Novel single hazy image restoration method based on nonlocal total variation regularization optimization

Renjie He, Yangyu Fan, Zhiyong Wang, David Feng

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Based on the property that the scene radiance is of high contrast and the atmospheric veil is locally smooth, a novel single hazy image restoration method based on nonlocal total variation regularization optimization is proposed in this paper. In order to obtain the atmospheric veil of a hazy image, a constrained nonlocal total variation regularization is firstly applied. Then, the accurate atmospheric veil is estimated using a nonlocal Rudin-Osher-Fatemi model, which is solved by a modified split Bregman method. Experimental results demonstrate that the proposed approach is capable of recovering the scene radiance from a single hazy image effectively, especially for the regions with multi-texture.

Original languageEnglish
Pages (from-to)2509-2514
Number of pages6
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume38
Issue number10
DOIs
StatePublished - 1 Oct 2016

Keywords

  • Contrast enhancement
  • Image dehazing
  • Image processing
  • Regularization optimization

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