In airborne UAV operations, it is desirable to havemultiple UAVs operate in a cooperationmode tomaximize
the use of resources, as well as take unique advantages of increased views frommultiple positions separated
in time and space. This capability requires image registration across potentially widely different views that
are taken at different places or time. The resulting images also vary in their noise contents, resolutions,
and projection deformation. In this paper, we characterize the performance enhancement between single
view from a single UAV and multiple views by multiple UAVs using ROC curves. In addition, we propose
a computational framework to facilitate an efficient and accurate registration across images with varied
resolutions, noise levels, and projective deformation. We implement various stages in this framework and
demonstrate the promising results using low to medium resolution images with synthetically-generated
flying path and camera poses.
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