Infrared and Laser Engineering, Volume. 51, Issue 8, 20220305(2022)
Progress and prospect of non-line-of-sight imaging （invited）
Figures & Tables(23)
Fig. 1. Schematic diagrams of line-of-sight imaging and non-line-of-sight imaging. (a) Line-of-sight imaging; (b) Optical path is blocked; (c) None-line-of-sight imaging
Fig. 2. Non-line-of-sight imaging using speckle correlations[32]. (a) Setup; (b) Original object; (c) Camera image; (d) Reconstruction
Fig. 3. Spatial coherence measurement[36]. (a) Measurement setup; (b) Phase map
Fig. 4. Non-line-of-sight imaging from shadow[11]. (a) Experimental scenario; (b) Scene setup; (c) Camera image; (d) Selected views of true scene; (e) Selected views of recovered scene
Fig. 6. Schematic diagram of transient imaging based on time-of-flight[14]. (a) Transient imaging system; (b) Transient image
Fig. 7. Transient imaging reconstruction algorithm, hardware system and imaging performance comparison based on time-of-flight
Fig. 8. Reconstruction using back-projection algrothim[14]. (a) Object; (b) Heatmap; (c) Reconstruction
Fig. 10. Confocal non-line-of-sight imaging based on the light-cine transform[1]. (a) Confocal imaging; (b) Temporal transient response; (c) Transient imaging; (d) Reconstruction
Fig. 11. Reconstruction of NLOS scene with partial occlusions[91]. (a) Illustration of visibility in NLOS scene; (b) Object; (c) Reconstruction of linear result; (d) Reconstruction of nonlinear result
Fig. 13. Non-line-of-sight imaging using phasor-field virtual wave optics[16]. (a) Imaging framework; (b) Imaging princple; (c) Reconstruction
Fig. 15. Comparison of reconstructions based on non-confocal images
Fig. 16. Comparison of reconstructions using various algorithms at different exposure times
Fig. 17. Comparison of reconstructions using various algorithms at different temporal resolutions
Fig. 18. Comparison of reconstructions of objects with different surface albedo using various algorithms
Fig. 19. Comparison of reconstructions single-shot non-confocal images using typical algorithms
Table 1. Comparison of time-of-flight based imaging schemes
View tableView in ArticleTable 1. Comparison of time-of-flight based imaging schemes
Imaging scheme Related work Detector Source Time resolution Pixel size Wavelength/nm Frequency/MHz Pulsed width Pulsed laser & streak camera [Velten et al. 2012] 2 ps 1280×1024 795 75 50 fs [Gupta et al. 2012] 2 ps 1280×1024 795 75 50 fs Pulsed laser & SPAD [Gariepy et al. 2015] 45.5 ps 32×32 800 67 10 fs [O’Toole et al. 2018] 60 ps 1×1 670 10 30.6 ps [Lindell et al. 2019] 70 ps 1×1 532 10 35 ps [Liu et al. 2019] 67 ps 1×1 532 10 35 ps Modulated source & AMCW camera [Heide et al. 2014] 1 ns 160×120 650 - 2-3 ns [Kadambi et al. 2013] 100 ps 160×120 — 50 -
Table 2. Performance comparison of NLOS algorithms based on time-of-flight
View tableView in ArticleTable 2. Performance comparison of NLOS algorithms based on time-of-flight
Algorithm Principle Related work Resolution Computational complexity Scenario requirement Note: green, yellow and red represent the high, medium and low performance respectively. Back projection Geometrical optics [Velten et al. 2012] Low $O({N^5})$ Lambertian object Linear reconstruction Geometrical optics [O’Toole et al. 2018] Medium $O({N^3}\log N)$ Unlimited [Young et al. 2020] High $O({N^3}\log N)$ Lambertian object Nonlinear reconstruction Geometrical optics [Heide et al. 2019] Medium $O({N^5})$ Lambertian object Analysis-by-synthesis Geometrical optics [Tsai et al. 2019] High — Unlimited [Xin et al. 2019] Low — Unlimited Wave based reconstruction Wave optics [Lindell et al. 2019] High $O({N^3}\log N)$ Unlimited [Liu et al. 2019] High $O({N^5})$ Non-mirror object Deep learning Geometrical optics [Chen et al. 2020] High Cost of training Unlimited
Table 3. Comparison of reconstruction time based on confocal images (Unit: s)
View tableView in ArticleTable 3. Comparison of reconstruction time based on confocal images (Unit: s)
Back-projection LCT D-LCT f-k Phasor field T 1.22 1.34 7.80 1.89 1.35 Teaser 4.41 4.48 42.94 8.53 4.93 Outdoor 4.13 4.42 52.00 7.03 4.66
Table 4. Performance comparison of NLOS imaging methods
View tableView in ArticleTable 4. Performance comparison of NLOS imaging methods
Imaging method Equipment Resolution Prior Imaging ability Dimension Ambient light Note: green, yellow and red represent the high, medium and low performance respectively. Time-of-flight based method Pulsed laser & streak camera High Not required Macroscopic complex object 3D Robust Pulsed laser &SPAD Modulated source & AMCW camera Coherence-based method Speckle-based: passive source & traditional camera High Part of methods required Microscopic simple object 2D/3D Sensitive Spatial-coherence-based: passive source & interferometer Low Not required Macroscopic simple object Intensity-based method Passive source & traditional camera Medium Required Macroscopic simple object 2D Sensitive
Tools
Get Citation
Copy Citation Text
Xin Jin, Dongyu Du, Rujia Deng. Progress and prospect of non-line-of-sight imaging （invited）[J]. Infrared and Laser Engineering, 2022, 51(8): 20220305
Paper Information
Category: Special issue——Scattering imaging and non-line-of-sight imaging
Received: May. 5, 2022
Accepted: Jun. 23, 2022
Published Online: Jan. 9, 2023
The Author Email:
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20