  We propose a guidance strategy to optimize real-time synthetic aperture
sampling for occlusion removal with drones by pre-scanned point-cloud data.
Depth information can be used to compute visibility of points on the ground for
individual drone positions in the air. Inspired by Helmholtz reciprocity, we
introduce reciprocal visibility to determine the dual situation - the
visibility of potential sampling position in the air from given points of
interest on the ground. The resulting visibility map encodes which point on the
ground is visible by which magnitude from any position in the air. Based on
such a map, we demonstrate a first greedy sampling optimization.
