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

Authors

  • R. H. Chan, A. Lanza, S. Morigi & F. Sgallari

DOI:

https://doi.org/10.4208/nmtma.2013.mssvm15

Keywords:

Ill-posed problem, deblurring, fractional order derivatives, regularizing iterative method.

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. According 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.

Published

2013-06-01

Issue

Section

Articles