Abstract

This paper presents a time-of-flight (ToF) measurement method for use in foggy weather. The depth measured by a ToF camera is greatly distorted in fog because the light scattered in the fog reaches the camera much faster than the target reflection. We reveal that the multi-frequency measurements contain a cue whether two arbitrary pixels have the same depth. After clustering the same depth pixels using this cue, the original depth can be recovered for each cluster by line fitting in the Cartesian coordinate frame. The effectiveness of this method is evaluated numerically via real-world and road-scale experiments.

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

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References

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  5. J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.
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  7. I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
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    [Crossref]
  10. A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
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  13. M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.
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    [Crossref]
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    [Crossref]
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  22. A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).
  23. D. Jimenez, D. Pizarro, M. Mazo, and S. Palazuelos, “Modelling and correction of multipath interference in time of flight cameras,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 893–900.
  24. F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
    [Crossref] [PubMed]
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  26. D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.
  27. H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
    [Crossref] [PubMed]
  28. N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.
  29. A. Kadambi, J. Schiel, and R. Raskar, “Macroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 893–902.
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    [Crossref]
  31. K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
    [PubMed]
  32. M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
    [Crossref]

2017 (2)

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

2015 (6)

H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
[Crossref] [PubMed]

S. Lee and H. Shim, “Skewed stereo time-of-flight camera for translucent object imaging,” Image Vis. Comput. 43, 27–38 (2015).
[Crossref]

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

2014 (2)

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
[Crossref] [PubMed]

2013 (3)

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

2012 (3)

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

K. Nishino, L. Kratz, and S. Lombardi, “Baysian defogging,” Int. J. Comput. Vis. 98, 263–278 (2012).
[Crossref]

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

2011 (2)

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2341–2353 (2011).
[Crossref]

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

1978 (1)

Abramson, N.

Achar, S.

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

Aoto, T.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

Avidan, S.

D. Berman, T. Treibitz, and S. Avidan, “Non-local image dehazing,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 1674–1682.

Awatsuji, Y.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Barsi, C.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

Bartels, J.

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

Bawendi, M.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Bawendi, M. G.

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Benedetti, A.

A. Kirmani, A. Benedetti, and P. A. Chou, “Spumic: Simultaneous phase unwrapping and multipath interference cancellation in time-of-flight cameras using spectral methods,” in Proceedings of IEEE International Conference on Multimedia and Expo, (IEEE, 2013), pp. 1–6.

Berman, D.

D. Berman, T. Treibitz, and S. Avidan, “Non-local image dehazing,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 1674–1682.

Bhandari, A.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

Bing Kang, S.

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

Chou, P. A.

A. Kirmani, A. Benedetti, and P. A. Chou, “Spumic: Simultaneous phase unwrapping and multipath interference cancellation in time-of-flight cameras using spectral methods,” in Proceedings of IEEE International Conference on Multimedia and Expo, (IEEE, 2013), pp. 1–6.

Cree, M. J.

A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).

Dai, Q.

H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
[Crossref] [PubMed]

J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Fourier analysis on transient imaging with a multifrequency time-of-flight camera,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2014), pp. 3230–3237.

Davis, J.

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

Diamond, S.

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Dorrington, A.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

Dorrington, A. A.

A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).

Durand, F.

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

Freedman, D.

D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.

Fuchs, S.

S. Fuchs, “Multipath interference compensation in time-of-flight camera images,” in International Conference on Pattern Recognition, (IEEE, 2010), pp. 3583–3586.

Funatomi, T.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Gkioulekas, I.

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

Godbaz, J. P.

A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).

Gregson, J.

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

Gupta, M.

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

Gupta, O.

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Gutierrez, D.

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

He, K.

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2341–2353 (2011).
[Crossref]

Heide, F.

F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
[Crossref] [PubMed]

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Heidrich, W.

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
[Crossref] [PubMed]

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

Hullin, M. B.

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
[Crossref] [PubMed]

F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
[Crossref] [PubMed]

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Fourier analysis on transient imaging with a multifrequency time-of-flight camera,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2014), pp. 3230–3237.

Hutchison, T.

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

Izadi, S.

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

Jarabo, A.

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Jimenez, D.

D. Jimenez, D. Pizarro, M. Mazo, and S. Palazuelos, “Modelling and correction of multipath interference in time of flight cameras,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 893–900.

Joshi, C.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Kadambi, A.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

A. Kadambi, J. Schiel, and R. Raskar, “Macroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 893–902.

Kakue, T.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Kirmani, A.

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

A. Kirmani, A. Benedetti, and P. A. Chou, “Spumic: Simultaneous phase unwrapping and multipath interference cancellation in time-of-flight cameras using spectral methods,” in Proceedings of IEEE International Conference on Multimedia and Expo, (IEEE, 2013), pp. 1–6.

Kitano, K.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

Klein, J.

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

Klein, R.

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

Kolb, A.

Kratz, L.

K. Nishino, L. Kratz, and S. Lombardi, “Baysian defogging,” Int. J. Comput. Vis. 98, 263–278 (2012).
[Crossref]

Krupka, E.

D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.

Kubo, H.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Kubota, T.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Kutulakos, K. N.

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

Lawson, E.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Lee, S.

S. Lee and H. Shim, “Skewed stereo time-of-flight camera for translucent object imaging,” Image Vis. Comput. 43, 27–38 (2015).
[Crossref]

Leichter, I.

D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.

Levin, A.

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

Lin, J.

H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
[Crossref] [PubMed]

J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Fourier analysis on transient imaging with a multifrequency time-of-flight camera,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2014), pp. 3230–3237.

Lindell, D.

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Liu, Y.

H. Qiao, J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Resolving transient time profile in tof imaging via log-sum sparse regularization,” Opt. Lett. 40, 918–921 (2015).
[Crossref] [PubMed]

J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Fourier analysis on transient imaging with a multifrequency time-of-flight camera,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2014), pp. 3230–3237.

Lombardi, S.

K. Nishino, L. Kratz, and S. Lombardi, “Baysian defogging,” Int. J. Comput. Vis. 98, 263–278 (2012).
[Crossref]

Marco, J.

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

Martin, J.

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

Masia, B.

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Matsushita, Y.

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Mazo, M.

D. Jimenez, D. Pizarro, M. Mazo, and S. Palazuelos, “Modelling and correction of multipath interference in time of flight cameras,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 893–900.

Mukaigawa, Y.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Naik, N.

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

Narasimhan, S. G.

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

Nayar, S. K.

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

Nishino, K.

K. Nishino, L. Kratz, and S. Lombardi, “Baysian defogging,” Int. J. Comput. Vis. 98, 263–278 (2012).
[Crossref]

Nishio, K.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

O’Toole, M.

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Okamoto, T.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

Palazuelos, S.

D. Jimenez, D. Pizarro, M. Mazo, and S. Palazuelos, “Modelling and correction of multipath interference in time of flight cameras,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 893–900.

Payne, A. D.

A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).

Peters, C.

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

Pizarro, D.

D. Jimenez, D. Pizarro, M. Mazo, and S. Palazuelos, “Modelling and correction of multipath interference in time of flight cameras,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2012), pp. 893–900.

Qiao, H.

Raskar, R.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

G. Satat, M. Tancik, and R. Raskar, “Towards photography through realistic fog,” in Proceedings of IEEE International Conference on Computational Photography, (IEEE, 2018), pp. 1–10.

A. Kadambi, J. Schiel, and R. Raskar, “Macroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 893–902.

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

Rhemann, C.

N. Naik, A. Kadambi, C. Rhemann, S. Izadi, R. Raskar, and S. Bing Kang, “A light transport model for mitigating multipath interference in time-of-flight sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2015), pp. 73–81.

Sankaranarayanan, A. C.

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

Satat, G.

G. Satat, M. Tancik, and R. Raskar, “Towards photography through realistic fog,” in Proceedings of IEEE International Conference on Computational Photography, (IEEE, 2018), pp. 1–10.

