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Proceedings Paper

Hybrid high-fidelity image compression technique using multiscale wavelets
Author(s): Sunanda Mitra; Richard Andrew Muyshondt; Suryalakshmi Pemmaraju
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Paper Abstract

Multiresolution pyramid decomposition of images for data compression and transmission have been successfully employed using the common frame of linear subband filtering techniques involving wavelet transform, and Laplacian of Gaussian while multiresolution morphological pyramid decomposition represent a different class of nonlinear filters that maybe used as an optimal predictor of an image. To achieve a desired compression ratio for a specific class of images, a compression algorithm needs to be optimized at all stages from initial mapping to final encoding. We demonstrate the superiority of an optimized wavelet transform based compression algorithm over the standard JPEG from a number of distortion measure criteria for radiographic images. We also describe here a hybrid technique for noisy images where a combination of multiresolution morphological and wavelet filters dramatically reduce the inherent noise and hence increase the peak signal to noise ratio at a particular compression level. Noisy synthetic aperture radar images are chosen as illustrations.

Paper Details

Date Published: 1 September 1995
PDF: 8 pages
Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217615
Show Author Affiliations
Sunanda Mitra, Texas Tech Univ. (United States)
Richard Andrew Muyshondt, Texas Tech Univ. (United States)
Suryalakshmi Pemmaraju, Texas Tech Univ. (United States)


Published in SPIE Proceedings Vol. 2569:
Wavelet Applications in Signal and Image Processing III
Andrew F. Laine; Michael A. Unser, Editor(s)

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