An Investigation on Semismooth Newton based Augmented Lagrangian Method for Image Restoration

The augmented Lagrangian method (also called as of multipliers) is an important and powerful optimization for lots smooth or nonsmooth variational problems in modern signal processing, imaging optimal control. However, one usually needs to solve a coupled nonlinear system equations, which very challenging. In this paper, we propose several semismooth Newton methods arising subproblems image restoration finite dimensional spaces, leads highly efficient competitive algorithms processing. With the analysis metric subregularities corresponding functions, give both global convergence local linear rate proposed with solvers.