Generative Adversarial Network for Image Raindrop Removal of Transmission Line Based on Unmanned Aerial Vehicle Inspection

摘要

In the process of UAV line inspection, there may be raindrops on the camera lens. Raindrops have a serious impact on the details of the image, reducing the identification of the target transmission equipment in the image, reducing the accuracy of the target detection algorithm, and hindering the practicability of UAV line inspection technology in cyber-physical energy systems. In this paper, the principle of raindrop image formation is studied, and a method of raindrop removal based on generation countermeasure network is proposed. In this method, the attention recurrent network is used to generate the raindrop attention map, and the context code decoder is used to generate the raindrop image. The experimental results show that the proposed method can remove the raindrops in the image and repair the background image of raindrop coverage area and can generate a higher quality raindrop removal image than the traditional method.