Dehazing using Color-Lines

Raanan Fattal


Photographs of hazy scenes typically have low-contrast and offer a limited scene visibility. We describe a new method for single-image dehazing that relies on a generic regularity in natural images in which pixels of small image patches exhibit one-dimensional distributions in RGB space, known as color-lines. We derive a local formation model that explains the color-lines in the context of hazy scenes and use it for recovering the scene transmission based on the lines' offset from the origin. Moreover, this model allows us to identify and dismiss pixels that do not follow the color-line model and hence, unlike existing approaches that follow their assumptions across the entire image, our algorithm validates its hypotheses and obtains more reliable estimates where possible. We also describe a Markov random field model that is dedicated for producing complete and regularized transmission maps. Unlike traditional field models that consist of local coupling, the new model is augmented with long-range connections between pixels of similar color. This allows our algorithm to properly resolve the transmission in isolated regions where nearby pixels do not offer relevant information. An extensive evaluation of our method over different types of images and its comparison to state-of-the-art methods over established benchmark images show a consistent improvement in the accuracy of the estimated scene transmission and recovered haze-free radiances.

Bibtex reference:

author = {Fattal, Raanan},
title = {Dehazing using Color-Lines},
journal = {ACM Transaction on Graphics},
volume = {34},
issue = {1}, 
number = {13},
year = {2014},
publisher = {ACM},
address = {New York, NY, USA},


  • Manuscript
  • Results pages
  • A work on recovering atmopheric light vector automatically can be found here
  • Information abotu liceensing this technology can be found here