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Laser & Optoelectronics Progress, Volume. 61, Issue 10, 1011010(2024)

Ghost Imaging Quality Optimization Based on Deep Convolutional Generative Adversarial Networks

Maoxin Hou1、* and Zhaotao Liu2
Author Affiliations
  • 1Collective Intelligence & Collaboration Laboratory, Zhongbing Intelligent Innovation Research Institute Limited Liabilty Company, Beijing 100072, China
  • 2China North Vehicle Research Institute, Beijing 100072, China
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    Article index updated: Sep. 10, 2025

    The article is cited by 1 article(s) CLP online library. (Some content might be in Chinese.)
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    Maoxin Hou, Zhaotao Liu. Ghost Imaging Quality Optimization Based on Deep Convolutional Generative Adversarial Networks[J]. Laser & Optoelectronics Progress, 2024, 61(10): 1011010

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    Paper Information

    Category: Imaging Systems

    Received: Nov. 2, 2023

    Accepted: Dec. 26, 2023

    Published Online: Apr. 29, 2024

    The Author Email: Maoxin Hou (wang17835132895@163.com)

    DOI:10.3788/LOP232421

    CSTR:32186.14.LOP232421

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology