A relaxed fixed point method for a mean curvature-based denoising model

Fenlin Yang, Ke Chen, Bo Yu*, Donghui Fang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Mean curvature-based energy minimization denoising model by Zhu and Chan offers one approach for restoring both smooth (no edges) and non-smooth (with edges) images. The resulting fourth-order partial differential equations arising from minimization of this model is non-trivial to solve due to appearance of a high nonlinearity and stiffness term, because simple alternative methods such as the fixed point method and the primal dual method do not work. In this paper, we first present a relaxed fixed point method for solving such equations and further to combine with a homotopy algorithm to achieve fast convergence. Numerical experiments show that our method is able to maintain all important information in the image, and at the same time to filter out noise.

Original languageEnglish
Pages (from-to)274-285
Number of pages12
JournalOptimization Methods and Software
Volume29
Issue number2
DOIs
Publication statusPublished - 4 Mar 2014

Keywords

  • homotopy method
  • image denoising
  • mean curvature model
  • relaxed fixed point method

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