To extract high voltage pylons from airborne LiDAR point clouds, a pylon automatic extraction algorithm is proposed. First, the point cloud is preprocessed, and the cloth simulation filtering (CSF) algorithm is used to obtain ground points and non-ground points. Then, spatially regularized grid processing is carried out for non-ground point clouds, rough extraction is performed according to the elevation characteristics of high voltage pylons, and region of interest grids with pylons are obtained. Finally, the improved DBSCAN (density-based spatial clustering of applications with noise) algorithm is used to remove the noise points in ROI grids, and the pylon point cloud is finely extracted. The test results show that the algorithm in this paper can realize the automatic extraction of high voltage pylons from LiDAR point clouds, with a high degree of automation and a high processing efficiency.