We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The key idea behind our proposal relies on a novel hard constraint imposed on the residual of the restoration, namely we characterize a residual whiteness set to which the restored image must belong. As the feasible set is unbounded, solution existence results for the proposed variational model are given. Moreover, based on theoretical derivations as well as on Monte Carlo simulations, we provide well-founded guidelines for setting the whiteness constraint limits. 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, which in particular reduces the solution to a sequence of convex optimization subproblems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.

Alessandro Lanza, S.M. (2018). Whiteness Constraints in a Unified Variational Framework for Image Restoration. JOURNAL OF MATHEMATICAL IMAGING AND VISION, 60(9), 1503-1526 [10.1007/s10851-018-0845-6].

Whiteness Constraints in a Unified Variational Framework for Image Restoration

Alessandro Lanza;Serena Morigi
;
Fiorella Sgallari
2018

Abstract

We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The key idea behind our proposal relies on a novel hard constraint imposed on the residual of the restoration, namely we characterize a residual whiteness set to which the restored image must belong. As the feasible set is unbounded, solution existence results for the proposed variational model are given. Moreover, based on theoretical derivations as well as on Monte Carlo simulations, we provide well-founded guidelines for setting the whiteness constraint limits. 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, which in particular reduces the solution to a sequence of convex optimization subproblems. Numerical results show the potentiality of the proposed model for restoring blurred images corrupted by several kinds of additive white noises.
2018
Alessandro Lanza, S.M. (2018). Whiteness Constraints in a Unified Variational Framework for Image Restoration. JOURNAL OF MATHEMATICAL IMAGING AND VISION, 60(9), 1503-1526 [10.1007/s10851-018-0845-6].
Alessandro Lanza, Serena Morigi, Federica Sciacchitano, Fiorella Sgallari
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/653482
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