计算机科学
干涉测量
光学
计算机视觉
人工智能
计算机图形学(图像)
物理
作者
Isaac Nape,Andrew Forbes
标识
DOI:10.1038/s41377-024-01575-2
摘要
Abstract Transparent objects are invisible to traditional cameras because they can only detect intensity fluctuations, necessitating the need for interferometry followed by computationally intensive digital image processing. Now it is shown that the necessary transformations can be performed optically by combining machine learning and diffractive optics, for a direct in-situ measurement of transparent objects with conventional cameras.
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