We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
HDRD-Net: High-resolution detail-recovering image deraining network.
- Authors
Zhu, Dingkun; Deng, Sen; Wang, Weiming; Cheng, Gary; Wei, Mingqiang; Wang, Fu Lee; Xie, Haoran
- Abstract
Image deraining aims to restore the clean scenes of rainy images, which facilitates a number of outdoor vision systems, such as autonomous driving, unmanned aerial vehicles and surveillance systems. This paper proposes a high-resolution detail-recovering image deraining network (HDRD-Net) to effectively remove rain streaks and recover lost details, as well as improving the quality of derained images. HDRD-Net consists of three sub-networks. First, we combine the residual network and Squeeze-and-Excitation block for rain streak removal. Second, we integrate the Structure Detail Context Aggregation block into the detail-recovering network to extract detail features form rainy images. Third, a dual super-resolution reconstruction network is utilized to enhance the quality of derained images. In addition, we extend the Rain100 dataset by incorporating low-resolution rainy images to construct a new Rain100++ dataset for high-resolution image deraining. Experimental results on several datasets show that HDRD-Net outperforms state-of-the-art methods in terms of rain removal, detail preservation and visual quality.
- Subjects
AERIAL surveillance; AUTONOMOUS vehicles; RADARSAT satellites
- Publication
Multimedia Tools & Applications, 2022, Vol 81, Issue 29, p42889
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-022-13489-5