Model-Based Single Image Deep Dehazing

• URL: http://arxiv.org/abs/2111.10943v1
• Date: Mon, 22 Nov 2021 01:57:51 GMT
• Title: Model-Based Single Image Deep Dehazing
• Authors: Zhengguo Li, Chaobing Zheng, Haiyan Shu, Shiqian Wu
• Abstract summary: A novel single image dehazing algorithm is introduced by fusing model-based and data-driven approaches. Experimental results indicate that the proposed algorithm can remove haze well from real-world and synthetic hazy images.
• Score: 20.39952114471173
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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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