The fusion of aerial imagery and LiDAR point clouds are considered as one of the most promising approaches for many fields, such as 3D city reconstruction and tree detection. The purpose of this paper is to achieve reliable registering LiDAR data and aerial images without orientation parameters based on a progressive optimizing process.
First, combination of edges and their corners is extracted and considered as registration primitives; then search conjugate primitives globally with a suitable buffer of each edge; after that, a progressive algorithm is adopted to optimize the registration; finally, error analysis and data fusion are carried out.
After a progressive optimum algorithm, the number and the distribution of the matched pairs are sufficient for generation of reliable and accurate orientation parameters. The results show RMS of residual errors gets close to one DSM cell, which is equal to or even better than that in other literatures.
The method proposed in the paper is feasible and effective to generate reliable and accurate registering results.
