 1996
PDF: 12 pages
Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255280
Show Author Affiliations
Sathyanarayana S. Rao, Villanova Univ. (United States)
Sung H. Yoon, Villanova Univ. (United States)
Deepak Shenoy, Villanova Univ. (United States)

Published in SPIE Proceedings Vol. 2825:
Wavelet Applications in Signal and Image Processing IV
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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