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

Published online by Cambridge University Press:  28 May 2015

R. H. Chan ,
A. Lanza ,
S. Morigi  and
F. Sgallari
R. H. Chan*
Affiliation:
Department of Mathematics, The Chinese University of Hong Kong, Shatin, Hong Kong
A. Lanza*
Affiliation:
Department of Mathematics-CIRAM, University of Bologna, Via Saragozza, 8, Bologna, Italy
S. Morigi*
Affiliation:
Department of Mathematics, University of Bologna, Piazza Porta San Donato, 5, Bologna, Italy
F. Sgallari*
Affiliation:
Department of Mathematics-CIRAM, University of Bologna, Via Saragozza, 8, Bologna, Italy
*
Corresponding author.Email address:rchan@math.cuhk.edu.hk
Corresponding author.Email address:alanza@arces.unibo.it
Corresponding author.Email address:serena.morigi@unibo.it
Corresponding author.Email address:fiorella.sgallari@unibo.it
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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.

Keywords

65F1065F2265K10Ill-posed problemdeblurringfractional order derivativesregularizing iterative method
Type
Research Article
Information
Numerical Mathematics: Theory, Methods and Applications , Volume 6 , Issue 1 , February 2013 , pp. 276 - 296
Copyright
Copyright © Global Science Press Limited 2013

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