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ON VOLUME DATA REDUCTION FOR LIDAR DATASETS
LiDAR Redundancy Q-tree Big Data Problem Topography DTM
2018/11/9
This paper discusses a current issue for several experimental science disciplines, which is the Big Data Problem (BDP). This research study focused on light intensity and ranging (LiDAR) datasets, whi...
LIDAR Data Reduction for Efficient and High Quality DEM Generation
LiDAR Laser Scanning DEM Interpolation Catchment Data Reduction
2015/12/8
Airborne Light Detection and Ranging (LiDAR) - also referred to as Airborne Laser Scanning (ALS), provides means for high density and high accuracy topographic data acquisition. LiDAR data have become...
基于非均匀细分的散乱点云数据精简算法（Algorithm of Scattered Point Cloud Data Reduction Based on Non-uniform Subdivision）
逆向工程 散乱点云 非均匀细分
2009/9/25
针对海量散乱点云数据精简问题，提出了基于非均匀细分的精简算法。采用八叉树结构对点云数据进行空间分割，由分割结果建立k邻域。对k邻域内的散乱点进行二次曲面拟合，以拟合曲面的平均曲率为判据决定是否对八叉树空间实行非均匀细分，细分过程中由数据点之间的最大间隔角决定细分程度。构造曲率差函数，识别出边界数据点，对其进行数据保护。该算法对具有曲率多样化特点的点云数据的精简具有实用性，通过实验验证了该算法的可靠...
The k-nearest neighbours (kNN) is a simple but effective method for classification. Its major drawbacks are (1) low efficiency, and (2) dependency on the selection of a “good value” for k. In this pap...