Abstract

Degradation of images by the atmosphere is a familiar problem. For example, when terrain is imaged from a forward-looking airborne camera, the atmosphere degradation causes a loss in both contrast and color information. Enhancement of such images is a difficult task because of the complexity in restoring both the luminance and the chrominance while maintaining good color fidelity. One particular problem is the fact that the level of contrast loss depends strongly on wavelength. A novel method is presented for the enhancement of color images. This method is based on the underlying physics of the degradation process, and the parameters required for enhancement are estimated from the image itself.

© 2001 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. N. S. Kopeika, I. Dror, D. Sadot, “Causes of atmospheric blur: comment on Atmospheric scattering effect on spatial resolution of imaging systems,” J. Opt. Soc. Am. A 15, 3097–3106 (1998).
    [CrossRef]
  2. N. S. Kopeika, A System Engineering Approach to Imaging (SPIE Optical Engineering Press, Bellingham, Wash., 1998).
  3. W. Niblack, An Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, London, 1986).
  4. I. Pitas, P. Kiniklis, “Multichannel techniques in color image enhancement and modelling,” IEEE Trans. Image Process. 5, 168–171 (1996).
    [CrossRef]
  5. J. S. Tyo, “Enhancement of the point-spread function for imaging in scattering media by use of polarization-difference imaging,” J. Opt. Soc. Am. A 17, 1–10 (2000).
    [CrossRef]
  6. X. Gan, S. P. Schilders, M. Gu, “Image enhancement through turbid media under a microscope by use of polarization gating methods,” J. Opt. Soc. Am. A 16, 2177–2184 (1999).
    [CrossRef]
  7. E. P. Zege, I. L. Katsev, “To see the unseen: vision in scattering media,” in Current Trends in Optics, J. C. Dainty, ed. (Academic, London, 1994), pp. 107–121.
  8. S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
    [CrossRef]
  9. V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
    [CrossRef]
  10. J. A. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process. 9, 889–896 (2000).
    [CrossRef]
  11. T. Lin, T. Kao, “Adaptive local contrast enhancement method for medical images displayed on a video monitor,” Med. Eng. Phys. 22, 79–87 (2000).
    [CrossRef] [PubMed]
  12. G. Aviram, S. R. Rotman, “Analyzing the improving effect of modeled histogram enhancement on human target detection performance of infrared images,” Infrared Phys. Technol. 41, 163–168 (2000).
    [CrossRef]
  13. H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
    [CrossRef]
  14. Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
    [CrossRef]
  15. R. A. McKim, S. K. Sinha, “Condition assessment of underground sewer pipes using a modified digital image processing paradigm,” Trenchless Technol. Res. 14, 29–37 (1999).
  16. Y. Rzhanov, L. Linnett, R. Forbes, “Underwater video mosaicing for seabed mapping,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 224–227.
  17. J. P. Oakley, B. L. Satherley, “Improving image quality in poor visibility conditions using a physical model for contrast degradation,” IEEE Trans. Image Process. 7, 167–179 (1998).
    [CrossRef]
  18. E. J. McCartney, Optics of the Atmosphere (Wiley, Toronto, 1976),
  19. M. Iqbal, An Introduction to Solar Radiation (Academic, Toronto, 1983).
  20. R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
    [CrossRef]
  21. Matlab Version 5.1.0.521 (The MathWorks Inc., Natick, Mass., 1997).

2000

J. A. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process. 9, 889–896 (2000).
[CrossRef]

T. Lin, T. Kao, “Adaptive local contrast enhancement method for medical images displayed on a video monitor,” Med. Eng. Phys. 22, 79–87 (2000).
[CrossRef] [PubMed]

G. Aviram, S. R. Rotman, “Analyzing the improving effect of modeled histogram enhancement on human target detection performance of infrared images,” Infrared Phys. Technol. 41, 163–168 (2000).
[CrossRef]

J. S. Tyo, “Enhancement of the point-spread function for imaging in scattering media by use of polarization-difference imaging,” J. Opt. Soc. Am. A 17, 1–10 (2000).
[CrossRef]

1999

V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
[CrossRef]

X. Gan, S. P. Schilders, M. Gu, “Image enhancement through turbid media under a microscope by use of polarization gating methods,” J. Opt. Soc. Am. A 16, 2177–2184 (1999).
[CrossRef]

H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
[CrossRef]

R. A. McKim, S. K. Sinha, “Condition assessment of underground sewer pipes using a modified digital image processing paradigm,” Trenchless Technol. Res. 14, 29–37 (1999).

