This work tackles the problem of image restoration, a crucial task in many fields of applied sciences, focusing on removing degradation caused by blur and noise during the acquisition process. Drawing inspiration from the multi-penalty approach based on the Uniform Penalty principle, discussed in previous work, here we develop a new image restoration model and an iterative algorithm for its effective solution. The model incorporates pixel-wise regularization terms and establishes a rule for parameter selection, aiming to restore images through the solution of a sequence of constrained optimization problems. To achieve this, we present a modified version of the Newton Projection method, adapted to multi-penalty scenarios, and prove its convergence. Numerical experiments demonstrate the efficacy of the method in eliminating noise and blur while preserving the image edges.
An Automatic Pixel-Wise Multi-Penalty Approach to Image Restoration / Bortolotti V.; Landi G.; Zama F.. - In: JOURNAL OF IMAGING. - ISSN 2313-433X. - ELETTRONICO. - 9:11(2023), pp. 249.1-249.15. [10.3390/jimaging9110249]
An Automatic Pixel-Wise Multi-Penalty Approach to Image Restoration
Bortolotti V.Membro del Collaboration Group
;Landi G.Investigation
;Zama F.
Writing – Review & Editing
2023
Abstract
This work tackles the problem of image restoration, a crucial task in many fields of applied sciences, focusing on removing degradation caused by blur and noise during the acquisition process. Drawing inspiration from the multi-penalty approach based on the Uniform Penalty principle, discussed in previous work, here we develop a new image restoration model and an iterative algorithm for its effective solution. The model incorporates pixel-wise regularization terms and establishes a rule for parameter selection, aiming to restore images through the solution of a sequence of constrained optimization problems. To achieve this, we present a modified version of the Newton Projection method, adapted to multi-penalty scenarios, and prove its convergence. Numerical experiments demonstrate the efficacy of the method in eliminating noise and blur while preserving the image edges.File | Dimensione | Formato | |
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