Abstract

Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed. It can image the stationary target scene continuously along the scanning direction by taking advantage of the relative movement between the platform and the target scene. Compared to conventional ghost imaging LiDAR that requires multiple speckle patterns staring the target, ghost imaging LiDAR via sparsity constraints using push-broom scanning not only simplifies the imaging system, but also reduces the sampling number. Numerical simulations and experiments have demonstrated its efficiency.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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    [Crossref]
  14. H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
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    [Crossref]
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    [Crossref]
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    [Crossref] [PubMed]

2018 (3)

T. A. Smith and Y. Shih, “Turbulence-free double-slit interferometer,” Phys. Rev. Lett. 120, 063606 (2018).
[Crossref] [PubMed]

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

2017 (1)

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

2016 (4)

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

2015 (2)

W. Yu, X. Yao, X. Liu, L. Li, and G. Zhai, “Compressive moving target tracking with thermal light based on complementary sampling,” Appl. Opt. 54, 4249–4254 (2015).
[Crossref]

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

2014 (3)

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

M. Chen, E. Li, and S. Han, “Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints,” Appl. Opt. 53, 2924–2928 (2014).
[Crossref] [PubMed]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

2013 (3)

C. Zhang, W. Gong, and S. Han, “Improving imaging resolution of shaking targets by fourier-transform ghost diffraction,” Appl. Phys. Lett. 102, 021111 (2013).
[Crossref]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

W. Gong, Z. Bo, E. Li, and S. Han, “Experimental investigation of the quality of ghost imaging via sparsity constraints,” Appl. Opt. 52, 3510–3515 (2013).
[Crossref] [PubMed]

2012 (6)

Y. Shih, “The physics of ghost imaging: nonlocal interference or local intensity fluctuation correlation?” Quantum Inf. Process. 11, 995–1001 (2012).
[Crossref]

B. Sun, S. S. Welsh, M. P. Edgar, J. H. Shapiro, and M. J. Padgett, “Normalized ghost imaging,” Opt. Express 20, 16892–16901 (2012).
[Crossref]

W. Gong and S. Han, “Multiple-input ghost imaging via sparsity constraints,” JOSA A. 29, 1571–1579 (2012).
[Crossref] [PubMed]

J. H. Shapiro and R. W. Boyd, “The physics of ghost imaging,” Quantum Inf. Process. 11, 949–993 (2012).
[Crossref]

W. Gong and S. Han, “Experimental investigation of the quality of lensless super-resolution ghost imaging via sparsity constraints,” Phys. Lett. A. 376, 1519–1522 (2012).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

2011 (1)

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

2010 (1)

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

2009 (1)

O. Katz, Y. Bromberg, and Y. Silberberg, “Compressive ghost imaging,” Appl. Phys. Lett. 95, 131110 (2009).
[Crossref]

2008 (2)

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Trans. Signal Process. 25, 21–30 (2008).
[Crossref]

J. H. Shapiro, “Computational ghost imaging,” Phys. Rev. A. 78, 061802 (2008).
[Crossref]

2007 (1)

A. Stern, Y. Rivenson, and B. Javidi, “Single-shot compressive imaging,” Int. Soc. Opt. Photonics 6778, 67780 (2007).

2006 (2)

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).
[Crossref]

E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006).
[Crossref]

2005 (1)

2004 (1)

J. Cheng and S. Han, “Incoherent coincidence imaging and its applicability in x-ray diffraction,” Phys. Rev. Lett. 92, 093903 (2004).
[Crossref] [PubMed]

Bo, Z.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

W. Gong, Z. Bo, E. Li, and S. Han, “Experimental investigation of the quality of ghost imaging via sparsity constraints,” Appl. Opt. 52, 3510–3515 (2013).
[Crossref] [PubMed]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

Boyd, R. W.

J. H. Shapiro and R. W. Boyd, “The physics of ghost imaging,” Quantum Inf. Process. 11, 949–993 (2012).
[Crossref]

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

Bromberg, Y.

O. Katz, Y. Bromberg, and Y. Silberberg, “Compressive ghost imaging,” Appl. Phys. Lett. 95, 131110 (2009).
[Crossref]

Candès, E. J.

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Trans. Signal Process. 25, 21–30 (2008).
[Crossref]

E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006).
[Crossref]

Chan, K. W. C.

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

Chen, M.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

M. Chen, E. Li, and S. Han, “Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints,” Appl. Opt. 53, 2924–2928 (2014).
[Crossref] [PubMed]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

Chen, X.-H.

