Residual Squeeze-and-Excitation Network for Fast Image Deraining
- URL: http://arxiv.org/abs/2006.00757v1
- Date: Mon, 1 Jun 2020 07:17:01 GMT
- Title: Residual Squeeze-and-Excitation Network for Fast Image Deraining
- Authors: Jun Fu and Jianfeng Xu and Kazuyuki Tasaka and Zhibo Chen
- Abstract summary: We propose a residual squeeze-and-excitation network called RSEN for fast image deraining.
RSEN adopts a lightweight encoder-decoder architecture to conduct rain removal in one stage.
- Score: 19.48155134126906
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Image deraining is an important image processing task as rain streaks not
only severely degrade the visual quality of images but also significantly
affect the performance of high-level vision tasks. Traditional methods
progressively remove rain streaks via different recurrent neural networks.
However, these methods fail to yield plausible rain-free images in an efficient
manner. In this paper, we propose a residual squeeze-and-excitation network
called RSEN for fast image deraining as well as superior deraining performance
compared with state-of-the-art approaches. Specifically, RSEN adopts a
lightweight encoder-decoder architecture to conduct rain removal in one stage.
Besides, both encoder and decoder adopt a novel residual squeeze-and-excitation
block as the core of feature extraction, which contains a residual block for
producing hierarchical features, followed by a squeeze-and-excitation block for
channel-wisely enhancing the resulted hierarchical features. Experimental
results demonstrate that our method can not only considerably reduce the
computational complexity but also significantly improve the deraining
performance compared with state-of-the-art methods.
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