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arXiv · 2111.10943

Model-Based Single Image Deep Dehazing

Zhengguo Li·Chaobing Zheng·Haiyan Shu·Shiqian Wu
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Abstract

Model-based single image dehazing algorithms restore images with sharp edges and rich details at the expense of low PSNR values. Data-driven ones restore images with high PSNR values but with low contrast, and even some remaining haze. In this paper, a novel single image dehazing algorithm is introduced by fusing model-based and data-driven approaches. Both transmission map and atmospheric light are initialized by the model-based methods, and refined by deep learning approaches which form a neural augmentation. Haze-free images are restored by using the transmission map and atmospheric light. Experimental results indicate that the proposed algorithm can remove haze well from real-world and synthetic hazy images.

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Zhengguo Li, Chaobing Zheng, Haiyan Shu, Shiqian Wu. 2021-11-22. Model-Based Single Image Deep Dehazing. https://arxiv.org/abs/2111.10943

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