Cheng, J.

J. Cheng and S. Han, “Incoherent coincidence imaging and its applicability in x-ray diffraction,” Phys. Rev. Lett. 92, 093903 (2004).
[Crossref] [PubMed]

Council, N. R.

N. R. Council, Laser Radar: Progress and Opportunities in Active Electro-Optical Sensing (National Academies, 2014).

Deng, C.

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

Donoho, D. L.

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).
[Crossref]

Du, G.

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Edgar, M. P.

Elachi, C.

C. Elachi, Spaceborne radar remote sensing: applications and techniques (IEEE, 1988).

Ferri, F.

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

Gao, X.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

Gatti, A.

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

Gong, W.

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

C. Zhang, W. Gong, and S. Han, “Improving imaging resolution of shaking targets by fourier-transform ghost diffraction,” Appl. Phys. Lett. 102, 021111 (2013).
[Crossref]

W. Gong, Z. Bo, E. Li, and S. Han, “Experimental investigation of the quality of ghost imaging via sparsity constraints,” Appl. Opt. 52, 3510–3515 (2013).
[Crossref] [PubMed]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

W. Gong and S. Han, “Experimental investigation of the quality of lensless super-resolution ghost imaging via sparsity constraints,” Phys. Lett. A. 376, 1519–1522 (2012).
[Crossref]

W. Gong and S. Han, “Multiple-input ghost imaging via sparsity constraints,” JOSA A. 29, 1571–1579 (2012).
[Crossref] [PubMed]

Han, S.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

M. Chen, E. Li, and S. Han, “Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints,” Appl. Opt. 53, 2924–2928 (2014).
[Crossref] [PubMed]

C. Zhang, W. Gong, and S. Han, “Improving imaging resolution of shaking targets by fourier-transform ghost diffraction,” Appl. Phys. Lett. 102, 021111 (2013).
[Crossref]

W. Gong, Z. Bo, E. Li, and S. Han, “Experimental investigation of the quality of ghost imaging via sparsity constraints,” Appl. Opt. 52, 3510–3515 (2013).
[Crossref] [PubMed]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

W. Gong and S. Han, “Multiple-input ghost imaging via sparsity constraints,” JOSA A. 29, 1571–1579 (2012).
[Crossref] [PubMed]

W. Gong and S. Han, “Experimental investigation of the quality of lensless super-resolution ghost imaging via sparsity constraints,” Phys. Lett. A. 376, 1519–1522 (2012).
[Crossref]

J. Cheng and S. Han, “Incoherent coincidence imaging and its applicability in x-ray diffraction,” Phys. Rev. Lett. 92, 093903 (2004).
[Crossref] [PubMed]

Z. Liu, X. Shen, H. Liu, and S. Han, “Lensless wiener-khinchin telescope based on high-order spatial autocorrelation of light field,” arXiv preprint arXiv:1804.01270 (2018).

Howell, J. C.

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

Javidi, B.

A. Stern, Y. Rivenson, and B. Javidi, “Single-shot compressive imaging,” Int. Soc. Opt. Photonics 6778, 67780 (2007).

Katz, O.

O. Katz, Y. Bromberg, and Y. Silberberg, “Compressive ghost imaging,” Appl. Phys. Lett. 95, 131110 (2009).
[Crossref]

Lan, R.

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

Li, E.

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

M. Chen, E. Li, and S. Han, “Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints,” Appl. Opt. 53, 2924–2928 (2014).
[Crossref] [PubMed]

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

W. Gong, Z. Bo, E. Li, and S. Han, “Experimental investigation of the quality of ghost imaging via sparsity constraints,” Appl. Opt. 52, 3510–3515 (2013).
[Crossref] [PubMed]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

Li, L.

Li, W.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

Li, X.

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

Liu, H.

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

Z. Liu, X. Shen, H. Liu, and S. Han, “Lensless wiener-khinchin telescope based on high-order spatial autocorrelation of light field,” arXiv preprint arXiv:1804.01270 (2018).

Liu, X.

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

W. Yu, X. Yao, X. Liu, L. Li, and G. Zhai, “Compressive moving target tracking with thermal light based on complementary sampling,” Appl. Opt. 54, 4249–4254 (2015).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Liu, Z.

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

Z. Liu, X. Shen, H. Liu, and S. Han, “Lensless wiener-khinchin telescope based on high-order spatial autocorrelation of light field,” arXiv preprint arXiv:1804.01270 (2018).

