RESTORATION OF QUANTUM-LIMITED IMAGES BY CONVEX PROJECTIONS

We propose a new algorithm for restoring quantum-limited images. The a lgorithm is based on projection methods but uses constraint sets in wh ich set membership is based on probabilistic measures. Such constraint s can be regarded as soft as opposed to hard constraints in which less latitude is given in defining set membership. We show that the restor ation of quantum-limited images has certain similarities to estimating a probability-density function. We apply the algorithm to a widely us ed image phantom and demonstrate that the processed image features les s noise without blurred edges. (C) 1995 Optical Society of America