Fast Algorithms for Poisson Image Denoising using Fractional-Order Total Variation

In this talk, we present a new Poisson image denoising model based on fractional-order total variation regularization. To obtain its global optimal solution, the augmented Lagrangian method, the Chambolle’s dual algorithm and the primal-dual algorithm are introduced. Experimental results are supplied to demonstrate the effectiveness and efficiency of the proposed algorithms for solving our proposed model, with comparison to the total variation Poisson image denoising model.