架空输电线路可视化监拍图像联合去雨雾算法研究

Study of Combined Rain and Fog Removal Algorithm for Visual Monitoring Images of Overhead Power Lines

远程视频监控巡视架空线路可以减少人工巡线工作量,提升巡视效率,当前架空输电线路通道环境恶劣,气候多变,雨雾天气采集的场景图像质量,对巡线辨别产生不利影响,为此提出了一种架空输电线路可视化监拍图像联合去雨雾算法,该算法通过建立镜头雨滴模型、图像雨痕模型和雾化模型,利用深度神经网络训练去雨滴、去雨痕和去雾化模型,联合三种模型实现图像去雨雾,试验检测证实,该方法在输电通道环境下具有较好的去雨雾效果。

Remote video monitoring inspection of overhead lines can reduce the workload of manual inspection and improve the inspection efficiency.At present,the channel environment of overhead transmission lines is bad,the climate is changeable,and the image quality of rain and fog weather collection scene has adverse effects on the identification of inspection lines.Through the establishment of the lens raindrop model,image raintrace model and atomization model,the algorithm uses the depth neural network to train the raindrop removal model,raintrace removal model and atomization removal model,and combines the three models to realize image rain fog removal.The experimental results show that the method has good rain fog removal effect in the transmission channel environment.