In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees the uniqueness of the solution and the stabilization of the algorithm. For solving the new convex variational model, a primal-dual algorithm is proposed, and its convergence is studied. The paper ends with a report on numerical tests for the simultaneous deblurring and denoising of images subject to multiplicative noise. A comparison with other methods is provided as well.
S I a M Journal on Imaging Sciences, 2013, Vol 6, Issue 3, p. 1598-1625
Convexity; Deblurring; Multiplicative noise; Primal-dual algorithm; Total variation regularization; Variational model