Abstract

Human vision is sensitive to the changes of local image details, which are actually image gradients. To enhance faint infrared image details, this article proposes a gradient field specification algorithm. First we define the image gradient field and gradient histogram. Then, by analyzing the characteristics of the gradient histogram, we construct a Gaussian function to obtain the gradient histogram specification and therefore obtain the transform gradient field. In addition, subhistogram equalization is proposed based on the histogram equalization to improve the contrast of infrared images. The experimental results show that the algorithm can effectively improve image contrast and enhance weak infrared image details and edges. As a result, it can give qualified image information for different applications of an infrared image. In addition, it can also be applied to enhance other types of images such as visible, medical, and lunar surface.

© 2014 Optical Society of America

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References

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  1. J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
    [CrossRef]
  2. K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
    [CrossRef]
  3. V. E. Viekers, “Plateau equalization algorithm for real-time display of high-quality infrared imagery,” Opt. Eng. 35, 1921–1926 (1996).
    [CrossRef]
  4. Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).
  5. J. A. Ferrari and J. L. Flores, “Nondirectional edge enhancement by contrast reverted low-pass Fourier filtering,” Appl. Opt. 49, 3291–3296 (2010).
    [CrossRef]
  6. X. Z. Bai, F. G. Zhou, and B. D. Xue, “Noise-suppressed image enhancement using multiscale top-hat selection transform through region extraction,” Appl. Opt. 51, 338–347 (2011).
    [CrossRef]
  7. R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
    [CrossRef]
  8. K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
    [CrossRef]
  9. M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
    [CrossRef]
  10. Q. Wang and K. Ward, “Fast image/video contrast enhancement based on weighted threshold histogram equalization,” IEEE Trans. Consum. Electron. 53, 757–764 (2007).
    [CrossRef]
  11. X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
    [CrossRef]
  12. A. Belyaev, “Implicit image differentiation and filtering with applications to image sharpening,” SIAM J. Imag. Sci. 6, 660–679 (2013).
  13. C. C. Tseng and S. L. Lee, “Digital image sharpening using fractional derivative and mach band effect,” in International Symposium on Circuits and Systems (ISCAS) (IEEE, 2012).
  14. C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
    [CrossRef]
  15. C. Wang and Z. F. Ye, “Brightness preserving histogram equalization with maximum entropy: a variational perspective,” IEEE Trans. Consum. Electron. 51, 1326–1334 (2005).
    [CrossRef]
  16. M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
    [CrossRef]
  17. D. Sen and S. K. Pal, “Automatic exact histogram specification for contrast enhancement and visual system based quantitative evaluation,” IEEE Trans. Image Process. 20, 1211–1220 (2011).
    [CrossRef]
  18. W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.
  19. N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), Vol. 1, pp. 886–893.
  20. Y. Z. Zhang, “Improving the accuracy of direct histogram specification,” Electron. Lett. 28, 213–214 (1992).
    [CrossRef]
  21. D. A. Socolinsky and L. B. Wolff, “Multispectral image visualization through first-order fusion,” IEEE Trans. Image Process. 11, 923–931 (2002).
    [CrossRef]
  22. W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
    [CrossRef]

2013 (2)

A. Belyaev, “Implicit image differentiation and filtering with applications to image sharpening,” SIAM J. Imag. Sci. 6, 660–679 (2013).

M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
[CrossRef]

2012 (2)

J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
[CrossRef]

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

2011 (4)

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Noise-suppressed image enhancement using multiscale top-hat selection transform through region extraction,” Appl. Opt. 51, 338–347 (2011).
[CrossRef]

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

D. Sen and S. K. Pal, “Automatic exact histogram specification for contrast enhancement and visual system based quantitative evaluation,” IEEE Trans. Image Process. 20, 1211–1220 (2011).
[CrossRef]

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
[CrossRef]

2010 (2)

J. A. Ferrari and J. L. Flores, “Nondirectional edge enhancement by contrast reverted low-pass Fourier filtering,” Appl. Opt. 49, 3291–3296 (2010).
[CrossRef]

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

2007 (3)

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Q. Wang and K. Ward, “Fast image/video contrast enhancement based on weighted threshold histogram equalization,” IEEE Trans. Consum. Electron. 53, 757–764 (2007).
[CrossRef]

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

2005 (2)

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

C. Wang and Z. F. Ye, “Brightness preserving histogram equalization with maximum entropy: a variational perspective,” IEEE Trans. Consum. Electron. 51, 1326–1334 (2005).
[CrossRef]

2003 (1)

Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).

