Eliminating and modelling non-metric camera sensor distortions caused by sidewise and forward motion of the UAV

Abstract

This paper explains the critical importance of modelling and eliminating the effect of motion of an Unmanned Aerial Vehicle (UAV) as a result of air turbulence and unstable flight conditions on a camera sensor and the image geometry. A new method for improving the geometrical distortions caused by this motion is introduced. We have developed a hardware and software tool to minimize and model the geometric distortion of the image from commercial off-the-shelf (COTS) cameras which are commonly being used in aerial mapping UAVs. Due to the rolling shutter mechanism of the most common SLR cameras, sideway and forward motions of the UAV during image capture will have a strong effect on the image geometry and final product accuracies. As the amount of this random distortion varies from one photo to the next, a unique and robust camera calibration model cannot be established for interior orientation and image processing using photogrammetric methods, even by self-calibration. To achieve the highest possible accuracy, we also consider temperature effects on the camera calibration parameters. In this paper we show the results, accuracies and benefits of using this method compared with a typical UAV mapping system. To the best of our knowledge this is the first time that this method has been implemented in a UAV mapping system.