Robust Image Restoration Algorithm Using Markov Random Field Model

Abstract

A new method is proposed for image restoration of a gray-level image blurred by an erroneous point spread function and corrupted by either additive or multiplicative noise. The proposed method is based on a Markov random field model with an appropriate line field, whereby it has the ability to restore discontinuities. Robustness is incorporated by the total least-squares term in the posterior energy function. A simulated annealing algorithm is used to implement the proposed method. Simulation results comparing restoration based on minimizing posterior energy functions of type ℓ₂ ℓ₁, total ℓ₁, and total least squares with and without line field are presented.