Abstract

Underwater images often suffer from poor visibility due to photon scattering. However, in some cases, optical polarization filtering techniques can decrease the contribution of the scattered light and improve the visual image quality. In this Letter, the influence of these techniques for underwater image registration is analyzed, particularly when backscattered light is the main perturbation induced by the submarine environment. This analysis is performed using the Cramer–Rao bound and relies on a standard image formation model, taking into account various kinds of noises.

© 2012 Optical Society of America

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References

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2009 (3)

2008 (2)

2004 (1)

H. Singh, J. Howland, and O. Pizarro, IEEE J. Ocean. Eng. 29, 872 (2004).
[CrossRef]

2003 (1)

2002 (1)

S. Negahdaripour and X. Xu, IEEE J. Ocean. Eng. 27, 79 (2002).
[CrossRef]

1990 (1)

J. Jaffe, IEEE J. Ocean. Eng. 15, 101 (1990).
[CrossRef]

1979 (1)

B. McGlamery, SPIE Ocean Optics 208, 221 (1979).

1969 (1)

1967 (1)

1963 (1)

Arnone, R.

Chang, P.

Cochenour, B.

Duntley, S.

Flitton, J.

Garthwaite, P.

P. Garthwaite, I. Jolliffe, and B. Jones, Statistical Inference (Prentice Hall, 1995).

Gilbert, G.

Gracias, N.

J. Santos-Victor, N. Gracias, and S. van der Zwaan, “Using vision for underwater robotics: video mosaics and station keeping,” presented at the 1st International Workshop on Underwater robotics for Sea Exploitation and Environmental Monitoring, Rio de Janeiro, Brazil, 2001.

Gray, D.

Hopcraft, K.

Hou, W.

Howland, J.

H. Singh, J. Howland, and O. Pizarro, IEEE J. Ocean. Eng. 29, 872 (2004).
[CrossRef]

Jaffe, J.

J. Jaffe, IEEE J. Ocean. Eng. 15, 101 (1990).
[CrossRef]

Jakeman, E.

Jolliffe, I.

P. Garthwaite, I. Jolliffe, and B. Jones, Statistical Inference (Prentice Hall, 1995).

Jones, B.

P. Garthwaite, I. Jolliffe, and B. Jones, Statistical Inference (Prentice Hall, 1995).

Jordan, D.

Kanatani, K.

K. Kanatani and N. Ohta, in 7th IEEE International Conference on Computer Vision (IEEE, 1999), pp. 73–78.

Kollar, I.

B. Widrow and I. Kollar, Quantization Noise (Cambridge University, 2008).

LeMaster, D.

Mahon, R.

McGlamery, B.

B. McGlamery, SPIE Ocean Optics 208, 221 (1979).

Mobley, C.

C. Mobley, Light and Water: Radiative Transfer in Natural Waters (Academic Press, 1994).

Mullen, L.

Muth, J.

Negahdaripour, S.

S. Negahdaripour and X. Xu, IEEE J. Ocean. Eng. 27, 79 (2002).
[CrossRef]

Ohta, N.

K. Kanatani and N. Ohta, in 7th IEEE International Conference on Computer Vision (IEEE, 1999), pp. 73–78.

Pernicka, J.

Pizarro, O.

H. Singh, J. Howland, and O. Pizarro, IEEE J. Ocean. Eng. 29, 872 (2004).
[CrossRef]

Rabinovich, W.

Santos-Victor, J.

J. Santos-Victor, N. Gracias, and S. van der Zwaan, “Using vision for underwater robotics: video mosaics and station keeping,” presented at the 1st International Workshop on Underwater robotics for Sea Exploitation and Environmental Monitoring, Rio de Janeiro, Brazil, 2001.

Schechner, Y.

T. Treibitz and Y. Schechner, IEEE Trans. Pattern Anal. Machine Intell. 31, 385 (2009).
[CrossRef]

T. Treibitz and Y. Schechner, in Proceedings of 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition1861 (2006), Vol. 2.

