Computational imaging without a computer: seeing through random diffusers at the speed of light
Computational imaging without a computer: seeing through random diffusers at the speed of light
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DOI：
10.1186/s43593-022-00012-4
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发表时间：
2022-01-26
期刊：
影响因子：
--
通讯作者：
Ozcan, Aydogan
中科院分区：
文献类型：
--
作者：
Luo, Yi;Zhao, Yifan;Ozcan, Aydogan
通过漫射器成像对迄今为止使用计算机展示的各种数字图像重建解决方案提出了一个具有挑战性的问题。在这里，我们提出了一种无需计算机的全光学图像重建方法，可以以光速透过随机漫射器进行观察。使用深度学习，训练一组透射衍射表面以全光学重建被未知的随机相位漫射器完全覆盖的任意物体的图像。经过一次性训练阶段后，所产生的衍射表面被制造出来，并形成一个无源光学网络，该网络物理上位于未知物体和图像平面之间，以通过未知的新相位漫射器全光学重建物体图案。我们使用相干太赫兹照明和由未知的随机漫射器扭曲的全光学重建物体（在训练期间从未使用过）通过实验证明了这一概念。与数字方法不同，全光学衍射重建除了照明光之外不需要电源。这种透过漫射器的衍射解决方案可以扩展到其他波长，并可能推动生物医学成像、天文学、大气科学、海洋学、安全、机器人、自动驾驶汽车等领域的各种应用。
Imaging through diffusers presents a challenging problem with various digital image reconstruction solutions demonstrated to date using computers. Here, we present a computer-free, all-optical image reconstruction method to see through random diffusers at the speed of light. Using deep learning, a set of transmissive diffractive surfaces are trained to all-optically reconstruct images of arbitrary objects that are completely covered by unknown, random phase diffusers. After the training stage, which is a one-time effort, the resulting diffractive surfaces are fabricated and form a passive optical network that is physically positioned between the unknown object and the image plane to all-optically reconstruct the object pattern through an unknown, new phase diffuser. We experimentally demonstrated this concept using coherent THz illumination and all-optically reconstructed objects distorted by unknown, random diffusers, never used during training. Unlike digital methods, all-optical diffractive reconstructions do not require power except for the illumination light. This diffractive solution to see through diffusers can be extended to other wavelengths, and might fuel various applications in biomedical imaging, astronomy, atmospheric sciences, oceanography, security, robotics, autonomous vehicles, among many others.