Schiel, J.

A. Kadambi, J. Schiel, and R. Raskar, “Macroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 893–902.

Schmidt, M.

D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.

Shim, H.

S. Lee and H. Shim, “Skewed stereo time-of-flight camera for translucent object imaging,” Image Vis. Comput. 43, 27–38 (2015).
[Crossref]

Smolin, Y.

D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt, “SRA: fast removal of general multipath for ToF sensors,” in Proceedings of European Conference on Computer Vision, (Springer, 2014), pp. 1–15.

Streeter, L.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

Streeter, L. V.

A. A. Dorrington, J. P. Godbaz, M. J. Cree, A. D. Payne, and L. V. Streeter, “Separating true range measurements from multi-path and scattering interference in commercial range cameras,” in Proceedings of SPIE7864, (SPIE, 2011).

Sun, J.

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2341–2353 (2011).
[Crossref]

Tahara, T.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Tanaka, K.

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Tancik, M.

G. Satat, M. Tancik, and R. Raskar, “Towards photography through realistic fog,” in Proceedings of IEEE International Conference on Computational Photography, (IEEE, 2018), pp. 1–10.

Tang, X.

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2341–2353 (2011).
[Crossref]

Tosa, K.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Treibitz, T.

D. Berman, T. Treibitz, and S. Avidan, “Non-local image dehazing,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 1674–1682.

Ura, S.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Veeraraghavan, A.

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Velten, A.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Wang, J.

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

Wetzstein, G.

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Whittaker, W.

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

Whyte, R.

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

Willwacher, T.

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Wu, D.

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

Xiao, L.

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

F. Heide, L. Xiao, A. Kolb, M. B. Hullin, and W. Heidrich, “Imaging in scattering media using correlation image sensors and sparse convolutional coding,” Opt. Express 22, 26338–50 (2014).
[Crossref] [PubMed]

Yagi, Y.

K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, “Material classification from time-of-flight distortions,” IEEE Trans. Pattern Anal. Mach. Intell. (2018).
[PubMed]

Yuasa, J.

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

Zang, K.

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

Zickler, T.

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

ACM Trans. Graph. (8)

M. O’Toole, S. Achar, S. G. Narasimhan, and K. N. Kutulakos, “Homogeneous codes for energy-efficient illumination and imaging,” ACM Trans. Graph. 34, 35 (2015).

I. Gkioulekas, A. Levin, F. Durand, and T. Zickler, “Micron-scale light transport decomposition using interferometry,” ACM Trans. Graph. 34, 37 (2015).
[Crossref]

A. Velten, D. Wu, A. Jarabo, B. Masia, C. Barsi, C. Joshi, E. Lawson, M. Bawendi, D. Gutierrez, and R. Raskar, “Femto-photography: Capturing and visualizing the propagation of light,” ACM Trans. Graph. 32, 44 (2013).
[Crossref]

F. Heide, M. B. Hullin, J. Gregson, and W. Heidrich, “Low-budget transient imaging using photonic mixer devices,” ACM Trans. Graph. 32, 45 (2013).
[Crossref]

C. Peters, J. Klein, M. B. Hullin, and R. Klein, “Solving trigonometric moment problems for fast transient imaging,” ACM Trans. Graph. 34, 220 (2015).
[Crossref]

A. Kadambi, R. Whyte, A. Bhandari, L. Streeter, C. Barsi, A. Dorrington, and R. Raskar, “Coded time of flight cameras: Sparse deconvolution to address multipath interference and recover time profiles,” ACM Trans. Graph. 32, 1–10 (2013).
[Crossref]

M. O’Toole, F. Heide, L. Xiao, M. B. Hullin, W. Heidrich, and K. N. Kutulakos, “Temporal frequency probing for 5d transient analysis of global light transport,” ACM Trans. Graph. 33, 1–11 (2014).
[Crossref]

