使用随机邻域分析的地面激光扫描点云采样间隔估算

doi:10.3969/j.issn.0255-8297.2022.06.009

Abstract

Abstract: This paper focuses on the estimation of sampling interval from terrestrial laser scanning data and presents an estimation method based on the neighboring analysis of randomly selected points. We select n central points from the randomly scanning data and search for k nearest points of each central point. The horizontal and vertical (with Z axis) angles between the laser beam of each central point and corresponding neighboring points are calculated. Then histograms of horizontal and vertical angles are constructed respectively, with interval step △. The average angle of the interval with the second largest number of points is recognized as the corresponding horizontal or vertical sampling interval. Finally, the median value of the horizontal or vertical sampling values generated from a series of △ values is used as the final estimation result. Tests are carried on the data obtained from different scanners and test code is shared on the MathWorks community. The test results show that the error of our method is smaller than 0.002° with good robustness with respect to different types of targets and parameter settings.

Key words: terrestrial laser scanning, sampling interval estimation, neighboring analysis, angular resolution, point cloud

CLC Number:

P237
TP391.4

CHEN Maolin, ZHANG Xinyi, LIU Xiangjiang, JI Cuicui, ZHAO Lidu. Estimating Sampling Interval of Terrestrial Laser Scanning Point Cloud with Neighboring Analysis of Randomly Selected Points[J]. Journal of Applied Sciences, 2022, 40(6): 984-995.

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Estimating Sampling Interval of Terrestrial Laser Scanning Point Cloud with Neighboring Analysis of Randomly Selected Points

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