Laser & Optoelectronics Progress, Volume. 62, Issue 17, 1739009(2025)
Computational Ghost Imaging: From Classical Computation to Deep Learning Driven (Invited)
Fig. 2. Experimental setup and result of entangled two-photon ghost imaging[12]. (a) Experimental setup; (b) experimental result
Fig. 3. Experimental setup and result of ghost imaging based on classical light source[30]. (a) Experimental setup; (b) experimental result
Fig. 4. Experimental setup of ghost imaging based on pseudo-thermal light source[14]
Fig. 7. Framework of computational ghost imaging using self-supervised neural networks[112]
Fig. 12. Framework of large model enhanced computational ghost imaging[124]. (a) Framework of algorithm; (b) network structure
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Yifan Chen, Zhe Sun, Xuelong Li. Computational Ghost Imaging: From Classical Computation to Deep Learning Driven (Invited)[J]. Laser & Optoelectronics Progress, 2025, 62(17): 1739009
Category: AI for Optics
Received: Apr. 15, 2025
Accepted: May. 26, 2025
Published Online: Sep. 12, 2025
The Author Email: Zhe Sun (sunzhe@nwpu.edu.cn), Xuelong Li (li@nwpu.edu.cn)
CSTR:32186.14.LOP251007