Since the density of the haze is di

Since the density of the haze is different from place to place and it is hard to detect in
the hazy image, image dehazing is a challenging task. Early researchers use the traditional
techniques of image processing to remove the haze from a single image (for instance,
histogram-based dehazing methods [4, 5, 6]). However, the dehazing effect is limited,
because a single hazy image can hardly provide much information. Later, researchers try to
improve the dehazing effect with multiple images. In [7, 8], polarization-based methods
are used for dehazing with multiple images which are taken with different degrees of
polarization. Narasimhan et al. [9, 10, 11] propose haze removal approaches with multiple
images of the same scene under different weather conditions. In [12, 13], dehazing is
conducted based on the given depth information.