Total variation minimizing blind deconvolution with shock filter reference
Image and Vision Computing
Non-smooth SOR for L1-Fitting: Convergence Study and Discussion of Related Issues
Journal of Scientific Computing
Journal of Mathematical Imaging and Vision
Numerical Methods for the Vector-Valued Solutions of Non-smooth Eigenvalue Problems
Journal of Scientific Computing
SIAM Journal on Scientific Computing
SIAM Journal on Imaging Sciences
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In this paper, denoising of smooth (H10-regular) images is considered. The purpose of the paper is basically twofold. First, to compare the denoising methods based on L1- and L2-fitting. Second, to analyze and realize an active-set method for solving the non-smooth optimization problem arising from the former approach. More precisely, we formulate the algorithm, proof its convergence, and give an efficient numerical realization. Several numerical experiments are presented, where the convergence of the proposed active-set algorithm is studied and the denoising properties of the methods based on L1- and L2-fitting are compared. Also a heuristic method for determining the regularization parameter is presented and tested.