2002 (1)

D. A. Socolinsky and L. B. Wolff, “Multispectral image visualization through first-order fusion,” IEEE Trans. Image Process. 11, 923–931 (2002).
[CrossRef]

1996 (1)

V. E. Viekers, “Plateau equalization algorithm for real-time display of high-quality infrared imagery,” Opt. Eng. 35, 1921–1926 (1996).
[CrossRef]

1992 (1)

Y. Z. Zhang, “Improving the accuracy of direct histogram specification,” Electron. Lett. 28, 213–214 (1992).
[CrossRef]

Araújo, A.

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Bai, L. F.

Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).

Bai, X. Z.

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Noise-suppressed image enhancement using multiscale top-hat selection transform through region extraction,” Appl. Opt. 51, 338–347 (2011).
[CrossRef]

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
[CrossRef]

Belyaev, A.

A. Belyaev, “Implicit image differentiation and filtering with applications to image sharpening,” SIAM J. Imag. Sci. 6, 660–679 (2013).

Chae, O.

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

Chan, R.

M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
[CrossRef]

Chen, Q.

Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).

Choi, K.

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

Dalal, N.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), Vol. 1, pp. 886–893.

David, M.

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Dewan, M. A. A.

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

Ferrari, J. A.

Flores, J. L.

Gawarikar, A. S.

J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
[CrossRef]

Jacques, F.

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Kabir, M. H.

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

Kang, M. H.

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

Kim, C.

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

Lai, R.

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

Laurent, N.

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Lee, S. L.

C. C. Tseng and S. L. Lee, “Digital image sharpening using fractional derivative and mach band effect,” in International Symposium on Circuits and Systems (ISCAS) (IEEE, 2012).

Liang, K.

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

Ma, Y.

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

Nikolova, M.

M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
[CrossRef]

Pai, T. W.

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

Pal, S. K.

D. Sen and S. K. Pal, “Automatic exact histogram specification for contrast enhancement and visual system based quantitative evaluation,” IEEE Trans. Image Process. 20, 1211–1220 (2011).
[CrossRef]

Ra, J. B.

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

Ruan, S. J.

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

Sen, D.

D. Sen and S. K. Pal, “Automatic exact histogram specification for contrast enhancement and visual system based quantitative evaluation,” IEEE Trans. Image Process. 20, 1211–1220 (2011).
[CrossRef]

Shea, R. P.

J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
[CrossRef]

Shie, M. C.

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

Socolinsky, D. A.

D. A. Socolinsky and L. B. Wolff, “Multispectral image visualization through first-order fusion,” IEEE Trans. Image Process. 11, 923–931 (2002).
[CrossRef]

Song, C. W.

W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.

Sun, C. C.

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

Talghader, J. J.

J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
[CrossRef]

Triggs, B.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), Vol. 1, pp. 886–893.

Tseng, C. C.

C. C. Tseng and S. L. Lee, “Digital image sharpening using fractional derivative and mach band effect,” in International Symposium on Circuits and Systems (ISCAS) (IEEE, 2012).

Viekers, V. E.

V. E. Viekers, “Plateau equalization algorithm for real-time display of high-quality infrared imagery,” Opt. Eng. 35, 1921–1926 (1996).
[CrossRef]

Wadud, W. A. A.

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

Wang, B. J.

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

Wang, C.

C. Wang and Z. F. Ye, “Brightness preserving histogram equalization with maximum entropy: a variational perspective,” IEEE Trans. Consum. Electron. 51, 1326–1334 (2005).
[CrossRef]

Wang, Q.

Q. Wang and K. Ward, “Fast image/video contrast enhancement based on weighted threshold histogram equalization,” IEEE Trans. Consum. Electron. 53, 757–764 (2007).
[CrossRef]

Wang, R.

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

Ward, K.

Q. Wang and K. Ward, “Fast image/video contrast enhancement based on weighted threshold histogram equalization,” IEEE Trans. Consum. Electron. 53, 757–764 (2007).
[CrossRef]

Wen, Y. W.

M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
[CrossRef]

Wolff, L. B.

D. A. Socolinsky and L. B. Wolff, “Multispectral image visualization through first-order fusion,” IEEE Trans. Image Process. 11, 923–931 (2002).
[CrossRef]

Xue, B. D.

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
[CrossRef]

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Noise-suppressed image enhancement using multiscale top-hat selection transform through region extraction,” Appl. Opt. 51, 338–347 (2011).
[CrossRef]

Xue, Y.

