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Title: Real-time machine learning–enhanced hyperspectro-polarimetric imaging via an encoding metasurface
Light fields carry a wealth of information, including intensity, spectrum, and polarization. However, standard cameras capture only the intensity, disregarding other valuable information. While hyperspectral and polarimetric imaging systems capture spectral and polarization information, respectively, in addition to intensity, they are often bulky, slow, and costly. Here, we have developed an encoding metasurface paired with a neural network enabling a normal camera to acquire hyperspectro-polarimetric images from a single snapshot. Our experimental results demonstrate that this metasurface-enhanced camera can accurately resolve full-Stokes polarization across a broad spectral range (700 to 1150 nanometer) from a single snapshot, achieving a spectral sensitivity as high as 0.23 nanometer. In addition, our system captures full-Stokes hyperspectro-polarimetric video in real time at a rate of 28 frames per second, primarily limited by the camera’s readout rate. Our encoding metasurface offers a compact, fast, and cost-effective solution for multidimensional imaging that effectively uses information within light fields.  more » « less
Award ID(s):
2305139 2047446
PAR ID:
10549308
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
Science Advances
Date Published:
Journal Name:
Science Advances
Volume:
10
Issue:
36
ISSN:
2375-2548
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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