Fast algorithm for color texture image inpainting using the non-local CTV model

Jinming Duan, Zhenkuan Pan, Baochang Zhang, Wanquan Liu, Xue Cheng Tai

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)

Abstract

The classical non-local Total Variation model has been extensively used for gray texture image inpainting previously, but such model can not be directly applied to color texture image inpainting due to coupling of different image channels in color images. In order to solve the inpainting problem for color texture images effectively, we propose a non-local Color Total Variation model. This model is different from the recently proposed non-local Mumford–Shah model (NL-MS). Technically, the proposed model is an extension of local TV model for gray images but we take account of the relationship between different channels in color images and make use of concepts of the non-local operators. We will analyze how the coupling of different channels of color images in the proposed model makes the problem difficult for numerical implementation with the conventional split Bregman algorithm. In order to solve the proposed model efficiently, we propose a fast heuristic numerical algorithm based on the split Bregman algorithm with introduction of a threshold function. The performance of the proposed model with the proposed heuristic algorithm is compared with the NL-MS model. Extensive numerical experiments have shown that the proposed model and algorithm have superior excellent performance as well as with much faster speed.

Original languageEnglish
Pages (from-to)853-876
Number of pages24
JournalJournal of Global Optimization
Volume62
Issue number4
Early online date19 Mar 2015
DOIs
Publication statusPublished - Aug 2015

Keywords

  • Color texture images inpainting
  • CTV model
  • Mumford-Shad model
  • Non-local model
  • The split Bregman algorithm

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

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