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

Yang, Y. T.

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

Ye, Z. F.

C. Wang and Z. F. Ye, “Brightness preserving histogram equalization with maximum entropy: a variational perspective,” IEEE Trans. Consum. Electron. 51, 1326–1334 (2005).
[CrossRef]

Zhang, B. M.

Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).

Zhang, D.

W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.

Zhang, L.

W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.

Zhang, Y. Z.

Y. Z. Zhang, “Improving the accuracy of direct histogram specification,” Electron. Lett. 28, 213–214 (1992).
[CrossRef]

Zhou, B.

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

Zhou, F. G.

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
[CrossRef]

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Noise-suppressed image enhancement using multiscale top-hat selection transform through region extraction,” Appl. Opt. 51, 338–347 (2011).
[CrossRef]

Zhou, H. X.

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

Zuo, W. M.

W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.

Appl. Opt. (2)

Electron. Lett. (1)

Y. Z. Zhang, “Improving the accuracy of direct histogram specification,” Electron. Lett. 28, 213–214 (1992).
[CrossRef]

IEEE Signal Process. Lett. (1)

K. Choi, C. Kim, M. H. Kang, and J. B. Ra, “Resolution improvement of infrared images using visible image information,” IEEE Signal Process. Lett. 18, 611–614 (2011).
[CrossRef]

IEEE Trans. Consum. Electron. (5)

M. David, N. Laurent, F. Jacques, and A. Araújo, “Multi-histogram equalization methods for contrast enhancement and brightness preserving,” IEEE Trans. Consum. Electron. 53, 1186–1194 (2007).
[CrossRef]

Q. Wang and K. Ward, “Fast image/video contrast enhancement based on weighted threshold histogram equalization,” IEEE Trans. Consum. Electron. 53, 757–764 (2007).
[CrossRef]

C. C. Sun, S. J. Ruan, M. C. Shie, and T. W. Pai, “Dynamic contrast enhancement based on histogram specification,” IEEE Trans. Consum. Electron. 51, 1300–1305 (2005).
[CrossRef]

C. Wang and Z. F. Ye, “Brightness preserving histogram equalization with maximum entropy: a variational perspective,” IEEE Trans. Consum. Electron. 51, 1326–1334 (2005).
[CrossRef]

W. A. A. Wadud, M. H. Kabir, M. A. A. Dewan, and O. Chae, “A dynamic histogram equalization for image contrast enhancement,” IEEE Trans. Consum. Electron. 53, 593–600 (2007).
[CrossRef]

IEEE Trans. Image Process. (2)

D. A. Socolinsky and L. B. Wolff, “Multispectral image visualization through first-order fusion,” IEEE Trans. Image Process. 11, 923–931 (2002).
[CrossRef]

D. Sen and S. K. Pal, “Automatic exact histogram specification for contrast enhancement and visual system based quantitative evaluation,” IEEE Trans. Image Process. 20, 1211–1220 (2011).
[CrossRef]

Infrared Phys. Technol. (2)

X. Z. Bai, F. G. Zhou, and B. D. Xue, “Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform,” Infrared Phys. Technol. 54, 61–69 (2011).
[CrossRef]

K. Liang, Y. Ma, Y. Xue, B. Zhou, and R. Wang, “A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization,” Infrared Phys. Technol. 55, 309–315 (2012).
[CrossRef]

J. Infrared Millim. Waves (1)

Q. Chen, L. F. Bai, and B. M. Zhang, “Histogram double equalization in infrared image,” J. Infrared Millim. Waves 22, 428–430 (2003).

J. Math. Imaging Vis. (1)

M. Nikolova, Y. W. Wen, and R. Chan, “Exact histogram specification for digital images using a variational approach,” J. Math. Imaging Vis. 46, 309–325 (2013).
[CrossRef]

Light Sci. Appl. (1)

J. J. Talghader, A. S. Gawarikar, and R. P. Shea, “Spectral selectivity in infrared thermal detection,” Light Sci. Appl. 1, 6–16 (2012).
[CrossRef]

Opt. Commun. (1)

R. Lai, Y. T. Yang, B. J. Wang, and H. X. Zhou, “A quantitative measure based infrared image enhancement algorithm using plateau histogram,” Opt. Commun. 283, 4283–4288 (2010).
[CrossRef]

Opt. Eng. (1)

V. E. Viekers, “Plateau equalization algorithm for real-time display of high-quality infrared imagery,” Opt. Eng. 35, 1921–1926 (1996).
[CrossRef]

SIAM J. Imag. Sci. (1)

A. Belyaev, “Implicit image differentiation and filtering with applications to image sharpening,” SIAM J. Imag. Sci. 6, 660–679 (2013).

