唐涛,雷婉,孙轩

• 1:广东省国土资源测绘院
• 2:国家超级计算深圳中心
• 3:南开大学周恩来政府管理学院

摘要(Abstract)：

传统的线性预测滤波算法将目标点云划分为多个栅格,滤波在每一个栅格内进行,而滤波栅格大小,需要用户手动调整。针对此问题,该文提出一种从机载激光扫描数据中生成数字高程模型(DEM)的有效方法。引入统计学变量——面高程变异系数,刻画地形起伏特征,并建立线性预测滤波算法中栅格大小与面高程变异系数之间的函数关系。最后,利用几组点云数据为研究对象验证该方法的有效性,实验结果表明,该方法能自适应地根据地形的起伏特征调整滤波参数,得到比较理想的地面点数据,最终内插得到高精度的DEM。

关键词(KeyWords)： 机载LiDAR;数字高程模型;点云滤波;线性预测;地形起伏特征

Abstract:

Keywords:

基金项目(Foundation): 空间信息智能感知与服务深圳市重点实验室(深圳大学)开放基金资助项目;; 中央高校基本科研业务费专项资金项目(NKZXB1483)

作者(Author): 唐涛,雷婉,孙轩

DOI: 10.16251/j.cnki.1009-2307.2017.01.028

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