Aerial photography obtained by UAVs (Unmanned Aerial Vehicles) is an emerging market for civil applications. Small UAVs are believed to close gaps in niche markets, such as acquiring airborne image data for remote sensing purposes. Small UAVs will be able to fly at low altitudes, in dangerous environments and over long periods of time. However, the small lightweight constructions of these UAVs lead to new problems, such as higher agility leading to more susceptibility to turbulence and limitations in space and payload for sensor systems. This research investigates the use of low-cost fisheye lenses to overcome such problems which theoretically makes the airborne imaging less sensitive to turbulence. The fisheye lens has the benet of a large observation area (large field of view) and doesn't add additional weight to the aircraft, like traditional mechanical stabilizing systems. This research presents the implementation of a fisheye lens for aerial photography and mapping purposes, including theoretical background of fisheye lenses. Based on the unique feature of the distortion being a function of the viewing angle, methods used to derive the fisheye lens distortion are presented. The lens distortion is used to rectify the fisheye images before these images can be used in aerial photography. A detailed investigation into the inner orientation of the camera and inertial sensor is given, as well as the registration of airborne collected images. It was found that the attitude estimation is critical towards accurate mapping using low quality sensors. A loosely coupled EKF filter applied to the GPS and inertial sensor data estimated the attitude to an accuracy of 3-5° (1-sigma) using low-cost sensors typically found in small UAVs. However, the use of image stitching techniques may improve the outcome. On the other hand, lens distortion caused by the fisheye lens can be addressed by rectification techniques and removed to a sub-pixel level. Results of the process present image sequences gathered from a piloted aircraft demonstrating the achieved performance and potential applications towards UAVs. Further, an unforeseen issue with a vibrating part in the lens lead to the need for vibration compensation. The vibration could be estimated to ±1 pixel in 75% of the cases by applying an extended Hough transform to the fisheye images.
| Identifer | oai:union.ndltd.org:ADTP/265812 |
| Date | January 2008 |
| Creators | Gurtner, Alex |
| Publisher | Queensland University of Technology |
| Source Sets | Australiasian Digital Theses Program |
| Detected Language | English |
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