Towards a Unified Approach to Single Image Deraining and Dehazing

• URL: http://arxiv.org/abs/2103.14204v1
• Date: Fri, 26 Mar 2021 01:35:43 GMT
• Title: Towards a Unified Approach to Single Image Deraining and Dehazing
• Authors: Xiaohong Liu, Yongrui Ma, Zhihao Shi, Linhui Dai, Jun Chen
• Abstract summary: We develop a new physical model for the rain effect and show that the well-known atmosphere scattering model (ASM) for the haze effect naturally emerges as its homogeneous continuous limit. We also propose a Densely Scale-Connected Attentive Network (DSCAN) that is suitable for both deraining and dehazing tasks.
• Score: 16.383099109400156
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We develop a new physical model for the rain effect and show that the well-known atmosphere scattering model (ASM) for the haze effect naturally emerges as its homogeneous continuous limit. Via depth-aware fusion of multi-layer rain streaks according to the camera imaging mechanism, the new model can better capture the sophisticated non-deterministic degradation patterns commonly seen in real rainy images. We also propose a Densely Scale-Connected Attentive Network (DSCAN) that is suitable for both deraining and dehazing tasks. Our design alleviates the bottleneck issue existent in conventional multi-scale networks and enables more effective information exchange and aggregation. Extensive experimental results demonstrate that the proposed DSCAN is able to deliver superior derained/dehazed results on both synthetic and real images as compared to the state-of-the-art. Moreover, it is shown that for our DSCAN, the synthetic dataset built using the new physical model yields better generalization performance on real images in comparison with the existing datasets based on over-simplified models.

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