LiDAR Point Cloud Area Growth Filtering Algorithm under Moving Windows
Among the LiDAR filtering methods,the least square interpolation method can obtain the better trend surface of the terrain,but the algorithm cannot set parameters adaptively according to the terrain,the accuracy of the extraction results is low in areas with large terrain undulations and large buildings and vegetation with low penetration cannot be eliminated. There may be problems such as accepted gross error points and long calculation time and it is difficult to obtain higher accuracy using the least square interpolation fil-tering method. Therefore,this paper proposes an area growth filtering based on moving window weighted iterative least square fitting,namely using area growth filtering under moving windows to filter LiDAR data.
LiDAR point cloudsmoving windowsfiltering algorithms
NETL
NSTL
万方数据
