Real-time image restoration for space-object imaging

Military applications such as optical space surveillance and civilian applications such as astronomical imaging often require adaptive optics to compensate images of distant objects that are dynamically blurred by atmospheric turbulence. Many factors prevent adaptive optics (AO) from restoring a fully diffraction-limited image quality. Accordingly, restoration methods such as blind deconvolution and contrast enhancement are applied to further improve such imagery. Sometimes, the restoration must take place with low-latency and real-time frame rates because video imagery needs to be viewed promptly. This paper describes a procedure for conducting multi-frame blind deconvolution on experimental AO-compensated imagery in real time. In the procedure, registration and windowing enabled deconvolution, and subsequent enhancements improved the visibility of object features for visual assessment. This process features "multi-frame online blind deconvolution," which is a modification of the previously published "online blind deconvolution." This modified algorithm jointly processes multiple frames simultaneously, making it a true multi-frame, blind deconvolution method. The new method was tested on simulated and experimental imagery. The full procedure was implemented on a workstation with a low-end graphics processing unit, and timing tests were evaluated to estimate execution times.