Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210093, China.
Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210093, China.
Sensors (Basel). 2018 May 21;18(5):1641. doi: 10.3390/s18051641.
The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become important for geospatial data applications. This paper presents a comprehensive review of LiDAR data registration in the fields of photogrammetry and remote sensing. At present, a coarse-to-fine registration strategy is commonly used for LiDAR point clouds registration. The coarse registration method is first used to achieve a good initial position, based on which registration is then refined utilizing the fine registration method. According to the coarse-to-fine framework, this paper reviews current registration methods and their methodologies, and identifies important differences between them. The lack of standard data and unified evaluation systems is identified as a factor limiting objective comparison of different methods. The paper also describes the most commonly-used point cloud registration error analysis methods. Finally, avenues for future work on LiDAR data registration in terms of applications, data, and technology are discussed. In particular, there is a need to address registration of multi-angle and multi-scale data from various newly available types of LiDAR hardware, which will play an important role in diverse applications such as forest resource surveys, urban energy use, cultural heritage protection, and unmanned vehicles.
多平台、多角度和多时相的激光雷达数据的集成已成为地理空间数据应用的重要手段。本文对摄影测量和遥感领域的激光雷达数据配准进行了全面的回顾。目前，激光雷达点云配准通常采用粗-精配准策略。首先使用粗配准方法实现良好的初始位置，然后基于此使用精配准方法进行配准。根据粗-精框架，本文回顾了当前的配准方法及其方法，并确定了它们之间的重要区别。缺乏标准数据和统一的评估系统被认为是限制不同方法进行客观比较的一个因素。本文还描述了最常用的点云配准误差分析方法。最后，讨论了激光雷达数据配准在应用、数据和技术方面的未来工作方向。特别是需要解决来自各种新型激光雷达硬件的多角度和多尺度数据的配准问题，这将在森林资源调查、城市能源利用、文化遗产保护和无人驾驶车辆等各种应用中发挥重要作用。