M. Gupta, S. K. Nayar, M. B. Hullin, and J. Martin, “Phasor imaging: a generalization of correlation-based time-of-flight imaging,” ACM Trans. Graph. 34, 156 (2015).
[Crossref]

IEEE J. Sel. Top. Quantum Electron. (1)

T. Kakue, K. Tosa, J. Yuasa, T. Tahara, Y. Awatsuji, K. Nishio, S. Ura, and T. Kubota, “Digital light-in-flight recording by holography by use of a femtosecond pulsed laser,” IEEE J. Sel. Top. Quantum Electron. 18, 479–485 (2012).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33, 2341–2353 (2011).
[Crossref]

Image Vis. Comput. (1)

S. Lee and H. Shim, “Skewed stereo time-of-flight camera for translucent object imaging,” Image Vis. Comput. 43, 27–38 (2015).
[Crossref]

Int. J. Comput. Vis. (2)

K. Nishino, L. Kratz, and S. Lombardi, “Baysian defogging,” Int. J. Comput. Vis. 98, 263–278 (2012).
[Crossref]

A. Kirmani, T. Hutchison, J. Davis, and R. Raskar, “Looking around the corner using ultrafast transient imaging,” Int. J. Comput. Vis. 95, 13–28 (2011).
[Crossref]

IPSJ Trans. Comput. Vis. Appl. (1)

K. Kitano, T. Okamoto, K. Tanaka, T. Aoto, H. Kubo, T. Funatomi, and Y. Mukaigawa, “Recovering temporal psf using tof camera with delayed light emission,,” IPSJ Trans. Comput. Vis. Appl. 9, 15 (2017).
[Crossref]

Nat. Commun. (1)

A. Velten, T. Willwacher, O. Gupta, A. Veeraraghavan, M. G. Bawendi, and R. Raskar, “Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging,” Nat. Commun. 3, 745 (2012).
[Crossref] [PubMed]

Opt. Express (1)

Opt. Lett. (2)

Vis. Informatics (1)

A. Jarabo, B. Masia, J. Marco, and D. Gutierrez, “Recent advances in transient imaging: A computer graphics and vision perspective,” Vis. Informatics 1, 65–79 (2017).
[Crossref]

Other (13)

D. Berman, T. Treibitz, and S. Avidan, “Non-local image dehazing,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2016), pp. 1674–1682.

J. Wang, J. Bartels, W. Whittaker, A. C. Sankaranarayanan, and S. G. Narasimhan, “Programmable triangulation light curtains,” in Proceedings of European Conference on Computer Vision, (Springer, 2018), pp. 19–34.

M. O’Toole, F. Heide, D. Lindell, K. Zang, S. Diamond, and G. Wetzstein, “Reconstructing transient images from single-photon sensors,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2017), pp. 2289–2297.

J. Lin, Y. Liu, M. B. Hullin, and Q. Dai, “Fourier analysis on transient imaging with a multifrequency time-of-flight camera,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, (IEEE, 2014), pp. 3230–3237.

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Figures (8)

Fig. 1
Fig. 1 Differences of time-of-flight measurements between clear (upper) and foggy (lower) scenes. Measurements are significantly affected by the fog.
Fig. 2
Fig. 2 Phasor representation of AMCW ToF camera observation. Amplitude and phase of the returned light corresponds to the reflectance and the depth of the object, respectively. Both are represented in the polar coordinate frame.
Fig. 3
Fig. 3 The observation with a vector interpretation. The observed phasor corresponds to the sum of vectors in the Cartesian coordinate frame.
Fig. 4
Fig. 4 Phasors in multiple frequency measurements. (a) In a clear scene, the amplitude is constant and the phase is proportional to the frequency. (b) The fog component is the summation of all possible paths. (c) The observations are complicated because they are the summation of all components.
Fig. 5
Fig. 5 The distance of observed phasors δ(f, x1, x2) is constant along with (a) the frequency and (b) the density of fog, if the depths of two points are same. However, the distance varies with respect to the frequency if they are at different depths as shown in (c).
Fig. 6
Fig. 6 A line that connects two points in the Cartesian coordinate frame is parallel to the original phasors if the depths are same. The estimated slope of the line is the phase of the defogged phase with π ambiguity.
Fig. 7
Fig. 7 Experimental result for paper crafts using a smoke machine. While the ordinary ToF is affected by the reflectance of the car, our method recovers uniform depth.
Fig. 8
Fig. 8 Real-world experiment result. Depths are shown with pseudo color in two different depth ranges. The ground truth is measured through clear air. The black pixels are masked as the background. While the ordinary ToF measurement is greatly distorted in both color ranges, our method recovers a visually reasonable depth map, especially at the traffic signs. The numerical evaluations are shown in Table 1.

