Recent advances are presented for multiframe blind deconvolution (MFBD) of ground based telescope imagery for low-earth orbit objects. The iterative algorithm uses the maximum likelihood estimation optimization criterion. It is modeled from a previous well-known algorithm called the expectation-maximization (EM) algorithm. New renditions of the algorithm simplify the phase reconstruction, thereby reducing the complexity of the original EM algorithm. Examples are shown, with and without adaptive optics (AO). The system is being designed for on-the-fly streaming video operation.

Recent advances in multiframe blind deconvolution of ground based telescopes are presented. The paper focuses on practical aspects of the software and algorithm. (1) A computer simulation that models atmospheric turbulence, noise and other aspects, for testing and evaluation of the deconvolution system are explained. (2) A post-processing algorithm that corrects for glint due to specular and other bright reflections is presented. This glint correction is automated by a spatially adaptive scheme that calculates statistics of brightness levels. (3) Efforts to realize computational speed, wherein processing happens on-the-fly at streaming frame rates are underway. The massively parallel processing of graphical processing units (GPUs) and the Compute Unified Device Architecture (CUDA) language are used.