|
|
A Thinning Algorithm of LiDAR Point Cloud Data in Urban Area |
Peiqi Chen(),Xudong Lai(),Yongxu Li |
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China |
|
|
Abstract When the density of LiDAR point cloud data in urban area is high, there is so much data redundancy that a series of problems such as large computation, low efficiency, inconvenient display and so on arise, making the application of 3D visualization and 3D reconstruction of buildings more challenging. To solve this problem, a thinning algorithm suitable for LiDAR point cloud data in urban area is proposed, which combines the terrain adaptive features of Poisson disk sampling in geodesic space. Poisson disk sampling randomly add points whose geodesic distance is larger than a certain threshold to the sampling point set, and repeat this process until there are no new sampling points can be added anymore. On this basis, according to the characteristics of LiDAR point cloud data, a new weighted geodesic distance related to the height standard deviation of the points around the selected point is defined to improve the Poisson disk sampling algorithm. This method can effectively adjust the sampling rate of urban buildings, so as to keep the original features of buildings as much as possible, and keep good visualization effect at the same time. The experimental results of four sets of data demonstrate the applicability and efficiency of the algorithm.
|
Received: 01 September 2018
Published: 23 March 2020
|
|
Corresponding Authors:
Xudong Lai
E-mail: cpq94@126.com;laixudong @whu.edu.cn
|
1 |
Lai Xudong, Li Yongxu, Chen Peiqi. Present Situation and Prospect of Airborne LiDAR Technology[J]. Geospatial Information, 2017, 15(8):1-4.
|
1 |
赖旭东, 李咏旭, 陈佩奇. 机载激光雷达技术现状及展望[J]. 地理空间信息, 2017, 15(8):1-4.
|
2 |
Lai Xudong. Fundamentals and Applications of Airborne LiDAR[M]. Beijing: Publishing House of Electronics Industry, 2010.
|
2 |
赖旭东. 机载激光雷达基础原理与应用[M]. 北京: 电子工业出版社, 2010.
|
3 |
Qian Jinju, Zhang Changsai, Wang Ke, et al. Research Review on Thinning Algorithm of Airborne LiDAR Point Cloud Data[J]. Bulletin of Surveying and Mapping, 2017(Sup.1):33-35.
|
3 |
钱金菊, 张昌赛, 王柯,等. 机载LiDAR点云数据抽稀算法研究述评[J]. 测绘通报, 2017(增刊1):33-35.
|
4 |
Zhang Xiaohong. Theory and Method of Airborne LiDAR Measurement Technology[M]. Wuhan: Wuhan University Press, 2007.
|
4 |
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.
|
5 |
Wang Xuejiao, Hong Youtang. The Application of Airborn LiDAR Technique in Rapid Production for High-accuracy DEM[J].Beijing Surveying and Mapping, 2011(4):46-48.
|
5 |
王雪娇, 洪友堂. 机载LiDAR技术在快速生产高精度DEM中的应用[J]. 北京测绘, 2011(4):46-48.
|
6 |
Wang Pu, Xing Yanqiu, Wang Cheng. Road Extraction Using Airborne LiDAR Data in Mountainous Areas[J]. Remote Sensing Technology and Application, 2017,32(5):851-857.
|
6 |
王璞, 王成, 习晓环,等. 机载LiDAR数据提取山区道路方法研究[J]. 遥感技术与应用, 2017, 32(5):851-857.
|
7 |
Xu Jingzhong, Wan Youchuan, Zhang Shengwang. On Simplification Method for LiDAR Ground Points Cloud[J]. Journal of Geomatcis, 2008,33(1):32-34.
|
7 |
徐景中, 万幼川, 张圣望. LiDAR地面点云的简化方法研究[J]. 测绘地理信息, 2008, 33(1):32-34.
|
8 |
Miao Zhixiu, Qi Hua, Wang Guochang, et al. Discussion on Thinning Algorithm for Construction of DEM based on Airborne LiDAR Data[J]. Railway Investigation and Surveying, 2010, 36(4):39-44.
|
8 |
缪志修, 齐华, 王国昌,等. 基于机载LiDAR数据构建的DEM抽稀算法研究[J]. 铁道勘察, 2010, 36(4):39-44.
