Abstract

Image enhancement is an important preprocessing step of infrared (IR) based target recognition and surveillance systems. For a better visualization of targets, it is vital to develop image enhancement techniques that increase the contrast between the target and background and emphasize the regions in the target while suppressing noises and background clutter. This study proposes what we believe to be a novel IR image enhancement method for sea-surface targets based on local frequency cues. The image is transformed blockwise into the Fourier domain, and clustering is done according to the number of expected regions to be enhanced in the scene. Based on the variations in the elements in any cluster and the differences between the cluster centers in the frequency domain, two gain matrices are computed for midfrequency and high frequency images by which the image is enhanced accordingly. We provide results for real data and compare the performance of the proposed algorithm through subjective and quantitative tests with four different enhancement methods. The algorithm shows a better performance in the detail visibility of the target.

© 2010 Optical Society of America

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References

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  1. C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
    [CrossRef]
  2. W. K. Pratt, Digital Image Processing (Wiley, 2001).
    [CrossRef]
  3. H. McCauley and J. E. Auborn, “Image enhancement of infrared uncooled focal plane array imagery,” Proc. SPIE 1479, 416-422 (1991).
    [CrossRef]
  4. J. C. W. Beck, “Image enhancement and moving target detection in IR image sequences,” Proc. SPIE 2020, 187-195 (1993).
    [CrossRef]
  5. M. Irani and S. Peleg, “Motion analysis for image enhancement: resolution, occlusion, and transparency,” J. Visual Commun. Image Represent. 4, 324-335 (1993).
    [CrossRef]
  6. W. Zhao and C. Zhang, “Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion,” J. Opt. Soc. Am. A 25, 1668-1681 (2008).
    [CrossRef]
  7. M. Jourlin and J.-C. Pinoli, “Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model,” Signal Process. 41, 225-237 (1995).
    [CrossRef]
  8. G. Aviram and S. R. Rotman, “Evaluating the effect of infrared image enhancement on human target detection performance and image quality judgment,” Opt. Eng. (Bellingham) 38, 1433-1440 (1999).
    [CrossRef]
  9. J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
    [CrossRef]
  10. M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).
  11. S. Weith-Glushko and C. Salvaggio, “Quantitative analysis of infrared contrast enhancement algorithms,” Proc. SPIE 6543, 1-12 (2007).
  12. R. N. Strickland and H. I. Hahn, “Wavelet transform methods for object detection and recovery,” IEEE Trans. Image Process. 6, 724-735 (1997).
    [CrossRef] [PubMed]
  13. T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).
  14. A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
    [CrossRef]
  15. K. N. Jabri and D. L. Wilson, “Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy,” J. Opt. Soc. Am. A 19, 1297-1307 (2002).
    [CrossRef]
  16. R. Eschbach and K. T. Knox, “Error-diffusion algorithm with edge enhancement,” J. Opt. Soc. Am. A 8, 1844-1850 (1991).
    [CrossRef]
  17. R. Highnam and M. Brady, “Model-based image enhancement of far infrared images,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 410-415 (1997).
    [CrossRef]
  18. M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
    [CrossRef]
  19. U. Qidwai, “Infrared image enhancement using H∞ bounds for surveillance applications,” IEEE Trans. Image Process. 17, 1274-1282 (2008).
    [CrossRef] [PubMed]
  20. R. Muise and A. Mahalanobis, “Image enhancement for automatic target detection,” Proc. SPIE 4726, 267-272 (2002).
    [CrossRef]
  21. T. Yu, Q. Li, and J. Dai, “New enhancement of infrared image based on human visual system,” Chin. Opt. Lett. 7, 206-209 (2009).
    [CrossRef]
  22. F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
    [CrossRef]
  23. R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compression,” in Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (ACM Press, 2002), pp. 249-256.
  24. B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
    [CrossRef]
  25. F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
    [CrossRef]
  26. A. O. Karalı and T. Aytaç, “A comparison of different infrared image enhancement techniques for sea surface targets,” in Conference on Signal Processing, Communications and Applications (IEEE, 2009), pp. 765-768.
    [CrossRef]
  27. R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, 2002).
  28. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley, 2001).

