Smoothing techniques and difference of convex functions algorithms for image reconstructions

Generalization of hyperbolic smoothing approach for non-smooth and non-Lipschitz functions

“…The motivation of the smoothing studies emerge from the non-smooth problems. Therefore, many interesting non-smooth problems have been solved by using smoothing functions such as min-max [45], sum-max [36], penalty expressions of constrained optimization problems [19] and regularization problems [37,14,21]. Many interesting algorithms are developed and they are effectively applied to the nonsmooth optimization problems [44].…”