Deep residual skip connection neural network for single image deraining

Shiyan Qian; Huiping Li; Shuqin Xia; Jingxian Chang; Huasong Chen; Qiansheng Feng; Junhao Wang

doi:10.1117/12.3036181

22 November 2024 Deep residual skip connection neural network for single image deraining

Shiyan Qian, Huiping Li, Shuqin Xia, Jingxian Chang, Huasong Chen, Qiansheng Feng, Junhao Wang

Author Affiliations +

Proceedings Volume 13239, Optoelectronic Imaging and Multimedia Technology XI; 1323914 (2024) https://doi.org/10.1117/12.3036181
Event: SPIE/COS Photonics Asia, 2024, Nantong, Jiangsu, China

Abstract

Recently, deep neural networks have been successfully applied for removing rain streaks from images. However, these methods did not consider the relationships between the skip layers. In order to improve the deraining performance and use the information of different layers, we propose to construct connections between different layers and propose a residual skip connection neural network for single image deraining. Then we train the network on synthesized data. Both experiments on synthesized and real-world images show the proposed method outperforms state-of-the-art methods in terms of rain streak removal and image information preservation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shiyan Qian, Huiping Li, Shuqin Xia, Jingxian Chang, Huasong Chen, Qiansheng Feng, and Junhao Wang "Deep residual skip connection neural network for single image deraining", Proc. SPIE 13239, Optoelectronic Imaging and Multimedia Technology XI, 1323914 (22 November 2024); https://doi.org/10.1117/12.3036181

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