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Single-pixel Fresnel incoherent correlation holography compressed imaging using a Trumpet network.

Jiaosheng Li1, Yifei Chen1, Tianyun Liu1

  • 1School of Photoelectric Engineering, Guangdong Polytechnic Normal University, Guangzhou, 510665, China.

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|June 14, 2024
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Summary

Single-pixel Fresnel incoherent correlation holography (SP-FINCH) offers a low-cost, high-resolution 3D imaging solution. This compressed imaging method uses a Trumpet network for efficient data reconstruction, improving image quality at lower sampling rates.

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Holography

Background:

  • Fresnel incoherent correlation holography (FINCH) enables high-precision, non-scanning 3D imaging.
  • High bandwidth requirements and data volume limit FINCH applications.
  • High-resolution imaging with traditional detectors incurs significant hardware costs.

Purpose of the Study:

  • To propose a single-pixel Fresnel incoherent correlation holography (SP-FINCH) compressed imaging method.
  • To develop a low-cost, high-resolution imaging technique using a single-pixel detector.
  • To design a Trumpet neural network for efficient image reconstruction.

Main Methods:

  • A modified FINCH imaging system was constructed with a single-pixel detector for data acquisition.
  • A Trumpet network was designed for end-to-end mapping of 1D sampled data to 2D images.
  • Reconstructed images were compared against conventional single-pixel reconstruction methods.

Main Results:

  • The SP-FINCH method significantly improves image reconstruction quality at lower sampling rates.
  • The proposed method achieves imaging without the need for phase-shifting operations.
  • Numerical simulations and optical experiments validated the method's feasibility and advantages.

Conclusions:

  • SP-FINCH offers a cost-effective alternative to traditional holographic imaging systems.
  • The Trumpet network effectively reconstructs high-quality images from compressed single-pixel data.
  • This approach addresses the limitations of bandwidth and hardware costs in holographic imaging.