利用线特征进行高分辨率影像与LiDAR点云的配准

Registration of LiDAR Point Clouds and High Resolution Images Based on Linear Features

  • 摘要: 试图从离散点云数据中寻找影像的同名点是非常困难的,因此传统的基于同名特征点的配准方法难以使用。应用共线方程作为严格配准模型,利用LiDAR点云空间中的线特征替代传统配准模型中的点特征,取得了高精度的配准结果,同时对点云密度和影像分辨率之间的尺度关系进行了半定量分析。

     

    Abstract: To find tie points from semi-randomly distributed point clouds is difficult,though such a task can be completed much easier in terms of images.Therefore,conventional imageto-image registration algorithms are no longer valid,where tie points are the main features for calculating registration parameters.We take the collinearity equation as a strict mathematical model for registration,and replace point features by linear ones through the parametric form of a straight line.High accuracy registration results have been achieved by such a manner.Meanwhile,semi-quantitative analysis is conducted in terms of the relationship between the image resolution and the LiDAR point density,which,to the author's best knowledge,has never been performed in literature.

     

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