Tables (1)

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Table 1 Numerical Evaluation of the Mean Depth of Five Signature Regions.

Equations (16)

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{ a ( f , x ) = r ( x ) ϕ ( f , d ( x ) ) = 4 π f d ( x ) c ,
p ( f , x ) = a ( f , x ) e i ϕ ( f , d ( x ) ) .
p ( f , x ) = p s ( f , x ) + p t ( f , x ) = L ( d ( x ) ) s ( l ) e i ϕ ( f , d ( l ) ) d l + a ˜ ( x ) e i ϕ ( f , d ( x ) ) ,
{ a ( f 1 , x ) = a ( f 2 , x ) ϕ ( f 1 , x ) = f 1 f 2 ϕ ( f 2 , x ) ,
δ ( f , x 1 , x 2 ) = p ( f , x 1 ) p ( f , x 2 ) 2 .
δ ( f , x 1 , x 2 ) = a ˜ ( x 1 ) e i ϕ ( f , d ˜ ) a ˜ ( x 2 ) e i ϕ ( f , d ˜ ) + L ( d ˜ ) s ( l ) e i ϕ ( f , d ( l ) ) d l L ( d ˜ ) s ( l ) e i ϕ ( f , d ( l ) ) d l 2 = ( a ˜ 1 a ˜ 2 ) e i ϕ ( f , d ˜ ) 2 = a ˜ 1 a ˜ 2 2 ,
δ ( f , x 1 , x 3 ) = a ˜ 1 e i ϕ ( f , d ( x 1 ) ) a ˜ 3 e i ϕ ( f , d ( x 3 ) ) + [ L ( d ( x 3 ) ) L ( d ( x 1 ) ) ] s ( l ) e i ϕ ( f , d ( l ) ) d l 2 ,
δ ( f , x 1 , x 3 ) = a ˜ 1 2 + a ˜ 3 2 2 a ˜ 1 a ˜ 3 cos  ( ϕ 1 ( f ) ϕ 3 ( f ) ) ) ,
σ ( x i , x j ) = 1 n f ( δ ( f , x i , x j ) δ ˜ ( x i , x j ) ) 2 ,
σ ( x i , x j ) { < t x i and x j are in the same cluster t x i and x j are in other clusters
θ k ( f ) = arg   ( p ( f , x i ) p ( f , x j ) ) = arg   ( ( a ˜ i a ˜ j ) e i ϕ ( f , d ˜ ) ) = ϕ ( f , d ˜ ) mod   π ,
d ^ ( C k ) = argmin d f | θ ^ k ( f ) ( 4 π f d c mod  π ) | ,
δ ( f , x , x 1 ) = a ˜ 1 e i ϕ 1 ( f ) [ L ( ) L ( d ( x 1 ) ) ] s ( l ) e i ϕ ( f , d ( l ) ) d l 2 : = a ˜ 1 + ϵ ( f ) ,
σ ( x , x ) < ϵ ˜ ,
{ v max  = a ˜ i 2 + a ˜ j 2 2 a ˜ i a ˜ j cos  ( 4 π f min  Δ d c ) v min  = a ˜ i 2 + a ˜ j 2 2 a ˜ i a ˜ j cos  ( 4 π f max  Δ d c ) ,
t v max  v min  12

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