Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration. Here we present a texture-preserving strategy to restore images contaminated by blur and noise. A ccording to a texture detection strategy, we apply spatially adaptive fractional order diffusion. A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective function. Numerical results show the effectiveness of our strategy.

R. H. Chan, A. Lanza, S. Morigi, F.Sgallari (2013). An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization. NUMERICAL MATHEMATICS, 6(1), 276-296 [10.4208/nmtma.2013.mssvm15].

An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization

LANZA, ALESSANDRO;MORIGI, SERENA;SGALLARI, FIORELLA
2013

Abstract

Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration. Here we present a texture-preserving strategy to restore images contaminated by blur and noise. A ccording to a texture detection strategy, we apply spatially adaptive fractional order diffusion. A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective function. Numerical results show the effectiveness of our strategy.
2013
R. H. Chan, A. Lanza, S. Morigi, F.Sgallari (2013). An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization. NUMERICAL MATHEMATICS, 6(1), 276-296 [10.4208/nmtma.2013.mssvm15].
R. H. Chan; A. Lanza; S. Morigi; F.Sgallari
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/134355
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