Lu, R.

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Lugiato, L.

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

Magatti, D.

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

Mei, X.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

Padgett, M. J.

Pan, L.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

Qiu, P.

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

Rivenson, Y.

A. Stern, Y. Rivenson, and B. Javidi, “Single-shot compressive imaging,” Int. Soc. Opt. Photonics 6778, 67780 (2007).

Romberg, J.

E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006).
[Crossref]

Shapiro, J. H.

J. H. Shapiro and R. W. Boyd, “The physics of ghost imaging,” Quantum Inf. Process. 11, 949–993 (2012).
[Crossref]

B. Sun, S. S. Welsh, M. P. Edgar, J. H. Shapiro, and M. J. Padgett, “Normalized ghost imaging,” Opt. Express 20, 16892–16901 (2012).
[Crossref]

J. H. Shapiro, “Computational ghost imaging,” Phys. Rev. A. 78, 061802 (2008).
[Crossref]

Shen, X.

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

Z. Liu, X. Shen, H. Liu, and S. Han, “Lensless wiener-khinchin telescope based on high-order spatial autocorrelation of light field,” arXiv preprint arXiv:1804.01270 (2018).

Shih, Y.

T. A. Smith and Y. Shih, “Turbulence-free double-slit interferometer,” Phys. Rev. Lett. 120, 063606 (2018).
[Crossref] [PubMed]

Y. Shih, “The physics of ghost imaging: nonlocal interference or local intensity fluctuation correlation?” Quantum Inf. Process. 11, 995–1001 (2012).
[Crossref]

Silberberg, Y.

O. Katz, Y. Bromberg, and Y. Silberberg, “Compressive ghost imaging,” Appl. Phys. Lett. 95, 131110 (2009).
[Crossref]

Smith, T. A.

T. A. Smith and Y. Shih, “Turbulence-free double-slit interferometer,” Phys. Rev. Lett. 120, 063606 (2018).
[Crossref] [PubMed]

Stern, A.

A. Stern, Y. Rivenson, and B. Javidi, “Single-shot compressive imaging,” Int. Soc. Opt. Photonics 6778, 67780 (2007).

Sun, B.

Tan, S.

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

Tao, T.

E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006).
[Crossref]

Wakin, M. B.

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Trans. Signal Process. 25, 21–30 (2008).
[Crossref]

Wang, C.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Wang, H.

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

Wang, P.

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

Welsh, S. S.

Wu, J.

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

Wu, L.

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

Wu, L.-A.

Xiao, T.

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Xie, H.

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Xu, W.

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

Xu, X.

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

Yao, X.

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

W. Yu, X. Yao, X. Liu, L. Li, and G. Zhai, “Compressive moving target tracking with thermal light based on complementary sampling,” Appl. Opt. 54, 4249–4254 (2015).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Yu, H.

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Yu, W.

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

W. Yu, X. Yao, X. Liu, L. Li, and G. Zhai, “Compressive moving target tracking with thermal light based on complementary sampling,” Appl. Opt. 54, 4249–4254 (2015).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Zerom, P.

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

Zhai, G.

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

W. Yu, X. Yao, X. Liu, L. Li, and G. Zhai, “Compressive moving target tracking with thermal light based on complementary sampling,” Appl. Opt. 54, 4249–4254 (2015).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Zhai, Y.-H.

Zhang, C.

C. Zhang, W. Gong, and S. Han, “Improving imaging resolution of shaking targets by fourier-transform ghost diffraction,” Appl. Phys. Lett. 102, 021111 (2013).
[Crossref]

Zhang, D.

Zhao, C.

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

Zhao, Q.

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Zhu, D.

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

Acta Phys. Sin. (1)

P. Wang, X. Yao, X. Liu, W. Yu, P. Qiu, and G. Zhai, “Moving target compressive imaging based on improved row scanning measurement matrix,” Acta Phys. Sin. 66, 014201 (2017).

