一种基于移动最小二乘的LiDAR点云加密算法

A LiDAR Point Cloud Encryption Algorithm Based on Mobile Least Squares

在机载激光雷达点云的生产过程中,由于地形、飞行等因素的影响,会产生点云数据密度较低的现象,而重新采集点云数据不仅会增加生产成本,也很难满足时间要求。利用加密算法,在保证精度的情况下,内业实现点云密度增加,是一种经济且快速的增加点云密度手段。本文基于移动最小二乘原理进行采样计算,实现了点云数据量和密度的增大。实验证明,处理结果很好地保持了地形、地物完整性,加密后建筑物的屋脊、角点等细节的展现更加清晰完整,点云的可视化效果更佳。针对加密成果,本文采用三种精度评价方式验证了算法的可行性和有效性。

In the production process of airborne lidar point cloud,due to the influence of terrain,flight and other factors,the data density of point cloud is relatively low,and the re-collection of point cloud data will not only increase the production cost,but also hardly meet the time requirements. It is an economical and fast method to increase the point cloud density by using encryption algorithm with guaranteed precision. In this paper,based on the principle of moving least squares,the data volume and density of point cloud are increased. The experiment proves that the processing results can well maintain the integrity of topography and ground objects. After encryption,the details such as roof ridges and corner points of buildings can be displayed more clearly and completely,and the visualization effect of point cloud is better. Three precision evaluation methods are used to verify the feasibility and effectiveness of the algorithm.