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1 September 1990 Optimal constraint parameter estimation for constrained image restoration
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Proceedings Volume 1360, Visual Communications and Image Processing '90: Fifth in a Series; (1990) https://doi.org/10.1117/12.24151
Event: Visual Communications and Image Processing '90, 1990, Lausanne, Switzerland
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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stanley J. Reeves and Russell M. Mersereau "Optimal constraint parameter estimation for constrained image restoration", Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); https://doi.org/10.1117/12.24151
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