REFERENCE LIDAR SURFACES FOR ENHANCED AERIAL TRIANGULATION AND CAMERA CALIBRATION
Other literature type
Gneeniss, A. S.
Mills, J. P.
Miller, P. E.
Due to the complementary characteristics of lidar and photogrammetry, the integration of data derived from these techniques
continues to receive attention from the relevant research communities. The research presented in this paper draws on this by adopting
lidar data as a control surface from which aerial triangulation and camera system calibration can be performed. The research
methodology implements automatic registration between the reference lidar DTM and dense photogrammetric point clouds which are
derived using Integrated Sensing Orientation (ISO). This utilises a robust least squares surface matching algorithm, which is iterated
to improve results by increasing the photogrammetric point quality through self-calibrating bundle adjustment. After a successful
registration, well distributed lidar control points (LCPs) are automatically extracted from the transformed photogrammetric point
clouds using predefined criteria. Finally, self-calibrating bundle block adjustment using different configurations of LCPs is
performed to refine camera interior orientation (IO) parameters. The methodology has been assessed using imagery from a Vexcel
UltraCamX large format camera. Analysis and the performance of the camera and its impact on the registration accuracy was
performed. Furthermore, refinement of camera IO parameters was also applied using the derived LCPs. Tests also included
investigations into the influence of the number and weight of LCPs in the accuracy of the bundle adjustment. Results from the
UltraCamX block were compared with reference calibration results using ground control points in the test area, with good agreement
found between the two approaches.