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Haze removal based on multiple scattering model with superpixel algorithm
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DOI：10.1016/j.sigpro.2016.02.003.png)
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Abstract
En 中文
An efficient method to remove haze from single image based on dark channel prior and the multiple scattering described by atmosphere point spread function (APSF) is proposed in this paper. By means of statistical analysis of the quality assessments for more than 100 images, we apply generalized Gaussian distribution to approximate APSF kernel in the image domain with parameter mapping from both shape similarity and numeric reasonability. Furthermore, a superpixel method is employed for estimating the transmission on the sky and non-sky region, in order to mitigate the halo artifact around the sharp edges and reduce color distortion in the sky region. Therefore, the haze-free images with abundant distinguished details and little halo artifacts can be finally restored by first applying deconvolution to the original hazy image. A series of experiments are additionally implemented to demonstrate the effectiveness and robustness of the proposed dehazing algorithm from both qualitative and quantitative comparisons with the state-of-art. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Dehazing
Multiple scattering
Atmosphere point spread function
Dark channel prior
Superpixel
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