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Research on ghost imaging reconstruction by generative adversarial network and Rayleigh fading channel

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Abstract

In previous research on ghost imaging encoding transmission schemes, the influence of real transmission channels on the communication quality was weakened to some extent. Simultaneously, to ensure the imaging quality of the algorithm, it is often performed under full sampling or even supersampling, which undoubtedly requires a long sampling time. This paper proposes a ghost imaging reconstruction method that uses a generative adversarial network and Rayleigh fading channel. By introducing the channel transmission model (Rayleigh fading channel) in real scenes and the generative adversarial neural network model, the image is reconstructed under under-sampling and the imaging time is saved. To further explore how to improve the image transmission quality and reduce the channel interference as much as possible, this scheme provides a new imaging technology for the research of the image transmission field, which has good theoretical significance.

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No datasets were generated or analyzed during the current study.

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Acknowledgements

The authors are indebted to the anonymous referees for their instructive comments and suggestions. We are very thankful for the participants for their support and contribution to this study.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Changshu Institute of Technology, Suzhou, 215500, China

    Hualong Ye & Tongxu Xu

  2. University of Shanghai for Science and Technology, Shanghai, 200093, China

    Daidou Guo

Authors
  1. Hualong Ye
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  2. Tongxu Xu
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  3. Daidou Guo
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Contributions

We are very thankful for the participants for their support and contribution to this study. Ye Hualong designed the study and collected data. Guo Daidou provided the software platform for this experiment. Ye Hualong and Guo Daidou analyzed data and wrote the paper. Ye Hualong and Guo Daidou and Xu Tongxu revised the paper. We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

Corresponding author

Correspondence to Daidou Guo.

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Ye, H., Xu, T. & Guo, D. Research on ghost imaging reconstruction by generative adversarial network and Rayleigh fading channel. Quantum Inf Process 24, 88 (2025). https://doi.org/10.1007/s11128-025-04701-0

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  • DOI: https://doi.org/10.1007/s11128-025-04701-0

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