Abstract:

In foggy weather, images of outdoor scene are usually
characterized with poor visibility as well as faint color saturation.
The degraded hazy images may have substantial negative impact
on most computer vision systems. Thus image haze removal is
of the practical significance in engineering. This paper proposes a
fast and effective single image haze removal algorithm on the basis
of the physics imaging model. To extract the global atmospheric
light accurately, we exploit multiple prior rules underlying hazy images,
and put forward a novel measurement to judge the likelihood
that a pixel is regarded as the global atmospheric light. In addition,
the rough transmission map is estimated through a multiscale fusion
process based on the Laplace pyramid transform, and refined
by a total variation model. Experimental results demonstrate the
proposed method outperforms most of the state-of-the-art algorithms
in terms of the dehazing quality, and achieves a trade-off
between the computational efficiency and haze removal capability.