A new aerial image matching method using airborne LiDAR point cloud and POS data

Abstract

A novel aerial image tie point matching algorithm with the assistance of airborne LiDAR point cloud and POS data is proposed. Firstly, the conjugate point searching strategy used in traditional correlation coefficient matching is improved and a fast algorithm is presented. Secondly, an automatic camera boresight misalignment calibration method based on virtual ground control points is proposed, then the searching range of image matching is adaptively determined and applied to the image matching of the entire surveying area. Test results verified that the fast correlation coefficient matching algorithm proposed can reduce approximately 25% of the matching time without the loss of matching accuracy. The camera boresight misalignment calibration method can effectively increase the accuracy of exterior orientation elements of images calculated from POS data, and thus can significantly improve the predicted position of conjugate point for tie point matching. Our proposed image matching algorithm can achieve high matching accuracy with multi-scale, multi-view, cross-flight aerial images.