Relative orientation between a single frame image and LIDAR point cloud using linear features

Registration of multi-source remote sensing data is an essential task prior their efficient integrated use. It is known that accurate registration of different data sources, such as aerial frame images and lidar data, is a challenging process, where extraction and selection of robust tie features is the key issue. In the presented approach, we used linear features, namely roof ridges, as tie features. Roof ridges derived from lidar data are automatically located in the 2D image plane and the relative orientation is based on the well-known coplanarity condition. According to the results, the average registration (absolute) errors varied between 0.003 to 0.196 m in the X direction, between 0.018 to 0.282 m in the Y direction and between 0.010 to 0.967 m in the Z direction. Rotation (absolute) errors varied between 0.001 to 0.078 degrees, 0.006 to 0.466 degrees and 0.013 to 0.115 degrees for ω, ϕ and κ rotations, respectively. This study revealed that the method has potential in automatic relative orientation of a single frame image and lidar data. However, the distribution, orientation and the number of successfully located tie features have an essential role in succeeding in the task.