Physical-based optimization for non-physical image dehazing methods

Javier Vazquez-Corral, Graham D. Finlayson, Marcelo Bertalmío

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
18 Downloads (Pure)


Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied. Some of the most successful image dehazing algorithms are based on image processing methods but do not follow any physical image formation model, which limits their performance. In this paper, we propose a post-processing technique to alleviate this handicap by enforcing the original method to be consistent with a popular physical model for image formation under haze. Our results improve upon those of the original methods qualitatively and according to several metrics, and they have also been validated via psychophysical experiments. These results are particularly striking in terms of avoiding over-saturation and reducing color artifacts, which are the most common shortcomings faced by image dehazing methods.

Original languageEnglish
Pages (from-to)9327-9339
Number of pages13
JournalOptics Express
Issue number7
Early online date18 Mar 2020
Publication statusPublished - 30 Mar 2020



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