Abstract

Simulated annealing (SA) is a robust, stable, but computationally costly method for solving ill-posed image-restoration problems. We describe the use of a backprojection operator that identifies those regions of an object estimate that have the greatest likelihood of being in error at each step of the SA process. This reduces computational time by concentrating the computing effort of SA on those pixels most effective in reducing the reconstruction error. The performance of an area-adaptive SA algorithm is evaluated for the restoration of images blurred by a simple pillbox space-invariant and a biconical space-variant point-spread function typical of a depth-measuring optical system.

© 1994 Optical Society of America

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