Computational Interferometric Imaging
Computational Interferometric Imaging
复制标题
计算干涉成像
DOI：
10.1145/3587423.3595551
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Gkioulekas, Ioannis
中科院分区：
文献类型：
--
作者：
Kotwal, Alankar;Willomitzer, Florian;Gkioulekas, Ioannis
成像系统通常会累积光子，这些光子在从光源行进到相机时会遵循多个不同的路径并与多个场景对象交互。这种多路径累积过程混淆了捕获图像中关于场景的可用信息，并且使得使用这些图像来推断场景对象的属性（例如它们的形状和材料）具有挑战性。计算光传输技术通过使成像系统能够选择性地仅累积对于任何给定成像任务有用的光子来帮助克服这种多路径混淆问题。不幸的是，尽管在过去的二十年里，这种技术的扩散，他们被限制只能在宏观环境下运行。这使得它们无法用于需要显微分辨率的关键应用，例如医学成像和工业制造。在这篇论文中，我们通过引入一类新的技术来改变这种状况，我们称之为计算干涉成像：这些技术使用光学干涉测量实现计算光传输能力，这是一种非常适合于微米级应用的技术。我们通过操纵干涉测量设置中使用的照明属性或使用具有此类属性的自然可用照明来实现这一点。
IMAGING systems typically accumulate photons that, as they travel from a light source to a camera, follow multiple different paths and interact with several scene objects. This multi-path accumulation process confounds the information that is available in captured images about the scene, and makes using these images to infer properties of scene objects, such as their shape and material, challenging.Computational light transport techniques help overcome this multi-path confounding problem, by enabling imaging systems to selectively accumulate only photons that are informative for any given imaging task. Unfortunately, and despite a proliferation of such techniques in the last two decades, they are constrained to operate only under macroscopic settings. This places them out of reach for critical applications requiring microscopic resolutions, such as medical imaging and industrial fabrication. In this thesis, we change this state of affairs by introducing a new class of techniques that we call computational interferometric imaging: These techniques realize computational light transport capabilities using optical interferometry, a technology well-suited for micron-scale applications. We achieve this by either manipulating the properties of illumination used in interferometry setups, or using naturally-available illumination with such properties.