  Model driven single image dehazing was widely studied on top of different
priors due to its extensive applications. Ambiguity between object radiance and
haze and noise amplification in sky regions are two inherent problems of model
driven single image dehazing. In this paper, a dark direct attenuation prior
(DDAP) is proposed to address the former problem. A novel haze line averaging
is proposed to reduce the morphological artifacts caused by the DDAP which
enables a weighted guided image filter with a smaller radius to further reduce
the morphological artifacts while preserve the fine structure in the image. A
multi-scale dehazing algorithm is then proposed to address the latter problem
by adopting Laplacian and Guassian pyramids to decompose the hazy image into
different levels and applying different haze removal and noise reduction
approaches to restore the scene radiance at different levels of the pyramid.
The resultant pyramid is collapsed to restore a haze-free image. Experiment
results demonstrate that the proposed algorithm outperforms state of the art
dehazing algorithms and the noise is indeed prevented from being amplified in
the sky region.
