CAJ | 학술논문

提出了一种基于高程统计的LiDAR数据滤波方法，该方法以高程分布统计量为依据。通过迭代的方法逐个滤除，是一种基于原始点云的非监督滤波算法。采用北京凤凰岭地区某块机载LiDAR数据进行实验，并做出了实验改进。实验表明，该方法能够准确有效地滤除地物点，既能较好地保持数据信息量与精度，又不依赖于其他数据源，是一种简单有效的滤波算法。
제출료일충기우고정통계적LiDAR수거려파방법，해방법이고정분포통계량위의거。통과질대적방법축개려제，시일충기우원시점운적비감독려파산법。채용북경봉황령지구모괴궤재LiDAR수거진행실험，병주출료실험개진。실험표명，해방법능구준학유효지려제지물점，기능교호지보지수거신식량여정도，우불의뢰우기타수거원，시일충간단유효적려파산법。
The authors put forward a LiDAR data filtering method based on the statistics of elevation distribution in this research. The proposed method ,which is unsupervised and bases itself on raw points cloud, filters out object points via iteration on the basis of the statistics of elevation distribution. An experiment is conducted and improved with a group of LiDAR data of Fenghuangling area in Beijing. The results show that the proposed algorithm is simple and effective in filtering out object points, keeping data quantity and precision at the same time without relying on other data sources.