多级移动曲面拟合的自适应阈值点云滤波方法

朱笑笑; 王成; 习晓环; 王濮; 田新光; 杨学博

doi:10.11947/j.AGCS.2018.20170491

测绘学报 >

2018 , Vol. 47 >Issue 2: 153 - 160

DOI: https://doi.org/10.11947/j.AGCS.2018.20170491

多级移动曲面拟合的自适应阈值点云滤波方法

朱笑笑 ,
王成 ,
习晓环 ,
王濮 ,
田新光 ,
杨学博

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1. 中国科学院遥感与数字地球研究所中科院数字地球重点实验室, 北京 100049;
2. 中国科学院大学资源与环境学院, 北京 100049;
3. 太原市建筑设计勘测中心, 山西太原 030000

朱笑笑(1993-),女,硕士生,研究方向为激光雷达遥感。E-mail:zhuxx@radi.ac.cn

收稿日期: 2017-09-01

修回日期: 2017-12-20

网络出版日期: 2018-03-02

基金资助

国家自然科学基金面上项目（41671434；41371350）

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Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

ZHU Xiaoxiao ,
WANG Cheng ,
XI Xiaohuan ,
WANG Pu ,
TIAN Xinguang ,
YANG Xuebo

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1. Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing 100049, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Taiyuan Architectural Design Service Office, Taiyuan 030000, China

Received date: 2017-09-01

Revised date: 2017-12-20

Online published: 2018-03-02

Supported by

The General Program of National Natural Science Foundation of China (Nos. 41671434;41371350)

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摘要

为了提高机载激光雷达点云滤波算法的精度、效率以及自适应性，提出了一种多级移动曲面拟合的自适应阈值点云滤波方法。首先，对点云数据进行预处理即剔除粗差，然后通过格网化分割建立格网索引，利用每个格网的邻域格网中的最低点建立曲面方程，计算真实高程与拟合高程的差值并设置自适应性阈值进行滤波，最后采用多级滤波策略，即逐级改变格网大小并自动设置邻域和阈值，直到滤波结果达到精度要求。使用国际摄影测量与遥感学会（ISPRS）提供的测试数据对算法进行验证，第1、2类误差和总误差平均值分别为7.33%、10.64%、6.34%。将该算法与ISPRS公布的8大经典滤波算法进行比较，结果表明该方法的适应性强，滤波结果具有较高的准确性。

关键词： 点云数据; 格网化; 移动曲面; 邻域大小; 多级滤波; 曲面拟合

本文引用格式

朱笑笑 , 王成 , 习晓环 , 王濮 , 田新光 , 杨学博 . 多级移动曲面拟合的自适应阈值点云滤波方法[J]. 测绘学报, 2018 , 47(2) : 153 -160 . DOI: 10.11947/j.AGCS.2018.20170491

Abstract

In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS) is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

Key words： point cloud data; gridding; moving curve surface; neighborhood window; hierarchical filtering; surface fitting

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