一种改进的基于平面拟合的机载LiDAR点云滤波方法

doi:10.11873/j.issn.1004-0323.2011.1.117

遥感技术与应用

2011, Vol. 26

Issue (1): 117-122 DOI: 10.11873/j.issn.1004-0323.2011.1.117

图像处理

一种改进的基于平面拟合的机载LiDAR点云滤波方法

陈磊,赵书河

(南京大学地理与海洋科学学院,江苏南京210093)

An Improved Plane Fitting based Filtering Algorithm for Airborne LiDAR Data

CHEN Lei,ZHAO Shu-he

(School of Geographic & Oceanographic Sciences,Nanjing University,Nanjing 210093,China)

全文: PDF(3914 KB)

摘要：

在分析现有方法优劣的基础上,提出一种改进的基于平面拟合的机载LiDAR点云滤波方法。首先基于区域生长算法对重采样的LiDAR数据图像分割,提取最大连通区域为初始地面,然后基于坡度阈值剔除初始地面内的地物点,最后对筛选后的地面点克里金插值实现滤波。采用国际摄影测量与遥感学会(ISPRS)提供的测试数据进行实验,研究了设置不同坡度阈值对滤波结果产生的影响。结果表明,坡度阈值取0.5时滤波效果最优,整体错误率仅为4.29%。与传统的基于平面拟合的滤波方法相比较,该方法更简单实用。

关键词： LiDAR; 平面拟合; 滤波; 区域生长

Abstract:

Due to the strengths and weaknesses of the existing filtering methods,an improved plane fitting algorithm is presented for filtering of airborne LiDAR data.Firstly,resampled LiDAR data were segmented using region growing method,and then the largest connected region was selected as the initial ground area.Secondly,non\|ground points in the initial ground area were removed by a slope threshold.Finally,the ground points were interpolated using Kriging method and the filtering results were gained.The dataset provided by International Society for Photogrammetry and Remote Sensing (ISPRS) were selected as the test data.The influences of different slope thresholds on the filtering results were given after filtering experiments.The result shows that the optimal filtering effect is the best when the slope threshold sets to 0.5.The overall error rate can be only 4.29%.Contrast to the traditional filtering method based on plane fitting,the proposed method is more simple and practical.

Key words: LiDAR Plane fitting Filtering Region growing

收稿日期: 2010-07-20 出版日期: 2011-05-05

TN958.98

基金资助:

现代工程测量国家测绘局重点实验室开发基金资助项目(TJES1005)和国家自然科学基金项目(40501047)联合资助。

作者简介: 陈磊(1985-)，男,江苏盐城人,硕士研究生,主要从事激光雷达数据处理研究。Email：tq0fxzz@163.com。

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引用本文:

陈磊,赵书河. 一种改进的基于平面拟合的机载LiDAR点云滤波方法[J]. 遥感技术与应用, 2011, 26(1): 117-122.

CHEN Lei,ZHAO Shu-he. An Improved Plane Fitting based Filtering Algorithm for Airborne LiDAR Data. Remote Sensing Technology and Application, 2011, 26(1): 117-122.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2011.1.117 或 http://www.rsta.ac.cn/CN/Y2011/V26/I1/117

［1］Zhang Xiaohong.Theory and Methods of Airborne LiDAR M\|easurement Technology［M］.Wuhan:Wuhan University Press,2007:93-96.［张小红.机载激光雷达测量技术理论与方法［M］.武汉:武汉大学出版社,2007:93-96.］

［2］Sithole G,Vosselman G.Experimental Comparison of Filter Algorithms for Bare Earth Extraction from Airborne Laser Scanning Point Clouds［J］.ISPRS Journal of Photogrammetry and Remote Sensing,2004,59(1-2):85-101.

［3］Vosselman G.Slope based Filtering of Laser Altimetry Data［J］.International Archives of Photogrammetry and Remote Sensing,2000,33:935-942.

［4］Rogero M.Airborne Laser Scanning:Clustering in Raw Data［J］.International Archives of Photogrammetry and Remote Sensing,2001,34:227-232.

［5］Zhang Hao,Jia Xinmei,Zhang Yongsheng,et al.Filtering of Airborne LiDAR Data based on Pseudo\|grid Concept and Modified Slope Filtering Algorithm［J］.Journal of Geomatics Science and Technology,2009,26(3):224-227.［张皓,贾新梅,张永生,等.基于虚拟网格与改进坡度滤波算法的机载LIDAR数据滤波［J］.测绘科学技术学报,2009,26(3):224-227.］

［6］Killian J,Haala N,Englich M.Capture and Evaluation of Airborne Laser Scanner Data［J］.International Archives of Photogrammetry and Remote Sensing,1996,31:385-388.

［7］Zhang K Q,Chen S C,Whitman D,et al.A Progressive Morphological Filter for Removing Non\|ground Measurement from LiDAR Data［J］.IEEE Transactions on Geoscience and Remote Sensing,2003,41(4):872-882.

［8］Tao Jinhua,Su Lin,Li Shukai.A Detailed Protected Method of Extracting Digital Terrain Model from Airborne Laser Point Cloud in Urban Areas［J］.Journal of Remote Sensing,2008,12(2):233-238.［陶金花,苏林,李树楷.一种保护细节的从机载激光点云中提取城区DTM的方法［J］.遥感学报,2008,12(2):233-238.］

［9］Liang Xinlian,Zhang Jixian,Li Haitao.An Adaptive Morphological Filter for LiDAR Data Filtering in Urban Area［J］.Journal of Remote Sensing,2007,11(2):276-281.［梁欣廉,张继贤,李海涛.一种应用于城市区域的自适应形态学滤波方法［J］.遥感学报,2007,11(2):276-281.］

［10］Huang Xianfeng,Li Hui,Wang Xiao,et al.Filter Algorithms of Airborne LiDAR Data:Review and Prospects［J］.Acta Geodaetica et Cartographica Sinica,2009,38(5):466-469.［黄先锋,李卉,王潇,等.机载LiDAR数据滤波方法评述［J］.测绘学报,2009,38(5):466-469.］

［11］Brovelli M A,Cannata M,Longoni U M.Managing and Processing LiDAR Data within GRASS［C］//Proceedings of the Open Source GIS\|GRASS Users Conference,Trento,2002.

［12］Cheng Xiaoqian,Zhao Hongqiang.LiDAR Point Cloud Data Filtering based on Regional Growing［J］.Remote Sensing for Land & Resources,2008,78(4):6-8.［成晓倩,赵红强.基于区域生长的LIDAR点云数据滤波［J］.国土资源遥感,2008,78(4):6-8.］

［13］Yuan Feng,Gao Jingxiang,Zhang Jixian,et al.A Method of Extracting DEM from LiDAR Data in Urban Areas［J］.Bulletin of Surveying and Mapping,2010,2:26-28.［袁枫,高井祥,张继贤,等.一种从城区LiDAR数据提取DEM的方法［J］.测绘通报,2010,2:26-28.］

［14］Gonzalez R C,Woods R E,Eddins S L.Digital Image Processing Using MATLAB ［M］.Beijing:Publishing House of Electronics Industry,2005.［Gonzalez R C.数字图像处理［M］.北京:电子工业出版社,2005.］

［15］http://www.itc.nl/isprswgIII\|3/filtertest/index.html ［Z］.ISPRS Commission Ⅲ.2010,7.

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