Haze detection and haze degree estimation using dark channels and contrast histograms

Haze and mist always affect the quality of vision. If an image is suffered from haze or mist, then the object is unclear and the image seems whiter than the original one. There are several haze removal algorithms that can reduce the effect of haze and mist. However, if an image is not suffered from the haze and mist, applying the haze removal algorithm may darken the image. Therefore, in computer vision, it is important to determine whether an image is suffered from haze or mist. In this paper, we propose an algorithm that applies the histograms of contrast and dark channels together with the support vector machine to determine whether an image is interfered by haze or mist and the degree of the interference. Simulations show that the proposed algorithm can well distinguish the haze/ mist image from a normal image and accurately determine the haze degree of each image.

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