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A broadband hyperspectral image sensor with high spatio-temporal resolution.

Liheng Bian1, Zhen Wang2, Yuzhe Zhang2

  • 1State Key Laboratory of CNS/ATM & MIIT Key Laboratory of Complex-field Intelligent Sensing, Beijing Institute of Technology, Beijing, China. bian@bit.edu.cn.

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|November 7, 2024
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This summary is machine-generated.

We developed a compact, on-chip hyperspectral imaging sensor that captures detailed spectral data in real-time. This innovative technology enables high-resolution imaging for diverse applications, from agriculture to astronomy.

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Materials Science

Background:

  • Hyperspectral imaging (HSI) offers rich spatial-temporal-spectral data for material characterization.
  • Traditional HSI systems are often bulky, expensive, and computationally intensive.
  • There is a need for compact, high-resolution, and real-time HSI solutions.

Purpose of the Study:

  • To develop an on-chip computational hyperspectral imaging framework.
  • To achieve high spatial and temporal resolution in hyperspectral data acquisition.
  • To enable real-time HSI with reduced system complexity and cost.

Main Methods:

  • Integration of broadband modulation materials onto an image sensor chip.
  • Coupling spectral information non-uniformly to each pixel with high light throughput.
  • Utilizing intelligent reconstruction algorithms for multi-channel image recovery from single frames.
  • Fabrication of a broadband visible-near-infrared (400-1,700 nm) hyperspectral image sensor via photolithography.

Main Results:

  • Achieved an on-chip hyperspectral imaging framework with high spatial (1024x1024 pixels) and temporal (124 fps) resolution.
  • Developed a broadband visible-near-infrared sensor with 96 wavelength channels and 74.8% average light throughput.
  • Demonstrated real-time hyperspectral imaging capabilities through on-chip compression and agile computation.
  • Showcased versatile applications including intelligent agriculture, health monitoring, industrial automation, and astronomy.

Conclusions:

  • The on-chip computational hyperspectral imaging framework significantly advances HSI technology.
  • This compact and efficient sensor overcomes the limitations of traditional HSI systems.
  • The demonstrated applications highlight the broad potential of this technology across various fields.