Trilobite-inspired neural nanophotonic light-field camera with extreme depth-of-field

Qingbin Fan, Weizhu Xu, Xuemei Hu, Wenqi Zhu, Tao Yue (), Cheng Zhang, Feng Yan (), Lu Chen, Henri J. Lezec, Yanqing Lu (), Amit Agrawal and Ting Xu ()
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Qingbin Fan: Nanjing University
Weizhu Xu: Nanjing University
Xuemei Hu: Nanjing University
Wenqi Zhu: National Institute of Standards and Technology
Tao Yue: Nanjing University
Cheng Zhang: Huazhong University of Science and Technology
Feng Yan: Nanjing University
Lu Chen: National Institute of Standards and Technology
Henri J. Lezec: National Institute of Standards and Technology
Yanqing Lu: Nanjing University
Amit Agrawal: National Institute of Standards and Technology
Ting Xu: Nanjing University

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: Abstract A unique bifocal compound eye visual system found in the now extinct trilobite, Dalmanitina socialis, may enable them to be sensitive to the light-field information and simultaneously perceive both close and distant objects in the environment. Here, inspired by the optical structure of their eyes, we demonstrate a nanophotonic light-field camera incorporating a spin-multiplexed bifocal metalens array capable of capturing high-resolution light-field images over a record depth-of-field ranging from centimeter to kilometer scale, simultaneously enabling macro and telephoto modes in a snapshot imaging. By leveraging a multi-scale convolutional neural network-based reconstruction algorithm, optical aberrations induced by the metalens are eliminated, thereby significantly relaxing the design and performance limitations on metasurface optics. The elegant integration of nanophotonic technology with computational photography achieved here is expected to aid development of future high-performance imaging systems.

Date: 2022
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DOI: 10.1038/s41467-022-29568-y

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