Other (3)

C. C. Tseng and S. L. Lee, “Digital image sharpening using fractional derivative and mach band effect,” in International Symposium on Circuits and Systems (ISCAS) (IEEE, 2012).

W. M. Zuo, L. Zhang, C. W. Song, and D. Zhang, “Texture enhanced image denoising via gradient histogram preservation,” in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2013), pp. 1203–1210.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (IEEE, 2005), Vol. 1, pp. 886–893.

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Figures (12)

Fig. 1.
Fig. 1.

Overall process of the proposed algorithm.

Fig. 2.
Fig. 2.

Graphical illustration of the gradient histogram obtained from the Gaussian function.

Fig. 3.
Fig. 3.

Gradient magnitude fields and gradient histograms of the armored car. (a) Original image. (b) Modified image by gradient HS. (c) Enhanced image by HE and SHE only. (d) Final enhanced image by the proposed algorithm. (e) Original gradient magnitude field. (f) Transformed gradient amplitude field. (g) Original gradient histogram. (h) Transformed gradient histogram.

Fig. 4.
Fig. 4.

Flowchart of image reconstruction.

Fig. 5.
Fig. 5.

Subhistogram segmentation schematic diagram. (a) Dividing the histogram based on local minima. (b) Subhistogram expansion.

Fig. 6.
Fig. 6.

Modified images comparison with different β. (a) β=2.5, (b) β=2.0, (c) β=1.5, (d) β=1.0.

Fig. 7.
Fig. 7.

Experimental results comparison of different algorithms. (a) Original infrared image. (b) Plateau HE. (c) Double plateaus HE. (d) Multiscale new top-hat transform. (e) Proposed algorithm.

Fig. 8.
Fig. 8.

Experimental results comparison of a door. (a) Original infrared image. (b) Plateau HE. (c) Double plateaus HE. (d) Multiscale new top-hat transform. (e) Proposed algorithm.

Fig. 9.
Fig. 9.

Experimental results comparison of buildings. (a) Original infrared image. (b) Plateau HE. (c) Double plateaus HE. (d) Multiscale new top-hat transform. (e) Proposed algorithm.

Fig. 10.
Fig. 10.

Comparison experiment of visible images enhancement. (a) Original image. (b) Proposed algorithm. (c) HE.

Fig. 11.
Fig. 11.

Comparison experiment of medical images enhancement. (a) Original image. (b) Proposed algorithm. (c) HE.

Fig. 12.
Fig. 12.

Comparison experiment of lunar images enhancement. (a) Original image. (b) Proposed algorithm. (c) HE.

Tables (1)

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Table 1. Objective Comparison of Image Enhancement Effect Using GMG

Equations (19)

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up=[upx,upy].
skT=T(rkT)=i=0kp(riT)=i=0kniTnT,
vkT=G(zkT)=i=0kf(ziT).
zkT=G1(skT),
f(x)=12πσe(xμ)22σ2(<x<+);
μ=rT=0l1rTp(rT),
σ=1{β[rT=0l1(rTμ)2p(rT)]1/2},
G=S(|u0|)·u0|u0|,
F(us)=min{Ω|usG|2dxdy}.
{Δus=divGonΩus·n⃗=G·n⃗=0onΩ,
usn+1=usn14(ΔusndivG),
Δus(i,j)=us(i+1,j)+us(i1,j)+us(i,j+1)+us(i,j1)4us(i,j),
divG=Gx(i,j)Gx(i1,j)+Gy(i,j)Gy(i,j1),
usn+1(i,j)=usn(i,j)14{[us(i+1,j)+us(i1,j)+us(i,j+1)+us(i,j1)4us(i,j)][Gx(i,j)Gx(i1,j)+Gy(i,j)Gy(i,j1)]}.
{utemp=usn14(ΔusndivG)usn+1=max{0,min(255,utemp)}.
ai=(didi1)log(k=di1+1dink),
Ri=255×aik=1nak,
{ski=Ri·j=(i1)end+1kinjnii=1ski=m=1i1Rm+Ri·j=(i1)end+1kinjnii2,
GMG=1(M1)(N1)i=1M1j=1N1(ΔIx)2+(ΔIy)22,

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