Convolutional sparse coding and directional gradient prior based method for single image rain streak removal

Shengbiao Wang; Nina Hua; Jian Li; Yuanyuan Zheng; Pengfei Xie; Junhao Wang; Huasong Chen

doi:10.1117/12.2600416

9 October 2021 Convolutional sparse coding and directional gradient prior based method for single image rain streak removal

Shengbiao Wang, Nina Hua, Jian Li, Yuanyuan Zheng, Pengfei Xie, Junhao Wang, Huasong Chen

Author Affiliations +

Proceedings Volume 11897, Optoelectronic Imaging and Multimedia Technology VIII; 118970L (2021) https://doi.org/10.1117/12.2600416
Event: SPIE/COS Photonics Asia, 2021, Nantong, JS, China

Abstract

In this paper, we address the rain streak removal from a single image. In order to efficiently detect and remove the annoying rain streaks, we propose a global single-directional gradient prior with the L0 norm to model the rain streak. To preserve the abundant information of the background, we learn a convolutional sparse coding (CSC) to represent the background. Furthermore, we develop an alternating direction method of multipliers (ADMM) to solve multi-variable optimization problems. Experiments on synthesized and real-world images show that the proposed method outperforms state-of-art methods in terms of rain streak removal and background preservation.

Citation Download Citation

Shengbiao Wang, Nina Hua, Jian Li, Yuanyuan Zheng, Pengfei Xie, Junhao Wang, and Huasong Chen "Convolutional sparse coding and directional gradient prior based method for single image rain streak removal", Proc. SPIE 11897, Optoelectronic Imaging and Multimedia Technology VIII, 118970L (9 October 2021); https://doi.org/10.1117/12.2600416

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