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<p>Compact, high-quality imaging systems are highly desired for scientific, industrial, and consumer applications. Metalenses combined with computational imaging offer a promising solution for developing such systems, yet their performance is fundamentally limited by the commonly used point-to-point imaging model, which forces trade-offs between aperture size, F-number, field of view (FOV), waveband width, and image quality. Here, we experimentally demonstrate that a neural array imaging model can overcome these long-standing trade-offs, achieving a 25-Hz full-color imaging camera with a 2.76-mm aperture, 1.45 F-number, 50<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mrow /> <mo>∘</mo> </mmultiscripts> </math></EquationSource> </InlineEquation> FOV, and a spectral range of 400–700&#xa0;nm. The camera achieves image quality comparable to commercial compound lenses (e.g., Edmund 33-300) in both indoor and outdoor environments, while reducing the total track length by a factor of 13. We further demonstrate its suitability for object detection and depth estimation in real-world scenarios. This neural array imaging model is also applied to polarization imaging, showcasing its scalability and versatility for broadband applications.</p>

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Neural array meta-imaging

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月1日

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  • Xiong Dun,
  • Jian Zhang,
  • Fansheng Chen,
  • Zhanyi Zhang,
  • Xuquan Wang,
  • Yujie Xing,
  • Siyu Dong,
  • Zeying Fan,
  • Yuzhi Shi,
  • Wetzstein Gordon,
  • Zhanshan Wang,
  • Xinbin Cheng

摘要

Compact, high-quality imaging systems are highly desired for scientific, industrial, and consumer applications. Metalenses combined with computational imaging offer a promising solution for developing such systems, yet their performance is fundamentally limited by the commonly used point-to-point imaging model, which forces trade-offs between aperture size, F-number, field of view (FOV), waveband width, and image quality. Here, we experimentally demonstrate that a neural array imaging model can overcome these long-standing trade-offs, achieving a 25-Hz full-color imaging camera with a 2.76-mm aperture, 1.45 F-number, 50 \(^{\circ }\) ∘ FOV, and a spectral range of 400–700 nm. The camera achieves image quality comparable to commercial compound lenses (e.g., Edmund 33-300) in both indoor and outdoor environments, while reducing the total track length by a factor of 13. We further demonstrate its suitability for object detection and depth estimation in real-world scenarios. This neural array imaging model is also applied to polarization imaging, showcasing its scalability and versatility for broadband applications.