Direction-aware Feature-level Frequency Decomposition for Single Image Deraining

Sen DENG, Yidan FENG, Mingqiang WEI*, Haoran XIE*, Yiping CHEN, Jonathan LI, Xiao-ping ZHANG, Jing QIN

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)


We present a novel direction-aware feature-level frequency decomposition network for single image deraining. Compared with existing solutions, the proposed network has three compelling characteristics. First, unlike previous algorithms, we propose to perform frequency decomposition at feature-level instead of image-level, allowing both low-frequency maps containing structures and high-frequency maps containing details to be continuously refined during the training procedure. Second, we further establish communication channels between low-frequency maps and high-frequency maps to interactively capture structures from high-frequency maps and add them back to low-frequency maps and, simultaneously, extract details from low-frequency maps and send them back to high-frequency maps, thereby removing rain streaks while preserving more delicate features in the input image. Third, different from existing algorithms using convolutional filters consistent in all directions, we propose a direction-aware filter to capture the direction of rain streaks in order to more effectively and thoroughly purge the input images of rain streaks. We extensively evaluate the proposed approach in three representative datasets and experimental results corroborate our approach consistently outperforms state-of-the-art deraining algorithms.
Original languageEnglish
Title of host publicationProceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21)
EditorsZhi-Hua ZHOU
PublisherInternational Joint Conferences on Artificial Intelligence
Number of pages7
ISBN (Electronic)9780999241196
Publication statusPublished - Aug 2021
Event30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Montreal, Virtual, Online, Canada
Duration: 19 Aug 202127 Aug 2021

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823


Conference30th International Joint Conference on Artificial Intelligence, IJCAI 2021
CityVirtual, Online

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China (Nos. 62032011, 61502137).

Publisher Copyright:
© 2021 International Joint Conferences on Artificial Intelligence. All rights reserved.


Dive into the research topics of 'Direction-aware Feature-level Frequency Decomposition for Single Image Deraining'. Together they form a unique fingerprint.

Cite this