Songmao Chen, Wei Hao, Xiuqin Su, Zhenyang Zhang, Weihao Xu. Research Progress on Photon Counting Imaging Algorithms[J]. Laser & Optoelectronics Progress, 2021, 58(18): 1811010
- Laser & Optoelectronics Progress
- Vol. 58, Issue 18, 1811010 (2021)
Fig. 1. Principle of the photon counting imaging system
Fig. 2. Schematic diagram of echo and reconstruction results under different conditions. (a) Schematic diagram of single-pixel echo; (b) reconstruction result
Fig. 3. Principles of super-resolution imaging and NLOS imaging. (a) Low-resolution image; (b) super-resolution result; (c) principle of the NLOS imaging
Fig. 4. Schematic diagram of the OPN3DR algorithm[28]
Fig. 5. Reconstruction results of different algorithms under different dwelling times[28]
Fig. 6. Principle of the non-local neural network reconstruction algorithm[36]
Fig. 7. Reconstruction results of different algorithms on long-distance targets[36]
Fig. 8. Target classification results based on multispectral photon counting imaging[40]
Fig. 9. Three-dimensional reconstruction results of multispectral photon counting under different conditions. (a) Reference image; (b)--(d) SBR is 1, PPP is 10; (e)--(g) SBR is 0.1, PPP is 10[46]
Fig. 10. Restoration results of nylon net and the hiding target[7]
Fig. 11. Reconstruction results of long-distance targets for multi-peak signals by different algorithms[52]
Fig. 12. Super-resolution results of target located at 8.2 km[54]
Fig. 13. NLOS imaging results of different algorithms. (a) Physical map; (b) echo-time distribution diagram; (c) FBP algorithm; (d) LCT algorithm; (e) f-k algorithm[64]
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Table 1. Main problems of featured applications
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