In haze removal algorithm based on dark channel prior, the global atmospheric light is influenced easily by the white objects in the image, the sky region of recovered image has distortion phenomenon, and the optimization of the transmission is complicated by the soft matting. In this paper, an improved haze removal algorithm is proposed based on dark channel prior. We combine the prior knowledge with the atmospheric scattering model, estimate the global atmospheric light accurately with quadtree search algorithm, modify the transmission of sky area to avoid distortion, and optimize the transmission using the fast guided filter to recover a high-quality haze-free image. Experimental results demonstrate the superiority of the proposed algorithm. Moreover, the recovered image is clearer and the processing speed improves tenfold nearly compared with dark channel prior.
In haze removal algorithm based on dark channel prior, the global atmospheric light is influenced easily by the white objects in the image, the sky region of recovered image has distortion phenomenon, and the optimization of the transmission is complicated by the soft matting. In this paper, an improved haze removal algorithm is proposed based on dark channel prior. We combine the prior knowledge with the atmospheric scattering model, estimate the global atmospheric light accurately with quadtree search algorithm, modify the transmission of sky area to avoid distortion, and optimize the transmission using the fast guided filter to recover a high-quality haze-free image. Experimental results demonstrate the superiority of the proposed algorithm. Moreover, the recovered image is clearer and the processing speed improves tenfold nearly compared with dark channel prior.
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