A Single Image Mosquito Streaks Removal Method of High-Speed Railway Traction Substation Using DCNN
Xuemin Lu, Danyang Zheng, Wei Quan, Yueping Liu, Shaopeng Guo, Jim X. Chen · Journal of Physics Conference Series · 2020
Abstract With the proposal of intelligent high-speed railway, the research on remotely monitoring the intelligent traction substation becomes a key subject of high-speed railway safe operation. However, mosquitos adhered to the glass window or camera lens can severely hamper the visibility of a background scene, and degrade images considerably. Therefore, we propose a single image mosquito streaks removal method of high-speed railway traction substation based on the deep convolutional neural network. First, we employ guided filter to split input image into smoothing image and edge-preserving image. Then, the edge-preserving image is fed into our designed convolutional neural network to obtain learning map, which solves problems of background interference and focuses the model on the structure of rain streak in images, and the clean image is finally generated through adding the input image and learning map. The experiment results on Heishan traction substation real datasets show the effectiveness of our proposed method.