| Citation: | CHAI Guoqiang, WANG Dawei, LU Bin, et al. Lightweight densely connected network based on attention mechanism for single-image deraining[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2186-2192. doi: 10.13700/j.bh.1001-5965.2021.0294(in Chinese)
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The rain streaks attached to the image seriously affect the analysis and follow-up research of the image information. To restore the background texture damaged by rain streaks, this paper proposes a lightweight densely connected network based on attention mechanism to remove rain from a single image. The attention mechanism makes the network locate in the rain streaks area accurately, and the densely connected network enhances the feature reuse, alleviates the gradient disappearance and model degradation problems. The utilization of multi-scale mix channel depthwise separable convolutions realizes lightweight design by reducing the scale of network parameters and enhancing the efficiency of network operation. Both qualitative and quantitative validations on synthetic and real-world datasets demonstrate that the proposed approach can achieve competitive performance in comparison with the state-of-the-art methods.
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