Singh, H.

H. Singh, J. Howland, and O. Pizarro, IEEE J. Ocean. Eng. 29, 872 (2004).
[CrossRef]

Treibitz, T.

T. Treibitz and Y. Schechner, IEEE Trans. Pattern Anal. Machine Intell. 31, 385 (2009).
[CrossRef]

T. Treibitz and Y. Schechner, in Proceedings of 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition1861 (2006), Vol. 2.

van der Zwaan, S.

J. Santos-Victor, N. Gracias, and S. van der Zwaan, “Using vision for underwater robotics: video mosaics and station keeping,” presented at the 1st International Workshop on Underwater robotics for Sea Exploitation and Environmental Monitoring, Rio de Janeiro, Brazil, 2001.

Walker, J.

Weldemann, A.

Wells, W.

Widrow, B.

B. Widrow and I. Kollar, Quantization Noise (Cambridge University, 2008).

Xu, X.

S. Negahdaripour and X. Xu, IEEE J. Ocean. Eng. 27, 79 (2002).
[CrossRef]

Appl. Opt. (3)

IEEE J. Ocean. Eng. (3)

S. Negahdaripour and X. Xu, IEEE J. Ocean. Eng. 27, 79 (2002).
[CrossRef]

H. Singh, J. Howland, and O. Pizarro, IEEE J. Ocean. Eng. 29, 872 (2004).
[CrossRef]

J. Jaffe, IEEE J. Ocean. Eng. 15, 101 (1990).
[CrossRef]

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

T. Treibitz and Y. Schechner, IEEE Trans. Pattern Anal. Machine Intell. 31, 385 (2009).
[CrossRef]

J. Opt. Soc. Am. (2)

Opt. Express (2)

Opt. Lett. (1)

SPIE Ocean Optics (1)

B. McGlamery, SPIE Ocean Optics 208, 221 (1979).

Other (6)

P. Garthwaite, I. Jolliffe, and B. Jones, Statistical Inference (Prentice Hall, 1995).

K. Kanatani and N. Ohta, in 7th IEEE International Conference on Computer Vision (IEEE, 1999), pp. 73–78.

T. Treibitz and Y. Schechner, in Proceedings of 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition1861 (2006), Vol. 2.

B. Widrow and I. Kollar, Quantization Noise (Cambridge University, 2008).

J. Santos-Victor, N. Gracias, and S. van der Zwaan, “Using vision for underwater robotics: video mosaics and station keeping,” presented at the 1st International Workshop on Underwater robotics for Sea Exploitation and Environmental Monitoring, Rio de Janeiro, Brazil, 2001.

C. Mobley, Light and Water: Radiative Transfer in Natural Waters (Academic Press, 1994).

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Figures (2)

Fig. 1.
Fig. 1.

Image formation model and setup. A polarization splitting system (PSS) allows one to select one or both polarization states. The “intensity imaging” configuration refers to the case where the PSS is not used.

Fig. 2.
Fig. 2.

(a) Variations as a function of P, of the lower (dashed line) and upper (plain line) bounds of the precision gain GT given by Eq. (5) and of GT given by Eq. (6) (black diamonds and black dots), for β=0 and β=0.9. (b) Map of GT for backscattering limited imaging [see Eq. (6)] as a function of P and β.

Equations (8)

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

i(x)=s(xη)+b(x),
i(x)=1+P2s(xη)+1+β2b(x).
Λ[i(x)|η]=exp([i(x)i(x)]22[σ02+σb2(x)+i(x)])2π[σ02+σb2(x)+i(x))].
IF=2logΛ[i|η]/η2,
IF=x[s(xη)]2σ02+ξ(x)+s(xη).
IF=(1+P)24x[s(xη)]2σ02+1+β2ξ(x)+1+P2s(xη).
1+P22GT12[(1+P)21+m+(1P)21M].
GT1+(Pβ)2/(1β2),

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