1998

J. P. Oakley, B. L. Satherley, “Improving image quality in poor visibility conditions using a physical model for contrast degradation,” IEEE Trans. Image Process. 7, 167–179 (1998).
[CrossRef]

R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
[CrossRef]

N. S. Kopeika, I. Dror, D. Sadot, “Causes of atmospheric blur: comment on Atmospheric scattering effect on spatial resolution of imaging systems,” J. Opt. Soc. Am. A 15, 3097–3106 (1998).
[CrossRef]

1997

Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
[CrossRef]

1996

I. Pitas, P. Kiniklis, “Multichannel techniques in color image enhancement and modelling,” IEEE Trans. Image Process. 5, 168–171 (1996).
[CrossRef]

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Aviram, G.

G. Aviram, S. R. Rotman, “Analyzing the improving effect of modeled histogram enhancement on human target detection performance of infrared images,” Infrared Phys. Technol. 41, 163–168 (2000).
[CrossRef]

Barr, C. J.

R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
[CrossRef]

Barry, N. P.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Caselles, V.

V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
[CrossRef]

Chan, F. H. Y.

H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
[CrossRef]

Dainty, J. C.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Dror, I.

N. S. Kopeika, I. Dror, D. Sadot, “Causes of atmospheric blur: comment on Atmospheric scattering effect on spatial resolution of imaging systems,” J. Opt. Soc. Am. A 15, 3097–3106 (1998).
[CrossRef]

Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
[CrossRef]

Forbes, R.

Y. Rzhanov, L. Linnett, R. Forbes, “Underwater video mosaicing for seabed mapping,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 224–227.

French, P. M. W.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Fuller, R. M.

R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
[CrossRef]

Gan, X.

Gu, M.

Hyde, S. C. W.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Iqbal, M.

M. Iqbal, An Introduction to Solar Radiation (Academic, Toronto, 1983).

Jones, R.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Kao, T.

T. Lin, T. Kao, “Adaptive local contrast enhancement method for medical images displayed on a video monitor,” Med. Eng. Phys. 22, 79–87 (2000).
[CrossRef] [PubMed]

Katsev, I. L.

E. P. Zege, I. L. Katsev, “To see the unseen: vision in scattering media,” in Current Trends in Optics, J. C. Dainty, ed. (Academic, London, 1994), pp. 107–121.

Kiniklis, P.

I. Pitas, P. Kiniklis, “Multichannel techniques in color image enhancement and modelling,” IEEE Trans. Image Process. 5, 168–171 (1996).
[CrossRef]

Kopeika, N. S.

N. S. Kopeika, I. Dror, D. Sadot, “Causes of atmospheric blur: comment on Atmospheric scattering effect on spatial resolution of imaging systems,” J. Opt. Soc. Am. A 15, 3097–3106 (1998).
[CrossRef]

Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
[CrossRef]

N. S. Kopeika, A System Engineering Approach to Imaging (SPIE Optical Engineering Press, Bellingham, Wash., 1998).

Lam, F. K.

H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
[CrossRef]

Lin, T.

T. Lin, T. Kao, “Adaptive local contrast enhancement method for medical images displayed on a video monitor,” Med. Eng. Phys. 22, 79–87 (2000).
[CrossRef] [PubMed]

Linnett, L.

Y. Rzhanov, L. Linnett, R. Forbes, “Underwater video mosaicing for seabed mapping,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 224–227.

