We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The solution of the non-trivial optimization problem, due to the non-smooth non-convex proposed model, is efficiently obtained by an Alternating Directions Method of Multipliers (ADMM), which in particular reduces the solution to a sequence of convex optimization sub-problems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.
Lanza, A., Sciacchitano, F., Morigi, S., Sgallari, F. (2017). A Unified Framework for the Restoration of Images Corrupted by Additive White Noise. Cham : Springer International Publishing [10.1007/978-3-319-58771-4_40].
A Unified Framework for the Restoration of Images Corrupted by Additive White Noise
LANZA, ALESSANDRO;MORIGI, SERENA;SGALLARI, FIORELLA
2017
Abstract
We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The solution of the non-trivial optimization problem, due to the non-smooth non-convex proposed model, is efficiently obtained by an Alternating Directions Method of Multipliers (ADMM), which in particular reduces the solution to a sequence of convex optimization sub-problems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
