测绘学报 ›› 2015, Vol. 44 ›› Issue (12): 1359-1366.doi: 10.11947/j.AGCS.2015.20140514

• 摄影测量学与遥感 • 上一篇    下一篇

基于可变半径圆环和B样条拟合的机载LiDAR点云滤波

郑辑涛1,2, 张涛2   

  1. 1. 清华大学计算机科学与技术系, 北京 100084;
    2. 北京航空气象研究所, 北京 100085
  • 收稿日期:2014-10-10 修回日期:2014-06-19 出版日期:2015-12-20 发布日期:2016-01-04
  • 作者简介:郑辑涛(1975-),男,博士,工程师,研究方向为数字地形建模与计算机图形学。E-mail:zhengjt8741@163.com
  • 基金资助:
    国家自然科学基金(61104082)

Filtering of Airborne LiDAR Point Cloud Based on Variable Radius Circle and B-spline Fitting

ZHENG Jitao1,2, ZHANG Tao2   

  1. 1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
    2. Beijing Aviation Meteorological Institute, Beijing 100085, China
  • Received:2014-10-10 Revised:2014-06-19 Online:2015-12-20 Published:2016-01-04
  • Supported by:
    The National Natural Science Foundation of China (No.61104082)

摘要: 提出了一种LiDAR点云滤波方法,首先沿同一方向等间距逐行扫描点云,获取点序列构成的扫描线,针对每条扫描线,采取半径可变的圆环从面向地心一侧滚过,保留扫描线上被圆周滚过的点,从而滤除每条扫描线上的地物点;然后对滤波后每条扫描线上的地表点云数据等间隔采样,在此基础上采用均匀B样条曲面拟合地形表面,遍历每一个点,在拟合的B样条曲面上投影,根据投影点高程与实际高程的差判断其属性,保留地面点并滤除地物点。试验结果表明,与传统方法相比,本文方法的滤波精度提高1~5倍,可用于城市、山区和林地等各种地形,通用性好,其算法时间复杂度为O(n)。

关键词: 滤波, 点云, 均匀B样条, 曲面拟合

Abstract: Filtering is the key to acquire digital terrain model from airborne LiDAR point cloud. In this paper, a new LiDAR point cloud filtering method is proposed. First, the scanning lines formed with point sequence are obtained throuth scanning the point cloud along the same direction. Then a circle with the variable radius rolling over the bottom of these scanning lines, the purpose is to acquire the points on the ground surface and delete the points on the objects at the same time. The next step is interval sampling from the scanning lines. On this basis, after fitting terrain surface with uniform B-spline surface, every point is projected to the fitting surface and calculate its height. According to compare the real height and its projection height to judge every point is on the terrain surface or not. The experiments show that filtering precision of the algorithm proposed in this paper is improved 1 to 5 times of the traditional methods, it can be used for the city, mountains and forest, and the time complexity of the algorithm is O(n).

Key words: filtering, point cloud, uniform B-spline, surface fitting

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