Hillmann Dierck, Pfäffle Clara, Spahr Hendrik, Burhan Sazan, Kutzner Lisa, Hilge Felix, Hüttmann Gereon
Opt Lett. 2019 Aug 1;44(15):3905-3908. doi: 10.1364/OL.44.003905.
Computational adaptive optics (CAO) is emerging as a viable alternative to hardware-based adaptive optics-in particular when applied to optical coherence tomography of the retina. For this technique, algorithms are required that detect wavefront errors precisely and quickly. Here we propose an extension of the frequently used subaperture image correlation. By applying this algorithm iteratively and, more importantly, comparing each subaperture not to the central subaperture but to several randomly selected apertures, we improved aberration correction. Since these modifications only slightly increase the run time of the correction, we believe this method can become the algorithm of choice for many CAO applications.
计算自适应光学（CAO）正在成为基于硬件的自适应光学的一种可行替代方案，特别是在应用于视网膜光学相干断层扫描时。对于这项技术，需要能够精确快速检测波前误差的算法。在这里，我们提出了对常用的子孔径图像相关性的扩展。通过迭代应用该算法，更重要的是，将每个子孔径与几个随机选择的孔径而不是中心子孔径进行比较，我们改进了像差校正。由于这些修改只会略微增加校正的运行时间，我们相信这种方法可以成为许多CAO应用的首选算法。
