Current Optics and Photonics

Optical Society of Korea (한국광학회)
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Image Reconstruction Method for Photonic Integrated Interferometric Imaging Based on Deep Learning

  • Qianchen Xu (School of Mechanical and Aerospace Engineering, Jilin University) ;
  • Weijie Chang (College of Mechanical Engineering and Automation, Fuzhou University) ;
  • Feng Huang (College of Mechanical Engineering and Automation, Fuzhou University) ;
  • Wang Zhang (School of Mechanical and Aerospace Engineering, Jilin University)
  • Received : 2024.04.04
  • Accepted : 2024.07.22
  • Published : 2024.08.25
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Abstract

An image reconstruction algorithm is vital for the image quality of a photonic integrated interferometric imaging (PIII) system. However, image reconstruction algorithms have limitations that always lead to degraded image reconstruction. In this paper, a novel image reconstruction algorithm based on deep learning is proposed. Firstly, the principle of optical signal transmission through the PIII system is investigated. A dataset suitable for image reconstruction of the PIII system is constructed. Key aspects such as model and loss functions are compared and constructed to solve the problem of image blurring and noise influence. By comparing it with other algorithms, the proposed algorithm is verified to have good reconstruction results not only qualitatively but also quantitatively.

Keywords

Acknowledgement

The authors thank the Editor-in-Chief, the reviewers, the School of Mechanical and Aerospace Engineering of Jilin University and College of Mechanical Engineering and Automation of Fuzhou University for this work.

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