Affiliations: College of Computer Science and Technology, Beijing University of Technology, Beijing, China
Correspondence:
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Corresponding author: Chuang-Bai Xiao, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China. E-mail: cbxiao@bjut.edu.cn.
Abstract: Atmospheric conditions induced by suspended particles, such as fog and haze, severely alter the scene appearance. In this paper, we proposed a novel adaptive defogging method based on the weighted least squares (WLS) framework, aiming at improving the image visibility under foggy or hazy weather condition. Through the inference of halo intensity and smooth degree, our method adopts image fusion technology based on multi-scale WLS filter to estimate atmospheric veil, and restores the foggy image by inverting the atmospheric scattering model. The results on the experiments of comparison with traditional algorithms demonstrate that the proposed method can achieve more accurate restoration, resulting in a great improvement in image visibility.
