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航空影像辅助的机载LiDAR植被点云分类

Classification of Airborne LiDAR Vegetation Piont Clouds Assisted by Aerial Images

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摘要

针对从非地面点云数据中难以自动分类植被和建筑物的问题,提出一种航空影像辅助的机载LiDAR(Light Detection and Ranging)植被点云分类方法。根据植被的光谱特征明显不同于其他地物这一特点,在生成数字正射影像的基础上,首先利用K均值(K-means)聚类算法对影像进行聚类和图像增强,然后将增强后的影像和对应区域的点云数据进行融合,最后通过影像处理结果对机载LiDAR植被点云进行分类。选取某城市的机载LiDAR植被点云数据和航空影像进行实验,定量分析结果显示所提方法的总分类精度为96.47%,Kappa系数为0.9248,该方法能够达到点云中植被自动分类的目的。

Abstract

Since it is difficult to automatically distinguish between vegetation and buildings from non-ground point cloud data, this research work proposes a method to automatically classify vegetation in airborne LiDAR (Light Detection and Ranging) point clouds, which is assisted by aerial image. Based on the fact that the spectral characteristics of vegetation are clearly different from other ground objects, digital orthophoto generation and K-means clustering algorithm are employed to cluster and enhance the images. Then, the enhanced image and the point cloud data of the corresponding area are fused. Finally, the airborne LiDAR vegetation point cloud data is classified using the image processing results. Experiments are carried out on airborne LiDAR vegetation point cloud data and aerial images of a particular city. Quantitative analysis results prove that total classification accuracy of the proposed method is 96.47%, and the Kappa coefficient is 0.9248. The introduced method can pave the way for automatic classification of the vegetation in LiDAR point clouds.

广告组1 - 空间光调制器+DMD
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中图分类号:P237

DOI:10.3788/LOP57.201005

所属栏目:图像处理

基金项目:国家自然科学基金、河南省重点研发与推广专项、河南省高等学校重点科研项目、河南工程学院博士基金;

收稿日期:2020-01-19

修改稿日期:2020-02-24

网络出版日期:2020-10-01

作者单位    点击查看

王果:河南工程学院土木工程学院, 河南 郑州 451191
王强:天津师范大学天津市地理空间信息技术工程中心, 天津 300387
张振鑫:首都师范大学资源环境与旅游学院, 北京 100048
徐棒:河南工程学院土木工程学院, 河南 郑州 451191
赵光兴:河南工程学院土木工程学院, 河南 郑州 451191

联系人作者:王果(wg@haue.edu.cn)

备注:国家自然科学基金、河南省重点研发与推广专项、河南省高等学校重点科研项目、河南工程学院博士基金;

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引用该论文

Wang Guo,Wang Qiang,Zhang Zhenxin,Xu Bang,Zhao Guangxing. Classification of Airborne LiDAR Vegetation Piont Clouds Assisted by Aerial Images[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201005

王果,王强,张振鑫,徐棒,赵光兴. 航空影像辅助的机载LiDAR植被点云分类[J]. 激光与光电子学进展, 2020, 57(20): 201005

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