Lisani, J.

V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
[CrossRef]

McCartney, E. J.

E. J. McCartney, Optics of the Atmosphere (Wiley, Toronto, 1976),

McKim, R. A.

R. A. McKim, S. K. Sinha, “Condition assessment of underground sewer pipes using a modified digital image processing paradigm,” Trenchless Technol. Res. 14, 29–37 (1999).

Morel, J.

V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
[CrossRef]

Niblack, W.

W. Niblack, An Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, London, 1986).

Oakley, J. P.

J. P. Oakley, B. L. Satherley, “Improving image quality in poor visibility conditions using a physical model for contrast degradation,” IEEE Trans. Image Process. 7, 167–179 (1998).
[CrossRef]

Pitas, I.

I. Pitas, P. Kiniklis, “Multichannel techniques in color image enhancement and modelling,” IEEE Trans. Image Process. 5, 168–171 (1996).
[CrossRef]

Rotman, S. R.

G. Aviram, S. R. Rotman, “Analyzing the improving effect of modeled histogram enhancement on human target detection performance of infrared images,” Infrared Phys. Technol. 41, 163–168 (2000).
[CrossRef]

Rzhanov, Y.

Y. Rzhanov, L. Linnett, R. Forbes, “Underwater video mosaicing for seabed mapping,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 224–227.

Sadot, D.

Satherley, B. L.

J. P. Oakley, B. L. Satherley, “Improving image quality in poor visibility conditions using a physical model for contrast degradation,” IEEE Trans. Image Process. 7, 167–179 (1998).
[CrossRef]

Schilders, S. P.

Sinha, S. K.

R. A. McKim, S. K. Sinha, “Condition assessment of underground sewer pipes using a modified digital image processing paradigm,” Trenchless Technol. Res. 14, 29–37 (1999).

Stark, J. A.

J. A. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process. 9, 889–896 (2000).
[CrossRef]

Tyo, J. S.

Wyatt, B. K.

R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
[CrossRef]

Yitzhakya, Y.

Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
[CrossRef]

Zege, E. P.

E. P. Zege, I. L. Katsev, “To see the unseen: vision in scattering media,” in Current Trends in Optics, J. C. Dainty, ed. (Academic, London, 1994), pp. 107–121.

Zhu, H.

H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
[CrossRef]

Comput. Vision Image Understand

H. Zhu, F. H. Y. Chan, F. K. Lam, “Image contrast enhancement by constrained local histogram equalization,” Comput. Vision Image Understand. 73, 281–290 (1999).
[CrossRef]

IEEE Trans. Image Process

V. Caselles, J. Lisani, J. Morel, “Shape preserving local histogram modification,” IEEE Trans. Image Process. 8, 220–230 (1999).
[CrossRef]

J. P. Oakley, B. L. Satherley, “Improving image quality in poor visibility conditions using a physical model for contrast degradation,” IEEE Trans. Image Process. 7, 167–179 (1998).
[CrossRef]

IEEE Trans. Image Process.

J. A. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process. 9, 889–896 (2000).
[CrossRef]

I. Pitas, P. Kiniklis, “Multichannel techniques in color image enhancement and modelling,” IEEE Trans. Image Process. 5, 168–171 (1996).
[CrossRef]

Infrared Phys. Technol.

G. Aviram, S. R. Rotman, “Analyzing the improving effect of modeled histogram enhancement on human target detection performance of infrared images,” Infrared Phys. Technol. 41, 163–168 (2000).
[CrossRef]

J. Environ. Manage.

R. M. Fuller, B. K. Wyatt, C. J. Barr, “Countryside survey from ground and space,” J. Environ. Manage. 54, 101–126 (1998).
[CrossRef]

J. Opt. Soc. Am. A

Med. Eng. Phys.

T. Lin, T. Kao, “Adaptive local contrast enhancement method for medical images displayed on a video monitor,” Med. Eng. Phys. 22, 79–87 (2000).
[CrossRef] [PubMed]

Opt. Commun.

