2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDTEC-3.5
Paper Title DYNAMIC MULTI-DOMAIN TRANSLATION NETWORK FOR SINGLE IMAGE DERAINING
Authors Zihong Huang, Jian Zhang, Peking University, China
SessionTEC-3: Restoration and Enhancement 3
LocationArea G
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Image and Video Processing: Restoration and enhancement
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract On the single image deraining task, traditional methods are too complicated while deep learning methods lack interpretability. To solve these issues, we propose a novel deep unfolding network, which has the advantages of low complexity and high interpretability. Specifically, by transforming the rain into high-dimensional features, we propose to utilize the proximal gradient descend technique to construct an algorithm. And a new symmetry constraint is introduced to reduce the algorithm complexity effectively. Furthermore, to enhance the representation of rain features, we propose a novel dynamic multi-domain translation (DMT) module. Finally, by unrolling the algorithm, a deep unfolding network named DMTNet is established. All the parameters in DMTNet are learned end-to-end. Extensive experimental results show that the proposed DMTNet outperforms SOTA methods on several benchmark datasets.