基于强度数据的地面激光点云自适应非监督分类  

Adaptive Unsupervised Classification of TLS Point Cloud Based on Intensity Data

作　　者：谭凯[1] 程效军[1] 

机构地区：[1]同济大学测绘与地理信息学院,上海200092

出　　处：《激光与光电子学进展》2016年第3期234-240,共7页Laser & Optoelectronics Progress

基　　金：国土环境与灾害监测国家测绘地理信息局重点实验室开放基金(LEDM2014B05);"十二五"国家科技支撑计划(2013BAK08B07)

摘　　要：基于激光雷达测距方程与扫描仪的辐射机制,建立激光强度值的线性改正模型。考虑到各种噪声的影响及非线性效应,对参数进行修正,建立强度值的修正改正模型,去除激光测距值及激光入射角对强度值的影响,得到仅与目标反射特性相关的改正强度值。通过设置类别总数,初始阈值及阈值步长,利用改正后强度值,提出了一种点云自适应非监督分类的方法。实验结果表明:基于修正模型改正后强度值的点云自适应非监督分类方法可以精确地对点云进行分类,整体分类精度达到84%。Based on the laser radar range equation and the radiation mechanism of the laser scanner systems, the linear laser intensity correction model is established. Taking into account of the noise impacts and nonlinear effects, a modified correction model is established by revising the parameters, which aims to remove the effects of range and incidence angle to obtain a corrected intensity value associated merely with the target reflection characteristics. By setting the total number of categories, the initial threshold and the threshold step, an adaptive unsupervised classification method is proposed based on the corrected intensity. Experimental results show that the adaptive unsupervised classification method based on the corrected intensity data can accurately classify the point cloud, and the overall accuracy is 84%.

关 键 词：遥感 点云分类 激光强度 激光入射角 激光测距值 非监督分类 

分 类 号：P232[天文地球—摄影测量与遥感]