基于Kraken多帧盲解卷积算法的AO后高分辨率成像
Post-AO high-resolution imaging using the Kraken multi-frame blind deconvolution algorithm
摘要：
在极端自适应光学（ExAO）的大望远镜的背景下，我们提出了Kraken多帧盲解卷积（MFBD）算法处理高节奏的收购，能够提供一个衍射有限的估计源亮度分布。这是通过估计入射光瞳处的瞬时波前驱动的序列中的每个帧的数据建模来实现的。在适当的物理约束下，数值收敛是由一个迭代计划从紧凑MFBD（CMFBD），它提供了一个非常强大的初始猜测，只采用了几个帧。我们描述了这一过程背后的数学原理，并报告了用SHARK-VIS的前体获得的光谱二进制α和（16.3质量分离）的高分辨率重建，SHARK-VIS是即将到来的大型双目望远镜可见光高对比度相机。
英文摘要：
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.
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