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| 低采样关联成像研究现状及发展 |
| Research status and development of low sampling ghost imaging |
| 投稿时间：2022-01-26 |
| DOI：10.3969/j.issn.1005-5630.2022.004.012 |
| 中文关键词: 关联成像 低采样 压缩感知 深度学习 成像质量 |
| 英文关键词:ghost imaging low sampling compressive sensing deep learning image quality |
| 基金项目: |
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| 中文摘要: |
| 关联成像是一种基于光场二阶或高阶关联的主动间接成像技术，具有灵敏度高、抗干扰能力强等特点，在生物医学成像、遥感成像、海洋探测等领域有着重要的利用价值。然而，关联成像过程中对采样数的要求导致采样时间长、成像速度慢。如何在低采样的情况下获得高质量的图像重构依旧是关联成像在实际应用中需要解决的问题之一。详细阐述了关联成像的原理并介绍了近几年低采样关联成像的进展情况，如以深度学习为主的计算关联成像的理论及实验研究成果，并对关联成像的应用进行了总结和展望。 |
| 英文摘要: |
| Ghost imaging is an active indirect imaging technology based on second-order or high-order correlation of light field. It has the characteristics of high sensitivity and strong anti-interference ability, and has important application value in biomedical imaging, remote sensing imaging, ocean detection and other fields. However, the sampling time is long and the imaging speed is slow due to the requirement of sampling number in the process of ghost imaging. Achieving high quality image reconstruction under the condition of low sampling is still one of the problems that need to be solved in the practical application of ghost imaging. In addition to the detailed description of the principle of ghost imaging, this paper introduces the progress of low-sampling ghost imaging in recent years, such as the theoretical and experimental results of deep learning-based computational ghost imaging, and summarizes and prospects the application of ghost imaging. |
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