Paper
19 May 2015 Textured digital elevation model formation from low-cost UAV LADAR/digital image data
Taylor C. Bybee, Scott E. Budge
Author Affiliations +
Abstract
Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (<$20k) UAV system fitted with ladar and electro-optical (EO) sensors. A texel camera fuses calibrated ladar and EO data upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Taylor C. Bybee and Scott E. Budge "Textured digital elevation model formation from low-cost UAV LADAR/digital image data", Proc. SPIE 9465, Laser Radar Technology and Applications XX; and Atmospheric Propagation XII, 94650H (19 May 2015); https://doi.org/10.1117/12.2177474
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Cameras

LIDAR

3D image processing

Unmanned aerial vehicles

Calibration

Electro optical modeling

Image registration

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