Appl. Opt. (3)

Appl. Phys. Lett. (4)

E. Li, Z. Bo, M. Chen, W. Gong, and S. Han, “Ghost imaging of a moving target with an unknown constant speed,” Appl. Phys. Lett. 104, 251120 (2014).
[Crossref]

C. Zhang, W. Gong, and S. Han, “Improving imaging resolution of shaking targets by fourier-transform ghost diffraction,” Appl. Phys. Lett. 102, 021111 (2013).
[Crossref]

C. Zhao, W. Gong, M. Chen, E. Li, H. Wang, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints,” Appl. Phys. Lett. 101, 141123 (2012).
[Crossref]

O. Katz, Y. Bromberg, and Y. Silberberg, “Compressive ghost imaging,” Appl. Phys. Lett. 95, 131110 (2009).
[Crossref]

Appl. Sci. (1)

S. Han, H. Yu, X. Shen, H. Liu, W. Gong, and Z. Liu, “A review of ghost imaging via sparsity constraints,” Appl. Sci. 8, 1379 (2018).
[Crossref]

IEEE Trans. Inf. Theory (2)

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).
[Crossref]

E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52, 489–509 (2006).
[Crossref]

IEEE Trans. Signal Process. (1)

E. J. Candès and M. B. Wakin, “An introduction to compressive sampling,” IEEE Trans. Signal Process. 25, 21–30 (2008).
[Crossref]

Int. Soc. Opt. Photonics (1)

A. Stern, Y. Rivenson, and B. Javidi, “Single-shot compressive imaging,” Int. Soc. Opt. Photonics 6778, 67780 (2007).

JOSA A. (1)

W. Gong and S. Han, “Multiple-input ghost imaging via sparsity constraints,” JOSA A. 29, 1571–1579 (2012).
[Crossref] [PubMed]

Opt. Commun. (1)

W. Yu, X. Yao, X. Liu, R. Lan, L. Wu, G. Zhai, and Q. Zhao, “Compressive microscopic imaging with positive–negative light modulation,” Opt. Commun. 371, 105–111 (2016).
[Crossref]

Opt. Express (1)

Opt. Lett. (1)

Opt. Photonics J. (1)

M. Chen, E. Li, W. Gong, Z. Bo, X. Xu, C. Zhao, X. Shen, W. Xu, and S. Han, “Ghost imaging lidar via sparsity constraints in real atmosphere,” Opt. Photonics J. 3, 83 (2013).
[Crossref]

Photonics Res. (1)

X. Li, C. Deng, M. Chen, W. Gong, and S. Han, “Ghost imaging for an axially moving target with an unknown constant speed,” Photonics Res. 3, 153–157 (2015).
[Crossref]

Phys. Lett. A (1)

W. Yu, X. Liu, X. Yao, C. Wang, G. Zhai, and Q. Zhao, “Single-photon compressive imaging with some performance benefits over raster scanning,” Phys. Lett. A 378, 3406–3411 (2014).
[Crossref]

Phys. Lett. A. (1)

W. Gong and S. Han, “Experimental investigation of the quality of lensless super-resolution ghost imaging via sparsity constraints,” Phys. Lett. A. 376, 1519–1522 (2012).
[Crossref]

Phys. Rev. A. (2)

P. Zerom, K. W. C. Chan, J. C. Howell, and R. W. Boyd, “Entangled-photon compressive ghost imaging,” Phys. Rev. A. 84, 061804 (2011).
[Crossref]

J. H. Shapiro, “Computational ghost imaging,” Phys. Rev. A. 78, 061802 (2008).
[Crossref]

Phys. Rev. Lett. (4)

T. A. Smith and Y. Shih, “Turbulence-free double-slit interferometer,” Phys. Rev. Lett. 120, 063606 (2018).
[Crossref] [PubMed]

H. Yu, R. Lu, S. Han, H. Xie, G. Du, T. Xiao, and D. Zhu, “Fourier-transform ghost imaging with hard x rays,” Phys. Rev. Lett. 117, 113901 (2016).
[Crossref] [PubMed]

F. Ferri, D. Magatti, L. Lugiato, and A. Gatti, “Differential ghost imaging,” Phys. Rev. Lett. 104, 253603 (2010).
[Crossref] [PubMed]

J. Cheng and S. Han, “Incoherent coincidence imaging and its applicability in x-ray diffraction,” Phys. Rev. Lett. 92, 093903 (2004).
[Crossref] [PubMed]

Quantum Inf. Process. (2)

Y. Shih, “The physics of ghost imaging: nonlocal interference or local intensity fluctuation correlation?” Quantum Inf. Process. 11, 995–1001 (2012).
[Crossref]

J. H. Shapiro and R. W. Boyd, “The physics of ghost imaging,” Quantum Inf. Process. 11, 949–993 (2012).
[Crossref]

Remote Sens. (1)

