This paper investigates the use of cascadic multiresolution methods for image deblurring. Iterations with a conjugate gradient-type method are carried out on each level, and terminated by a stopping rule based on the discrepancy principle. Prolongation is carried out by nonlinear edge-preserving operators, which are defined via PDEs associated with Perona–Malik or total variation-type models. Computed examples demonstrate the effectiveness of the methods proposed.
S.Morigi, L.Reichel, F.Sgallari, A.Shyshkov (2008). Cascadic Multiresolution Methods for Image Deblurring. SIAM JOURNAL ON IMAGING SCIENCES, 1, 51-74 [10.1137/070694065].
Cascadic Multiresolution Methods for Image Deblurring
MORIGI, SERENA;SGALLARI, FIORELLA;
2008
Abstract
This paper investigates the use of cascadic multiresolution methods for image deblurring. Iterations with a conjugate gradient-type method are carried out on each level, and terminated by a stopping rule based on the discrepancy principle. Prolongation is carried out by nonlinear edge-preserving operators, which are defined via PDEs associated with Perona–Malik or total variation-type models. Computed examples demonstrate the effectiveness of the methods proposed.File in questo prodotto:
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