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Proceedings Paper

Optimal constraint parameter estimation for constrained image restoration
Author(s): Stanley J. Reeves; Russell M. Mersereau
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Paper Abstract

Because of the presence of noise in blurred images, an image restoration algorithm must constrain the solution to achieve stable restoration results. Such constraints are often introduced by biasing the restoration toward the minimizer of a given functional. However, a proper choice of the degree of bias is critical to the success of this approach. Generally, the appropriate bias cannot be chosen a priori and must be estimated from the blurred and noisy image. Cross-validation is introduced as a method for estimating the optimal degree of bias for a general form of the constraint functional. Results show that this constraint is capable of improving restoration results beyond the capabilities of the traditional Tikhonov constraint.

Paper Details

Date Published: 1 September 1990
PDF: 9 pages
Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); doi: 10.1117/12.24151
Show Author Affiliations
Stanley J. Reeves, Auburn Univ. (United States)
Russell M. Mersereau, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1360:
Visual Communications and Image Processing '90: Fifth in a Series
Murat Kunt, Editor(s)

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