Real time stabilization of long range observation system turbulent video

Long Range Observation Systems is a domain, which carries a lot of interest in many fields such as astronomy (i.e. planet exploration), geology, ecology, traffic control, remote sensing, and homeland security (surveillance and military intelligence). Ideally, image quality would be limited only by the optical setup used, but, in such systems, the major cause for image distortion is atmospheric turbulence. The paper presents a real-time algorithm that compensates images distortion due to atmospheric turbulence in video sequences, while keeping the real moving objects in the video unharmed. The algorithm is based on moving objects extraction; hence turbulence distortion compensation is applied only to the static areas of images. For that purpose a hierarchical decision mechanism is suggested. First, a lightweight computational decision mechanism which extracts most stationary areas is applied. Then a second step improves accuracy by more computationally complex algorithms. Finally, all areas in the incoming frame that were tagged as stationary are replaced with an estimation of the stationary scene. The restored videos exhibit excellent stability for stationary objects while retaining real motion. This is achieved in real-time on standard computer hardware.