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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.