Poor visibility due to the effects of light absorption and scattering is challenging for processing images captured in foggy weather conditions. This paper proposes an effective algorithm for single image fog removal based on degradation model and group-based sparse representation (GSR). The proposed degradation model is constructed based on a classical physical model, i.e., dichromatic atmospheric scattering model. Then, the new degradation model is integrated into the group-based sparse representation framework. Finally, the single image defogging problem is regarded as an image restoration problem, which can be well optimized by GSR. The method is compared with several well-known algorithms from the literature using qualitative and quantitative evaluations, and results indicate considerable improvement over existing algorithms.
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This work was supported in part by the Fundamental Research Funds for the Central Universities (Grant No. 2019B15314, 30918014107), in part by the National Natural Science Foundation of China (Grant No. 61603124), in part by the Jiangsu Government Study Scholarship, in part by the Six Talents Peak Project of Jiangsu Province (Grant No. XYDXX-007), and in part by the 333 High-Level Talent Training Program of Jiangsu Province.
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Wang, X., Zhang, X., Zhu, H. et al. An Effective Algorithm for Single Image Fog Removal. Mobile Netw Appl 26, 1250–1258 (2021). https://doi.org/10.1007/s11036-019-01340-5
- Image restoration
- Fog removal
- Degradation model
- Group sparse representation