摘要
为了提高传统的不规则三角网(triangular irregular network,TIN)中初始种子点的选取效率问题,文章提出一种布料模拟滤波(cloth simulation filtering,CSF)与TIN结合的机载激光雷达(light detection and ranging,LiDAR)点云滤波算法。首先去除机载LiDAR点云中的粗差点,对去除粗差点后的点云使用CSF算法以获取初始地面点,然后对初始地面点通过改进的TIN算法构建三角网,同时连续迭代进而获取最终地面点。实验选取国际摄影测量与遥感学会网站的3组测试数据进行滤波,结果表明该算法能够在坡度较大的区域降低Ⅰ类误差,并将Ⅱ类误差控制在一定范围内,验证了该算法的可靠性。
In order to improve the selection efficiency of the initial seed points in the traditional triangular irregular network(TIN)algorithm,this paper proposes an airborne light detection and ranging(LiDAR)point cloud filtering algorithm combining the cloth simulation filtering(CSF)algorithm with the TIN.First,the gross errors in the airborne LiDAR point cloud are removed.Then,the CSF algorithm is applied to the point cloud after removing gross errors to get the initial points on the ground.Finally,the triangular mesh of initial ground points is built through the improved TIN algorithm,and the final ground point is gotten through the continuous iteration.Three groups of test data from the International Society for Photogrammetry and Remote Sensing(ISPRS)are chosen for filtering,and the results show that the proposed algorithm can reduce classⅠerror in the region with steeper slopes,and control classⅡerror within a certain range,which verify the reliability of the algorithm.
作者
崔浩
高飞
余敏
叶周润
CUI Hao;GAO Fei;YU Min;YE Zhourun(School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, China)
出处
《合肥工业大学学报（自然科学版）》
CAS
北大核心
2022年第5期644-648,共5页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金青年科学基金资助项目(41904010)
安徽省自然科学基金资助项目(2008085MD115)。
