论文部分内容阅读
LIDAR即激光雷达,是一种集激光,全球定位系统(GPS)和惯性导航系统(INS)三种技术与一身的系统,具有快速获取目标三维信息的能力,可用于精确DEM的生产。LIDAR数据是分布于物体表面的点云,具有离散、不均匀分布、数据类型多等特点。为了利用LIDAR数据生产DEM,就必须首先提取地面点信息,即对原始点云进行滤波处理。LIDAR点云滤波处理实质就是滤除非地面点,保留地面点。为了区分点云中的地面点和非地面点,必须设定点云的判别准则,即设计滤波算法。现有的滤波算法有很多种,它们从各自不同的角度来进行LIDAR点云滤波或者直接生成DEM,但是这些算法都有其局限性和缺点,从LIDAR数据中将地面点和非地面点有效分离仍然是一项挑战性的工作。
LIDAR is a laser radar, a global positioning system (GPS) and inertial navigation system (INS) three technologies and a system that has the ability to quickly get the target three-dimensional information, can be used for accurate DEM production. LIDAR data is distributed on the surface of the object point cloud, with discrete, uneven distribution, data types and more. In order to use DIDAR data to produce DEM, we must first extract the ground point information, that is, the original point cloud filtering. LIDAR point cloud filtering is essentially filtering non-ground point, keep the ground point. In order to distinguish between the ground point and the non-ground point in the point cloud, the criteria for determining the point cloud must be set, that is, the filter algorithm is designed. There are many existing filtering algorithms, which perform LIDAR point cloud filtering or generate DEM directly from different perspectives. However, these algorithms all have their limitations and shortcomings. Effectively separating the ground point and the non-ground point from the LIDAR data Still a challenging job.