基于机载激光点云的电力线自动提取方法

为了解决地形、走向复杂、点云密度不均匀的输电线路的电力线提取精度低的问题, 提出了一种高效的电力线自动提取和重建方法。首先通过空间分割和点云密度分析方法改进高程滤波算法实现电力线粗提取; 采用基于点云间倾斜角度平均值的滤波算法精提取电力线; 使用统计滤波算法完成电力线整体点云提取; 通过基于随机采样一致性算法的电力线分条提取算法分离电力线, 最后采用直线和抛物线结合的模型完成电力线重建。结果表明, 该方法电力线总的提取精度为99.342%, 单条电力线重建精度最低为0.042m, 对地形、线路走向和点云密度等因素具有较好的鲁棒性。该研究为复杂场景下大规模输电线路的电力线提取和3维重建提供了参考。

Power line automatic extraction method based on airborne laser point cloud

In order to solve the problem of low accuracy of power line extraction of transmission lines with complex terrain and trending, and uneven point cloud density, an efficient method for automatic extraction and reconstruction of power lines was proposed. Firstly, through the space segmentation and point cloud density analysis method, the improved elevation filtering algorithm was used to achieve the rough extraction of power lines; the filtering algorithm based on the average value of the inclination angle between the point clouds was used to extract the power lines precisely; the statistical filtering algorithm was used to complete the extraction of the whole point cloud of the power lines. Then the power lines were separated by the random sample consensus(RANSAC)-based power line striping extraction algorithm, and finally the power line reconstruction was completed by using a model combining straight lines and paraboloids. The results show that the total power line extraction accuracy of this method is 99.342%, and the minimum reconstruction accuracy of a single power line is 0.042m, which is robust to terrain, line direction, point cloud density and other factors. This research provides a reference for power line extraction and 3-D reconstruction of large-scale transmission lines in complex scenarios.