机载LiDAR点云定量化局部结构信息分析

Quantitative Local Structural Information Analysis of Airborne LiDAR Point Cloud

提出一种基于特征值的机载LiDAR数据定量化局部信息量分析方法。通过引入多项策略改进了传统主成分分析(PCA)点云局部结构分析对噪声敏感的缺点,利用这种鲁棒性很强的PCA局部结构分析结果,从信息论的角度给出了一种点云局部结构定量化分析的新方法。实验结果表明,该方法能够有效实现对机载LiDAR点云数据结构信息量的有效分析。

In this paper, a method for quantitative local information analysis of airborne Li DAR data based on eigen-feature was proposed. Noisesensitivity which was the vital drawback of the classical PCA based local was improved by employing several strategies. With the results of the proposed robust PCA based on structure analysis method, the corresponding quantitative local information was formulated from the view ofinformation theory. Experimental results illustrate that the proposed method can be used to efficiently obtain reliable structural information of airborne LiD AR data.