Single image haze removal using sharpness evaluation index

Abstract

In order to reproduce clear scenes of visible light images in hazy weather, and effectively suppress the image contrast and clarity degradation caused by haze degradation. General defogging methods do not take into account the uneven distribution of fog concentration and defog the whole image directly. Outdoor scenes of defogging is required to take into account the distribution of fog concentration. In this paper, a natural image defogging method for clarity evaluation indicators is proposed. We select representative indicators for fog concentration classification based on depth information and also obtain global transmittance maps. Compared with traditional method and the deep learning defogging method, The results outperform the other algorithms in different metrics. Experiments show that our results outperform other algorithms in various metrics and are robust to inhomogeneous fog.