基于区域生长的LIDAR点云数据滤波

LIDAR POINT CLOUD DATA FILTERING BASED ON REGIONAL GROWING

将区域生长算法引入LIDAR点云滤波,其原理与图像处理中的区域生长原理相似。首先选择可靠的种子点,当待定点与种子点的高差满足所设阈值时,则待定点为地面点,否则作为地物点滤去。当不再有激光点满足条件时,生长结束。该算法无需对原始数据进行插值,无需迭代,因此滤波速度快。与传统的最大局部倾斜度过滤算法(MLS)和扩大窗口高程阈值滤波方法相比,该算法的实验结果更优。

A new filtering algorithm named regional growing filer is proposed in this paper. The principle of the regional growing filer is similar to the regional growing used to process digital images. First, reliable seeds are selected, then the growing rule is formulated. If the height difference between the seeds and the selected points is lower than the threshold, the selected point is regarded as the ground point, otherwise the point is removed as a feature point. When there are no laser points that can meet the rule, the growing ends. The processed point clouds use regional growing filter with no need of original data interpolation and iteration, and hence the filtering speed is fast. Experiments show that the effects of the regional growing filer is better than the results of such traditional algorithms as the maximum local slope filer and the expansion of window height threshold filer.