MAP restoration of blurred, photon-limited images via an expectation maximization algorithm

A widely used approach to restoration of images degraded by Poisson noise has been to represent the degraded image as a linear transformation of the intact image plus zero-mean, uncorrelated additive noise. The explicit Poisson model is retained and the authors formulate maximum a posteriori (MAP) image restoration using homogeneous, isotropic Markov random field priors. For this purpose, a deterministic algorithm based upon the expectation maximization (EM) method of optimization is derived. The performance of candidate priors is compared