Abstract

The atmospheric scattering model includes two crucial parameters for dehazing: global atmospheric light and the transmission map. Most previous dehazing methods need to obtain these two parameters separately, which makes dehazing a difficult and ill-posed problem. Here, a new unified function that includes both the crucial parameters for haze removal is proposed. Then the haze removal network, which now needs to learn only one function during training, is proposed. Image dehazing can be performed as a simple addition of the haze removal function with the input hazy image. Experimental results show that the proposed method gives better subjective results for indoor and outdoor synthesized images as well as natural images compared to previous state-of-the-art methods. Quantitative evaluation results show that the proposed haze removal network gives improved objective results compared with the same previous methods.

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