论文标题
使用Kraken多帧盲卷算法的AO后高分辨率成像
Post-AO high-resolution imaging using the Kraken multi-frame blind deconvolution algorithm
论文作者
论文摘要
在用于大型望远镜的极端自适应光学器件（EXAO）的背景下，我们介绍了用于处理高添加性采集的Kraken多帧盲型反卷积（MFBD）算法，能够对源亮度分布进行衍射限制估计。这是通过在入口瞳孔上的瞬时波前估计驱动的序列中对每个帧的数据建模来实现的。在适当的物理在物理上，从紧凑的MFBD（CMFBD）开始的迭代方案可以保证数值收敛，该迭代方案提供了非常强大的初始猜测，该猜测仅采用了几个帧。我们描述了该过程背后的数学，并报告了光谱二进制α的高分辨率重建和（16.3 MAS分离）与Shark-Vis的前体获得的（16.3 MAS分离），Shark-Vis的前体是大型双眼望远镜的即将到来的高对比度相机。
In the context of extreme adaptive optics (ExAO) for large telescopes, we present the Kraken multi-frame blind deconvolution (MFBD) algorithm for processing high-cadence acquisitions, capable to provide a diffraction-limited estimation of the source brightness distribution. This is achieved by a data modeling of each frame in the sequence driven by the estimation of the instantaneous wavefront at the entrance pupil. Under suitable physical contraints, numerical convergence is guaranteed by an iteration scheme starting from a Compact MFBD (CMFBD) which provides a very robust initial guess which only employs a few frames. We describe the mathematics behind the process and report the high-resolution reconstruction of the spectroscopic binary α And (16.3 mas separation) acquired with the precursor of SHARK-VIS, the upcoming high-contrast camera in the visible for the Large Binocular Telescope.
