Real Time Deconvolution of Adaptive Optics Ground Based Telescope Imagery

Autor: Michael J. Steinbock, Timothy J. Schulz, Timothy Holmes, Toby Sanders, Melena Abijaoude, Anastacio Arreola, Robert Hedges, John Peters
Rok vydání: 2021
Předmět:
Zdroj: The Journal of the Astronautical Sciences. 69:175-191
ISSN: 2195-0571
0021-9142
DOI: 10.1007/s40295-021-00285-w
Popis: This article presents new developments in a multiframe blind deconvolution algorithm for imaging low earth orbiting objects during flyover. The foundational aspects of the algorithm rely on the constrained maximum likelihood (ML) formulation in the presence of Poisson noise, previously developed in Schulz et al. (2018). The new algorithm achieves real time evaluation capability at over two frames per second, which is allowed by two novel aspects. First, the prototype algorithms are transferred to highly parallelized computations on graphical processing units (GPUs) with CUDA implementation that reduce the computational time of a single iteration by a factor of up to 100. Second, new numerical optimization strategies are developed and demonstrated to accelerate the convergence of the algorithm by a factor of 5 to 10. Several other new capabilities are also demonstrated in this article. We derive and implement a modified variation of the algorithm that achieves subpixel resolution, which is shown effective on real and simulated data. Finally, a new post-processing visual enhancement technique is proposed with several examples, which in part helps deal with the dynamic range degradation due to glint.
Databáze: OpenAIRE
Externí odkaz: