机载激光扫描点云的三维数字图像表达模型将二维形态学运算推广至三维,给出基于三维数字图像的膨胀和腐蚀运算方法。针对点云三维数字图像,提出基于三维数学形态学和聚类分析的分割方法。将点云三维数字图像进行膨胀和聚类分析,依据聚类结果得到点云的分割结果。讨论了本方法两个参数与点云分辨率、地物间隔之间的关系。选用两套实例数据进行实验,并将第一套数据计算结果与Mean Shift算法、渐进三角网加密算法进行比较,从分割评价因子、精度、计算效率等方面分析本文方法与其他两种方法的优劣,最后分析了本文方法的稳定性。

A 3D digital image model is proposed to represent the LIDAR data. The mathematical morphology is extended to 3D and then, dilation and erosion operators are re-defi ned. A method combining 3D mathematical morphology with clustering analysis is developed . Sequential dilation operations and clustering analysis are introduced into the 3D point cloud to achieve the pixel- level results of point cloud. The relationships between the two parameters and data property, resolution of point cloud and the minimum distance between objects, is discussed. Two case data are used to demonstrate the feasibility of the proposed method. The result for the fi rst dataset is compared with those from the two other methods, Mean Shift algorithm and adaptive TIN fi lter method. The advantages and disadvantages are summarized using segmentation evaluation factors, segmentation accuracy, and computation effi ciency. Meanwhile the stabilization of proposed method is also analyzed.