通过传输矩阵的相干逆散射:有效的相位检索算法和公共数据集

Christopher A. Metzler, M. Sharma, S. Nagesh, Richard Baraniuk, O. Cossairt, A. Veeraraghavan
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引用次数: 58

摘要

传输矩阵描述了一个复杂波前穿过/反射多重散射介质(如磨砂玻璃或涂漆的墙壁)时的输入-输出关系。知道了介质的传输矩阵,就可以通过介质成像,通过介质发送信号,甚至可以将介质用作透镜。双相位恢复方法是最近提出的一种学习介质传输矩阵的技术,它避免了难以捕获的干涉测量。不幸的是,为了进行高分辨率成像,现有的双相检索方法需要(1)大量的测量和(2)不合理的计算量。在这项工作中,我们专注于这两个问题的后一个,并通过两种不同的方法减少计算时间:首先,我们开发了一种新的相位检索算法,该算法比现有方法快得多,特别是当与纯幅空间光调制器(SLM)一起使用时。其次,我们使用纯相位SLM来校准系统,而不是在以前的双相位恢复实验中使用的纯幅值SLM。这个看似微不足道的变化使我们能够使用更快的相位检索算法。由于这些进步,我们的计算时间减少了100倍,从而使我们能够以最先进的分辨率通过散射介质进行成像。除了这些进展,我们还发布了第一个公开可用的传输矩阵数据集。这一贡献将使相位检索研究人员能够将他们的算法应用于实际数据。这个社区特别感兴趣的是,我们的测量向量是自然的i.i.d亚高斯,也就是说,不需要编码的衍射图案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset
A transmission matrix describes the input-output relationship of a complex wavefront as it passes through/reflects off a multiple-scattering medium, such as frosted glass or a painted wall. Knowing a medium's transmission matrix enables one to image through the medium, send signals through the medium, or even use the medium as a lens. The double phase retrieval method is a recently proposed technique to learn a medium's transmission matrix that avoids difficult-to-capture interferometric measurements. Unfortunately, to perform high resolution imaging, existing double phase retrieval methods require (1) a large number of measurements and (2) an unreasonable amount of computation. In this work we focus on the latter of these two problems and reduce computation times with two distinct methods: First, we develop a new phase retrieval algorithm that is significantly faster than existing methods, especially when used with an amplitude-only spatial light modulator (SLM). Second, we calibrate the system using a phase-only SLM, rather than an amplitude-only SLM which was used in previous double phase retrieval experiments. This seemingly trivial change enables us to use a far faster class of phase retrieval algorithms. As a result of these advances, we achieve a 100x reduction in computation times, thereby allowing us to image through scattering media at state-of-the-art resolutions. In addition to these advances, we also release the first publicly available transmission matrix dataset. This contribution will enable phase retrieval researchers to apply their algorithms to real data. Of particular interest to this community, our measurement vectors are naturally i.i.d. subgaussian, i.e., no coded diffraction pattern is required.
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