基于分水岭算法与同质区合并的机载LiDAR点云数据分割方法OA

In response to the problems of excessive image overlap and low segmentation accuracy in the point cloud data seg-mentation process of airborne light detection and ranging(LiDAR)in real estate measurement,this paper adopted a method based on the watershed algorithm and homogeneous region merging to carry out the design and research of an airborne LiDAR point cloud data segmentation method.It improved the quality of point cloud data through preprocessing steps such as denoising,filtering,and normalization.Subsequently,the watershed algorithm was used to partition the image feature regions,and a homogeneous region merging algorithm was designed based on the merging criterion to optimize the segmenta-tion effect of point cloud data.The experimental results show that this method can not only effectively optimize the vertical segmentation of LiDAR point cloud data density and the horizontal segmentation of surface feature images but also signifi-cantly control the overlap of segmented images,improving segmentation accuracy and efficiency.The point cloud data seg-mentation method based on the watershed algorithm and homogeneous region merging proposed in this paper provides an effi-cient and accurate solution for real estate measurement.