针对二维格网形态学的插值误差及二维原始点云形态学的耗时等问题, 提出一种基于扫描线的一维渐进式形态学 LiDAR点云滤波方法。该方法根据点云数据近似直线扫描和顺序存储的特点, 将一维渐进式形态学方法运用于 LiDAR原始点云, 分析运算后的点值与其原始值的差异, 逐步滤除非地面点。为验证算法的有效性, 采用 ISPRS测试数据进行实验, 结果表明, 该算法无论是在城市地区还是在郊区均能有效滤除非地面点, 且具有较高的可靠性。

Ground filtering algorithms operate currently on either raw LiDAR point clouds or values that are derived by interpolation of raw data. In order to overcome interpolation error of grid elevation and time-consuming problem of raw LiDAR data, a new method of filtering based on 1-D progressive morphological method is proposed. This method can detect LiDAR non-ground objects from point cloud data by gradually increasing the size of the 1-D filter and using different elevation thresholds. Finally, we conducted a comprehensive test of the performance on fifteen study sites and compared our results to eight other publicized methods reported by ISPRS. The result shows that the filter can remove most of the non-ground points effectively. Overall, the 1-D progressive morphological filtering algorithm produces a promising performance in both urban and forest areas.