Fig. 1. Illustrative example of the multi-depth fast-denoising method

Fig. 2. Depth images and 3D point clouds of s of geometric shapes under different PPP and SBR. (a) Surfaces per pixel on geometric shapes; (b) Depth image estimated by MLE under PPP=11.12, SBR=3.40; (c)-(e) Depth images estimated by the proposed method respectively under PPP=11.12 and SBR=3.40, PPP=2.33 and SBR=0.99, PPP=1.08 and SBR=0.13, and (f)-(i) the corresponding 3D point clouds

Fig. 3. Depth images of the art scene. (a) Reference; (b)-(g) MLE, FDTCP, Rapp, SPISTA, ManiPOP, and proposed method, respectively

Fig. 4. 3D point clouds of the art scene. (a) Reference; (b)-(g) MLE, FDTCP, Rapp, SPISTA, ManiPOP, and proposed method, respectively

Fig. 5. Schematic diagram of long-range single-photon lidar system

Fig. 6. Complex buildings at 1 km. (a) Visible-band image; (b) Histogram of test dataset

Fig. 7. Depth images of complex buildings. (a) Reference; (b)-(g) MLE, FDTCP, Rapp, SPISTA, ManiPOP, and proposed method, respectively

Fig. 8. 3D point clouds of complex buildings. (a) Reference; (b)-(g) MLE, FDTCP, Rapp, SPISTA, ManiPOP, and proposed method, respectively

Table 1. RMSE, SRE and processing time of different methods on the art scene

Table 2. RMSE, SRE and processing time of different methods on complex buildings