S. C. W. Hyde, N. P. Barry, R. Jones, J. C. Dainty, P. M. W. French, “High resolution depth resolved imaging through scattering media using time resolved holography,” Opt. Commun. 122, 111–116 (1996).
[CrossRef]

Opt. Eng.

Y. Yitzhakya, I. Dror, N. S. Kopeika, “Restoration of atmospherically blurred images according to weather-predicted atmospheric modulation transfer functions,” Opt. Eng. 36, 3064–3072 (1997).
[CrossRef]

Trenchless Technol. Res.

R. A. McKim, S. K. Sinha, “Condition assessment of underground sewer pipes using a modified digital image processing paradigm,” Trenchless Technol. Res. 14, 29–37 (1999).

Other

Y. Rzhanov, L. Linnett, R. Forbes, “Underwater video mosaicing for seabed mapping,” in Proceedings of the IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers, New York, 2000), pp. 224–227.

E. P. Zege, I. L. Katsev, “To see the unseen: vision in scattering media,” in Current Trends in Optics, J. C. Dainty, ed. (Academic, London, 1994), pp. 107–121.

Matlab Version 5.1.0.521 (The MathWorks Inc., Natick, Mass., 1997).

N. S. Kopeika, A System Engineering Approach to Imaging (SPIE Optical Engineering Press, Bellingham, Wash., 1998).

W. Niblack, An Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, London, 1986).

E. J. McCartney, Optics of the Atmosphere (Wiley, Toronto, 1976),

M. Iqbal, An Introduction to Solar Radiation (Academic, Toronto, 1983).

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (7)

Fig. 1
Fig. 1

Image taken by an airborne camera at a height of approximately 1000 m in hazy conditions is shown in (a). Image (a) enhanced by using the proposed method, histogram equalization in RGB space,3 and histogram equalization in HSI space4 is shown in (b), (c), and (d), respectively.

Fig. 2
Fig. 2

Same as Fig. 1 but for another image.

Fig. 3
Fig. 3

Geometry of the imaging scene.

Fig. 4
Fig. 4

Efficiency in terms of color fidelity for different scattering coefficients. The solid, dashed, and dotted curves indicate that Gaussian, uniform, and surveyed20 distributions, respectively, were used to represent P(Fk(λ)) in the maximum-likelihood estimation.

Fig. 5
Fig. 5

Efficiency in terms of visible range for different scattering coefficients. The bold solid curve is the expected visible range obtained by using Eq. (6). The (thin) solid, dashed, and dotted curves indicate that Gaussian, uniform, and surveyed20 distributions, respectively, were used to represent P(Fk(λ)) in the maximum-likelihood estimation.

Fig. 6
Fig. 6

Number of iterations required to converge to the true scattering coefficient 2×10-4 m-1 from different initial scattering coefficients. The end points of each curve indicate the furthest initial scattering coefficient that the system can converge to the true scattering coefficient. The solid, dashed, and dotted curves indicate that Gaussian, uniform, and surveyed20 distributions, respectively, were used to represent P( Fk(λ)) in the maximum-likelihood estimation.

Fig. 7
Fig. 7

Scattering of normalized irradiance versus range.

Tables (2)

Tables Icon

Table 1 Estimated Parametersfor Figs. 1(a) and 2(a)

Tables Icon

Table 2 Average Classification Error and Visible Range for Fig. 2

Equations (6)

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

Jt(k,λ)=ΩI0(λ)Fk(λ)exp[-βsc(λ)Rk],
Jb(k, λ)=ΩkI0(λ){1-exp[-βsc(λ)Rk]}.
Js(k, λ)=ΩkI0(λ){1+[Fk(λ)-1]exp[-βsc(λ)Rk]}.
Fk(λ)=Js(k, λ)ΩkI0(λ)-1exp[βsc(λ)Rk]+1
βsc(λ)=βsc(λred)λλredv-2,
Rv=1βsc(λ) ln1,

Metrics