2009 (2)

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

T. Yu, Q. Li, and J. Dai, “New enhancement of infrared image based on human visual system,” Chin. Opt. Lett. 7, 206-209 (2009).
[CrossRef]

2008 (4)

W. Zhao and C. Zhang, “Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion,” J. Opt. Soc. Am. A 25, 1668-1681 (2008).
[CrossRef]

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

U. Qidwai, “Infrared image enhancement using H∞ bounds for surveillance applications,” IEEE Trans. Image Process. 17, 1274-1282 (2008).
[CrossRef] [PubMed]

2007 (1)

S. Weith-Glushko and C. Salvaggio, “Quantitative analysis of infrared contrast enhancement algorithms,” Proc. SPIE 6543, 1-12 (2007).

2006 (1)

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

2004 (2)

J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
[CrossRef]

B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
[CrossRef]

2002 (2)

2000 (2)

M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
[CrossRef]

A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
[CrossRef]

1999 (2)

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

G. Aviram and S. R. Rotman, “Evaluating the effect of infrared image enhancement on human target detection performance and image quality judgment,” Opt. Eng. (Bellingham) 38, 1433-1440 (1999).
[CrossRef]

1997 (2)

R. Highnam and M. Brady, “Model-based image enhancement of far infrared images,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 410-415 (1997).
[CrossRef]

R. N. Strickland and H. I. Hahn, “Wavelet transform methods for object detection and recovery,” IEEE Trans. Image Process. 6, 724-735 (1997).
[CrossRef] [PubMed]

1995 (1)

M. Jourlin and J.-C. Pinoli, “Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model,” Signal Process. 41, 225-237 (1995).
[CrossRef]

1993 (2)

J. C. W. Beck, “Image enhancement and moving target detection in IR image sequences,” Proc. SPIE 2020, 187-195 (1993).
[CrossRef]

M. Irani and S. Peleg, “Motion analysis for image enhancement: resolution, occlusion, and transparency,” J. Visual Commun. Image Represent. 4, 324-335 (1993).
[CrossRef]

1991 (2)

H. McCauley and J. E. Auborn, “Image enhancement of infrared uncooled focal plane array imagery,” Proc. SPIE 1479, 416-422 (1991).
[CrossRef]

R. Eschbach and K. T. Knox, “Error-diffusion algorithm with edge enhancement,” J. Opt. Soc. Am. A 8, 1844-1850 (1991).
[CrossRef]

Auborn, J. E.

H. McCauley and J. E. Auborn, “Image enhancement of infrared uncooled focal plane array imagery,” Proc. SPIE 1479, 416-422 (1991).
[CrossRef]

Aviram, G.

G. Aviram and S. R. Rotman, “Evaluating the effect of infrared image enhancement on human target detection performance and image quality judgment,” Opt. Eng. (Bellingham) 38, 1433-1440 (1999).
[CrossRef]

Aytaç, T.

A. O. Karalı and T. Aytaç, “A comparison of different infrared image enhancement techniques for sea surface targets,” in Conference on Signal Processing, Communications and Applications (IEEE, 2009), pp. 765-768.
[CrossRef]

Beck, J. C. W.

J. C. W. Beck, “Image enhancement and moving target detection in IR image sequences,” Proc. SPIE 2020, 187-195 (1993).
[CrossRef]

Brady, M.

R. Highnam and M. Brady, “Model-based image enhancement of far infrared images,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 410-415 (1997).
[CrossRef]

Branchitta, F.

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

Ciurea, F.

B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
[CrossRef]

Cloud, G.

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Corbin, T.

J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
[CrossRef]

Corsini, G.

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

Dai, J.

Diani, M.

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

Duda, R. O.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley, 2001).

Eschbach, R.

Fattal, R.

R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compression,” in Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (ACM Press, 2002), pp. 249-256.

Funt, B.

B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
[CrossRef]

Gonzalez, R. C.

R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, 2002).

Hahn, H. I.

R. N. Strickland and H. I. Hahn, “Wavelet transform methods for object detection and recovery,” IEEE Trans. Image Process. 6, 724-735 (1997).
[CrossRef] [PubMed]

Hart, P. E.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley, 2001).

Highnam, R.

R. Highnam and M. Brady, “Model-based image enhancement of far infrared images,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 410-415 (1997).
[CrossRef]

Hughes, H. G.

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

Irani, M.

M. Irani and S. Peleg, “Motion analysis for image enhancement: resolution, occlusion, and transparency,” J. Visual Commun. Image Represent. 4, 324-335 (1993).
[CrossRef]

Jabri, K. N.

Jourlin, M.

M. