Lidar点云数据中建筑物的快速提取

Lidar技术可快速获取地表的高精度三维点云数据, 目前对此类数据的分类却是速度慢、精度低, 尤其是城市区域建筑物和树木靠得较近时更是难以准确提取建筑物.介绍了一种基于点云数据生成距离影像, 而后引入对比度纹理辅助的点云数据建筑物快速提取方法.结果证明, 该方法不需要其他辅助数据就能实现点云数据中建筑物的快速提取. 

Extract Buildings Quickly from Lidar Point Cloud Data

Lidar can capture 3D geographical information quickly,and form a massive discrete point cloud.There are some shortcomings in the existing classification algorithms,such as low precision of classification and slow processing speed, especially in processing buildings close to trees. In this article, a new building extraction algorithm is introduced. The range image is abstracted from the original data and then the height texture is used for assisting classification. The authors tested the algorithm with Lidar data. The result of the experiment shows that this algorithm can distinguish adjacent buildings and trees. Also, the algorithm is good at classification precision and high speed. It has obvious advantages in the urban Lidar points cloud classification.