Multiscale Image Matching for Automated Calibration of UAV-Based Frame and Line Camera Systems

Abstract

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems together with frame and/or line cameras are used for a variety of applications. Geometric system calibration is crucial for delivering accurate products from UAV-based imaging systems. This article presents automated geometric calibration strategies for UAV-based frame and line camera systems to estimate accurate system calibration parameters without the need for ground control points or manual measurements of tie points. The matching strategy used in this article to establish conjugate features among overlapping frame camera images is based on a traditional Structure from Motion technique augmented with several layers of matching outlier removal. On the other hand, a new strategy relying on ortho-rectified images is introduced for automated feature matching in line camera scenes. Then, a general bundle adjustment procedure with system calibration capabilities for frame and line cameras is presented, where the derived automated tie points are used for estimating accurate geometric system calibration parameters. The proposed approach is evaluated using four datasets—two datasets captured by frame cameras and two datasets captured by line cameras. The results show that the developed automated calibration strategy is capable of producing the same level of absolute accuracy when compared to using manually measured tie points for both frame camera and line camera systems. Results also indicate that the presented automated system calibration approach can be applied to systems even with significant deviation of actual system parameters from their nominal values, and still produce accurate estimates of calibration parameters.