C. Wang, X. Mei, L. Pan, P. Wang, W. Li, X. Gao, Z. Bo, M. Chen, W. Gong, and S. Han, “Airborne near infrared three-dimensional ghost imaging lidar via sparsity constraint,” Remote Sens. 10, 732 (2018).
[Crossref]

Sci. Reports (2)

W. Gong, C. Zhao, H. Yu, M. Chen, W. Xu, and S. Han, “Three-dimensional ghost imaging lidar via sparsity constraint,” Sci. Reports 6, 26133 (2016).
[Crossref]

Z. Liu, S. Tan, J. Wu, E. Li, X. Shen, and S. Han, “Spectral camera based on ghost imaging via sparsity constraints,” Sci. Reports 6, 25718 (2016).
[Crossref]

Other (3)

Z. Liu, X. Shen, H. Liu, and S. Han, “Lensless wiener-khinchin telescope based on high-order spatial autocorrelation of light field,” arXiv preprint arXiv:1804.01270 (2018).

C. Elachi, Spaceborne radar remote sensing: applications and techniques (IEEE, 1988).

N. R. Council, Laser Radar: Progress and Opportunities in Active Electro-Optical Sensing (National Academies, 2014).

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Figures (6)

Fig. 1
Fig. 1 Schematic of the push-broom GISC LiDAR system. (a) Schematic diagram of push-broom GISC LiDAR system. (b) Two emission schematics. (c) The geometry correspondence details.
Fig. 2
Fig. 2 Experimental setup of push-broom GISC system. A halogen lamp emitted the light uniformly illuminated onto the DMD, then the speckle pattern reflected by the DMD was imaged onto the target scene, the reflected light of the speckle pattern projected onto target was imaged on CCD.
Fig. 3
Fig. 3 Simulated results of method-1 and method-2. (a1) Binary target alphabet “SIOM”, (c1) Gray scale target logo pattern, (e1) Gray scale target “house”. Columns (2)–(7) correspond to sampling rate η are 0.25, 0.5, 0.625, 0.75, 0.875 and 1, respectively. (a2)–(a7), (c2)–(c7) and (e2)–(e7) are the simulated results of method-1. (b2)–(b7), (d2)–(d7) and (f2)–(f7) are the simulated results of method-2.
Fig. 4
Fig. 4 Experimental results of method-1 and method-2. (a1) The printed photo of binary target alphabet “SIOM”, (c1) the printed photo of the gray scale target logo pattern, (e1) the printed photo of the gray scale target “house”. Columns (2)–(7) correspond to sampling rate η are 0.25, 0.5, 0.625, 0.75, 0.875 and 1, respectively. (a2)–(a7), (c2)–(c7) and (e2)–(e7) are the experimental results of method-1. (b2)–(b7), (d2)–(d7) and (f2)–(f7) are the experimental results of method-2.
Fig. 5
Fig. 5 PSNR curves with respect to sampling rate η. The blue and mauve dashed curves signify the fitted PSNR of the target scene reconstructed by method-1 and method-2, respectively. The scattered points of corresponding colors are the PSNR before fitting. (a) PSNR curves of simulated results of the alphabet “SIOM”. (b) PSNR curves of simulated results of the logo pattern. (c) PSNR curves of simulated results of the “house”. (d) PSNR curves of experimental results of the alphabet “SIOM”. (e) PSNR curves of experimental results of the logo pattern. (f) PSNR curves of experimental results of the “house”.
Fig. 6
Fig. 6 The simulated result of continuous the Great Wall image at the η = 0.625. (a) The original image. (b) The simulated result of method-1. (c) The simulated result of method-2.

Equations (12)

Equations on this page are rendered with MathJax. Learn more.

Y i = A i X i .
A i = [ I 1 ( i ) T I j ( i + j 1 ) T I m ( i + m 1 ) T ] ,
Y = AX .
Y = [ Y 1 Y i Y q ] ,
X = [ X 1 X i X q ] .
A = [ A 1 A i A q ] .
Y = A X ,
X * = arg min X Y AX 2 2 + λ TV ( X ) 1 ,
TV ( X ) 1 = 1 i q n n , i k n , k N ( x i + 1 x i ) 2 + ( x i + n x i ) 2 ,
X * = arg min X Y A X 2 2 + λ TV ( X ) 1 ,
TV ( X ) 1 = 1 i n 1 , 1 j q 1 ( x i + 1 , j x i , j ) 2 + ( x i , j + 1 x i , j ) 2 ,
PSNR = 10 × log 10 ( ( 2 n 1 ) 2 MSE ) ,

Metrics