Sept 2021
Congratulations to Dingkun Zhu, a PhD student in computer science and engineering. His paper titled “HDRD-Net: High-resolution Detail-recovering Image Deraining Network” has gained recognitions of HK IEEE Computational Intelligence Chapter. His effort made him an awardee of champion in the 18th Postgraduate Paper Competition.
The abstract of his paper:
Image deraining aims to restore the clean scenes of rainy images, which facilitates a number of smart 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 enhancing the quality of derained images. HDRD-Net consists of three sub-networks. First, we combine the residual network and Squeeze-and-Excitation block to remove rain streaks from rainy images. Second, we integrate the Structure Detail Context Aggregation block into the detail-recovering network to extract detail features from rainy images. Third, a dual super-resolution reconstruction network is utilized to improve 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 our HDRD-Net outperforms both traditional and learning-based methods in terms of rain removal, detail preservation and image quality.
