一种基于分层自适应移动曲面拟合机载LiDAR点云数据滤波方法

为提高机载Li DAR数据滤波精度,提出了一种分层自适应移动曲面拟合法滤波。通过改进均值限差法,对原数据进行"粗滤波";之后以Mean Shift算法进行数据分类,建立虚拟格网索引结构,通过二次多项式进行曲面拟合,以自适应阈值进行"精滤波"。实验结果表明:该方法的适应性强,滤波结果具有较高的准确性。

A Algorithm Based on Hierarchical Adaptive Moving Curved Surface and Fitting for LiDAR Point Clouds Date

To improve the accuracy of the filtering of airborne LiDAR, a filtering with hierarchical and adaptive by moving curved sur-face fitting is proposed.As“coarse filtering” the improved average-tolerance method is used to processes data.In the paper, virtual grid is established and the original data classification based on Mean Shift.What’s more, as“precision filtering”, the ground points and unground points are classified by quadratic polynomial surface fitting and adaptive threshold.The experiment results show that the method has well-adapted and it has high accurate filtering result.