Rui Wang, Bo Liu, Zhikang Li, Zhen Chen, Hao Yi. Adaptive spatial-temporal correlation depth estimation of photon-counting lidar[J]. Infrared and Laser Engineering, 2023, 52(5): 20220682

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- Infrared and Laser Engineering
- Vol. 52, Issue 5, 20220682 (2023)

Fig. 1. Echo photon counts model

Fig. 2. (a) Overall flow chart; (b) Adaptive selection of the time window

Fig. 3. Neighborhood data set (3×3). (a) The time interval of the maximum counts of each pixel in the neighborhood; (b) The time interval of the neighborhood data set and the corresponding photon counts in the original histogram

Fig. 4. (a) The original terrain; (b) Photon statistical histogram (M =10000 and 2 MHz noise)

Fig. 5. Comparison of reconstruction results of different algorithms at different noise intensities. (a) 0.2 MHz noise, 14.3 PPP; (b) 2 MHz noise, 13.8 PPP; (c) 3.5 MHz noise, 14.6 PPP; (d) 6 MHz noise, 14.1 PPP

Fig. 6. (a) Block diagram of photon counting lidar system; (b) Physical picture of device

Fig. 7. (a) Visible band image; (b) Reconstructed truth depth image of target

Fig. 8. Reconstruction results of target. (a) 0.23 MHz noise, 21.6 PPP; (b) 1.21 MHz noise, 21.2 PPP; (c) 2.17 MHz noise, 21.8 PPP; (d) 3.02 MHz noise, 22.5 PPP; (e) 5.08 MHz noise, 23.9 PPP
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Table 1. The main parameters of the simulated echo data

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