An adaptive strategy for the restoration of textured images using fractional order regularization

R. H. CHAN, A. LANZA, S. MORIGI, F. SGALLARI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

73 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)276-296
Number of pages21
JournalNumerical Mathematics
Volume6
Issue number1
Early online date11 Jan 2013
DOIs
Publication statusPublished - Feb 2013
Externally publishedYes

Keywords

  • Deblurring
  • Fractional order derivatives
  • Ill-posed problem
  • Regularizing iterative method

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