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A Survey on Rain Removal from Video and Single Image

Hong Wang, Yichen Wu, Minghan Li, Qian Zhao, and Deyu Meng

[Arxiv]

Citation

@article{wang2022survey,
  title={Survey on rain removal from videos or a single image},
  author={Wang, Hong and Wu, Yichen and Li, Minghan and Zhao, Qian and Meng, Deyu},
  journal={Science China Information Sciences},
  volume={65},
  number={1},
  pages={1--23},
  year={2022},
  publisher={Springer}
}

@article{WangA,
  title={A Survey on Rain Removal from Video and Single Image}, 
  author={Wang, Hong and Wu, Yichen and Li, Minghan and Zhao, Qian and Meng, Deyu}, 
  journal={arXiv preprint arXiv:1909.08326},
  year={2019}
}

Physical Properties of Raindrops

Video Deraining Methods

Single Image Deraining Methods

Datasets and Discriptions

*We note that:

i. RainTrainL/Rain100L and RainTrainH/Rain100H are synthesized by Yang Wenhan. Rain12600/Rain1400 is from Fu Xueyang and Rain12 is from Li Yu.

ii. In video experiment, the rain-removed results of the deep learning method are provided by the author Yang Wenhan. Really thanks!

iii. In single image experiment, we seperately retrain all the recent state-of-the-art methods via the three training datasets: RainTrainL(200 input/clean image pairs), RainTrainH(1800 pairs), and Rain12600(12600 pairs), and then evaluate their rain removal performance based on the correponding test datasets: Rain100L(100 pairs), Rain100H(100 pairs), and Rain1400(1400 pairs). Besides, the trained model obtained by RainTrainL is adpoted to predict rain-removed results of Rain12(12 pairs). Moreover, we utilize the Internet-Data(147 input images) and SPA-Data(1000 pairs) to compare the generalization ability.

iiii. In single image experiment, when training the semi-supervised method--SIRR, we always utilize Internet-Data as unsupervised samples.

Image Quality Metrics

*Please note that all quantitative results in our survey paper are computed based on Y channel.

Contact

If you have any question, please feel free to concat Hong Wang (Email: hongwang01@stu.xjtu.edu.cn).