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Proceedings Paper

Image restoration using statistical wavelet models
Author(s): Juan Liu; Pierre Moulin
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Paper Abstract

In this paper, we propose an image restoration algorithm based on state-of-the-art wavelet domain statistical models. We present an efficient method to estimate the model parameters from the observations, and solve the restoration problem in orthonormal and translation--invariant (TI) wavelet domains. Substantial improvements over previous wavelet-based restoration methods are obtained. The use of a TI wavelet transform further enhances the restoration performance. We study the improvement from the viewpoint of Bayesian estimation theory and show that replacing an estimator with its TI version will reduce the expected risk if the signal and the degradation model are stationary.

Paper Details

Date Published: 5 December 2001
PDF: 14 pages
Proc. SPIE 4478, Wavelets: Applications in Signal and Image Processing IX, (5 December 2001); doi: 10.1117/12.449704
Show Author Affiliations
Juan Liu, Univ. of Illinois/Urbana-Champaign (United States)
Pierre Moulin, Univ. of Illinois/Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 4478:
Wavelets: Applications in Signal and Image Processing IX
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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