|
9 |
Yang Mingjun, Su Chunmei, Kang Bingfeng, et al. Study and Application on Thinning Algorithm of Airborne LiDAR Data in Plain Area[J]. Bulletin of Surveying and Mapping, 2019(1):109-115.
|
9 |
杨明军, 苏春梅, 康冰锋,等. 平原地区机载激光雷达数据的抽稀算法分析[J]. 测绘通报, 2019(1):109-115.
|
10 |
Hou W, Zhang X, Li X, et al. Poisson Disk Sampling in Geodesic Metric for DEM Simplification[J]. International Journal of Applied Earth Observation & Geoinformation, 2013, 23(1):264-272.
|
11 |
Hou Wenguang, Wu Zicui, Ding Mingyue. Poisson Disk Sampling in Geodesic Metric for DEM Simplification[J]. Acta Electronica Sinica, 2012, 40(6):1274-1278.
|
11 |
侯文广, 吴梓翠, 丁明跃. 测地空间中泊松碟采样的地形模型约简方法[J]. 电子学报, 2012, 40(6):1274-1278.
|
12 |
Cook R. Stochastic Sampling in Computer Graphics[J]. ACM Trans Graph, 1986, 5(1):137-145.
|
13 |
Cao Lin, Xu Ziqian, Dai Jinsong, et al. Method Optimization and Accuracy Evaluation of Terrain and Buildings Extraction based on LiDAR and CCD Data[J]. Remote Sensing Technology and Application, 2014,29(1):130-137.
|
13 |
曹林, 许子乾, 代劲松,等. 基于LiDAR和CCD数据的地形与建筑提取方法优化及精度评价[J].遥感技术与应用,2014,29(1):130-137.
|
14 |
Dong Baogen, Ma Hongchao, Che Sen, et al. Method of Land Cover Refined Classification Supported by LiDAR Point Clouds[J]. Remote Sensing Technology and Application, 2016,31(1):165-169.
|
14 |
董保根, 马洪超, 车森,等. LiDAR点云支持下地物精细分类的实现方法[J].遥感技术与应用,2016,31(1):165-169.
|
15 |
Wei Guangyu, Gan Shu. Research on Elimination of Non-building Points in Airborne LiDAR Building Point Cloud[J]. Value Engineering, 2017, 36(2):31-33.
|
15 |
魏广宇, 甘淑. 机载LiDAR建筑物点云中非建筑物点剔除研究[J]. 价值工程, 2017, 36(2):31-33.
|
16 |
Tong Lihua, Cheng Liang, Li Manchun, et al. Extraction of Building Contours and Corners from Terrestrial LiDAR Data[J].Journal of Image and Graphics, 2013, 18(7):876-883.
|
16 |
童礼华, 程亮, 李满春,等. 地面LiDAR数据中建筑轮廓和角点提取[J]. 中国图象图形学报, 2013, 18(7):876-883.
|
17 |
Hu Cheng. Thinning Algorithm of LiDAR Bare Earth Surface Point Cloud Under the Restriction of Precision[D]. Chengdu: Southwest Jiaotong University, 2015.
|
17 |
胡诚. 精度约束下地表LiDAR点云抽稀方法研究[D]. 成都: 西南交通大学, 2015.
|
18 |
Zhao Chuan, Zhang Baoming, Chen Xiaowei, et al. A Method of Extracting Building based on LiDAR Point Clouds[J]. Bulletin of Surveying and Mapping, 2017(2):35-39.
|
18 |
赵传, 张保明, 陈小卫,等. 一种基于LiDAR点云的建筑物提取方法[J]. 测绘通报, 2017(2):35-39.
|
19 |
Fang Chengxi, Lichun Sui, Zhu Haixiong. LiDAR Point Cloud Thinning Algorithm for Road Survey and Design[J].Bulletin of Surveying and Mapping, 2017(10):58-61.方程喜, 隋立春, 朱海雄. 用于公路勘测设计的LiDAR点云抽稀算法[J]. 测绘通报, 2017(10):58-61.
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|