  In this article, we describe and validate the first fully automatic parameter
optimization for thermal synthetic aperture visualization. It replaces previous
manual exploration of the parameter space, which is time consuming and error
prone. We prove that the visibility of targets in thermal integral images is
proportional to the variance of the targets' image. Since this is invariant to
occlusion it represents a suitable objective function for optimization. Our
findings have the potential to enable fully autonomous search and recuse
operations with camera drones.
