Hybrid high-fidelity image compression technique using multiscale wavelets

Sunanda Mitra, Richard A. Muyshondt, Suryalakshmi Pemmaraju

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsAndrew F. Laine, Michael A. Unser, Mladen V. Wickerhauser
Pages623-630
Number of pages8
Edition2/-
StatePublished - 1995
EventWavelet Applications in Signal and Image Processing III. Part 1 (of 2) - San Diego, CA, USA
Duration: Jul 12 1995Jul 14 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Number2/-
Volume2569
ISSN (Print)0277-786X

Conference

ConferenceWavelet Applications in Signal and Image Processing III. Part 1 (of 2)
CitySan Diego, CA, USA
Period07/12/9507/14/95

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