  This paper describes a method to restore degraded images captured in a
participating media -- fog, turbid water, sand storm, etc. Differently from the
related work that only deal with a medium, we obtain generality by using an
image formation model and a fusion of new image priors. The model considers the
image color variation produced by the medium. The proposed restoration method
is based on the fusion of these priors and supported by statistics collected on
images acquired in both non-participating and participating media. The key of
the method is to fuse two complementary measures --- local contrast and color
data. The obtained results on underwater and foggy images demonstrate the
capabilities of the proposed method. Moreover, we evaluated our method using a
special dataset for which a ground-truth image is available.

Computer Vision and Pattern Recognition