Single Image Rain Removal Method by Fusing Residual and Channel Attention Mechanism
ZHANG Shi-hui1,2,YAN Xiao-rui1,SANG Yu1
1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao, Hebei 066004, China
Abstract：In order to remove the raindrops and restore the image sharpness,a single image rain removal method based on depth learning and image enhancement technology combined with residual and channel attention mechanism is proposed.Firstly, the rainy image is decomposed into the smooth base layer and the high-frequency detail layer by using the guided filter. Secondly,an adaptive gamma correction algorithm is proposed to enhance the smooth base layer to improve contrast. Thirdly, the deep neural network with residual block and the channel attention mechanism is constructed to remove rain in the high-frequency detail layer. Finally, the high-frequency detail layer after rain removal is combined with the enhanced smooth base layer to realize the single image rain removal. The experimental results show that compared with the representative single image rain removal method, the proposed method works well and can retain more image detail information.
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2021, Vol. 42 
