Integration of LiDAR and photogrammetric data for enhanced aerial triangulation and camera calibration

Abstract

The integration of complementary airborne light detection and ranging (LiDAR) and photogrammetric data continues to receive attention from the relevant research communities. Such an approach requires the optimized registration of the two data types within a common coordinate reference frame and thus enables the cross-calibration of one information source against another. This research assumes airborne LiDAR as a reference dataset against which in-flight camera system calibration and validation can be performed. The novel methodology involves the production of dense photogrammetric point clouds derived using the simultaneous adjustment of GNSS/IMU data and a dense set of photogrammetric tie points. Quality of the generated photogrammetric dataset is further improved through introducing the self-calibration additional parameters in the combined adjustment. A robust least squares surface matching algorithm is then used to minimise the Euclidean distances between the two datasets. After successful matching, well distributed LiDAR-derived control points (LCPs) are automatically identified and extracted. Adjustment of the photogrammetric data is then repeated using extracted LCPs in a self-calibrating bundle adjustment. The research methodology was tested using two datasets acquired using different photogrammetric digital sensor systems, a Microsoft UltraCamX large format camera and an Applanix DSS322 medium format camera. Systematic sensitivity testing included the influence of the number and weighting of LCPs required to achieve optimised adjustment. For the UltraCamX block it was found that when the number of control points exceeded 80, the accuracy of the adjustment stabilized at c. 2 cm in all axes, regardless of point weighting. Results were also compared with those from reference calibration using surveyed ground control points in the test area, with good agreement found between the two. Similar results were obtained for the DSS322 block, with block accuracy stabilizing at 100 LCPs. Moreover, for the DSS322 camera, introducing self-calibration greatly improved the accuracy of aerial triangulation.