Image Restoration Using Modifications of Simulated Annealing

Abstract

This article uses a modified version of the simulated annealing algorithm to restore degraded spatial patterns. Standard simulated annealing is used to find an image that is a posterior mode when the number of images under consideration precludes sequential search for a maximum. I incorporate jumping probabilities of the annealing algorithm without randomization. The convergence of our algorithm is proven under a practical annealing schedule. The same idea is also implemented to improve the performance of other modifications of simulated annealing. These include forcing proportions of labels in an image, using posterior marginals, and incorporating an edge process. This article also studies nonlinear presmoothing of the observations.