TURBULENT IMAGE-RECONSTRUCTION FROM A SUPERPOSITION MODEL

Imagery through random atmospheric turbulence is modelled as a stochastic superposition process. By this model, each short-exposure spread function is a superposition of randomly weighted and displaced versions of (ideally) one intensity profile, e.g. an Airy disc. In principle, this allows an object scene to be reconstructed from but two short-exposure images, and without the need for a point reference source in the field. A computational approach has been found implementing the reconstruction of simple objects. Some computer-simulated demonstrations of the approach are given. Generalization of the approach to more complex objects is currently under development.