Fast and Optimal Multi-Frame Blind Deconvolution Algorithm for High- Resolution Ground-Based Imaging of Space Objects--Journal Article (Preprint); Journal article

摘要

We report on a multi-frame blind deconvolution algorithm that we have developed for imaging through the atmosphere. The algorithm has been parallelized to a significant degree for execution on high-peformance computer, with an emphasis on distributed-memory systems so that it can be hosted on commodity clusters. As a result, image restorations can be obtained in seconds to minutes. We have compared the quality of its output to the associated Crammer-Rao lower bounds and demonstrated that, for the cases we have tested, it achieves or closely approaches these bounds. In this paper, we describe the algorithm and its parallelization in detail, demonstrate the scalability of its parallelization across associated Crammer-Rao lower bounds, and present image restorations obtained using data collected with ground-based telescopes.