Under rainy conditions,the video monitoring image contains raindrops,which blurs the detailed information of the monitoring target of the power substation equipment,and affects the performance of video monitoring.Aimed at the problem of image degradation caused by raindrops,a multi-scale model architecture is proposed based on deep neural networks to remove rain patterns in images.Using the prior information,the guided filtering is used to extract the fuzzy feature maps of raindrops that characterize the high-frequency components of the image,which renders the model focuses on the raindrop information.Learning from the multi-branch extraction structure of the multi-level feature of Inception network,a multi-scale deep neural network is built to fuse the bottom and high-level features.On the synthetic power substation equipment and real-world rainy day image sets,the method proposed has been experimentally verified.The experimental results show that the method has bet-ter rain removal effect than other methods.
关键词
多尺度深层网络/监控图像/去雨算法/变电站/质量检测
Key words
multi-scale deep network/monitoring image/rain removal method/power substation/quality detection
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