Single image dehazing and denoising: A fast variational approach

Faming Fang, Fang Li, Tieyong Zeng*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

56 Citations (Scopus)
18 Downloads (Pure)


In this paper, we propose a new fast variational approach to dehaze and denoise simultaneously. The proposed method first estimates a transmission map using a windows adaptive method based on the celebrated dark channel prior. This transmission map can significantly reduce the edge artifact in the resulting image and enhance the estimation precision. The transmission map is then converted to a depth map, with which the new variational model can be built to seek the final haze- and noise-free image. The existence and uniqueness of a minimizer of the proposed variational model is further discussed. A numerical procedure based on the Chambolle-Pock algorithm is given, and the convergence of the algorithm is ensured. Extensive experimental results on real scenes demonstrate that our method can restore vivid and contrastive haze- and noise-free images effectively.

Original languageEnglish
Pages (from-to)969-996
Number of pages28
JournalSIAM Journal on Imaging Sciences
Issue number2
Publication statusPublished - 13 May 2014

Scopus Subject Areas

  • Mathematics(all)
  • Applied Mathematics

User-Defined Keywords

  • Chambolle-pock algorithm
  • Dehazing
  • Denoising
  • Variational method
  • Weighted total variation


Dive into the research topics of 'Single image dehazing and denoising: A fast variational approach'. Together they form a unique fingerprint.

Cite this