A Unified Framework for Image Modeling and Estimation Using Measurement Constraints
Ishwar, Prakash
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https://hdl.handle.net/2142/80794
Description
Title
A Unified Framework for Image Modeling and Estimation Using Measurement Constraints
Author(s)
Ishwar, Prakash
Issue Date
2002
Doctoral Committee Chair(s)
Moulin, Pierre
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Statistics
Language
eng
Abstract
A new, rich class of maxent priors for natural images from imprecise subband statistics in multiple orthonormal wavelet bases is developed. Experimental results for the problem of image restoration in additive white Gaussian noise are presented. Denoising and restoration of natural images using algorithms based on these maxent priors demonstrate significant improvements in terms of both perceptual quality as well as mean-squared error over classical approaches such as adaptive Wiener filtering. Under appropriate conditions, a variety of classical wavelet-domain image models and denoising algorithms are shown to be subsumed by the proposed multiple-domain maxent modeling and estimation framework.
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