摘要
为发挥机载全波形激光探测与测量(light detection and ranging,LiDAR)技术优势,提高数字高程模型(digital elevation model,DEM)生成精度,提出了一种利用波形信息的加权曲面拟合LiDAR点云滤波方法。该方法利用全局收敛LM解算离散点云与波形参数,引入波形信息与抗差估计原理检测异常种子点,依据波形参数对地形曲面进行加权拟合,综合考虑滤波窗口尺寸与曲面拟合中误差影响设置自适应高差阈值。选取中国黑河综合遥感联合实验中的城市区域、耕地区域与山地区域数据进行实验,结果表明,相比传统方法,所提方法的波形分解结果更加可靠,点云滤波精度进一步提高,具备较高实用价值。
The important application of full-waveform LiDAR technology is to obtain high-precision DEM by making use of waveform data.The weighted curve fitting filtering method is proposed fusing waveform information.Discrete point cloud and waveform parameters are resolved by using global convergent LM.The waveform information and robust estimation theory are introduced to detect abnormal seed points.Then,the terrain curve is fitted according to waveform parameters.And the selfadaptive height difference threshold is determined in consideration of the window size and mean square error.The waveform data in urban,farmland and mountain areas from "WATER(watershed allied telemetry experimental research)"are selected for experiments.Experimental results prove that compared with traditional method,waveform decomposition results from proposed method are more reliable,the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2018年第3期420-427,共8页
Geomatics and Information Science of Wuhan University
基金
地理信息工程国家重点实验室开放研究基金(SKLGIE2016-M-3-1)~~
关键词
全波形LiDAR
波形分解
点云滤波
全局收敛LM
地面种子点
加权曲面拟合
full-waveform LiDAR
waveform decomposition
point cloud filtering
global convergent LM
ground seed points
weighted curve fitting
