Seeing invisible objects with intelligent optics

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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Publication Details

Journal
Light Science & Applications
Published
2024-09-05
DOI
https://doi.org/10.1038/s41377-024-01575-2
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

Seeing invisible objects with intelligent optics

Andrew Forbes, Isaac M. Nape
Light Science & Applications
Neural Networks and Reservoir Computing
article

Seeing invisible objects with intelligent optics

Andrew Forbes, Isaac M. Nape
article en

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.

Light Science & ApplicationsVol. 13(1)
University of the Witwatersrand (ZA)
Openalex Percentile: Top 87%
Neural Networks and Reservoir Computing
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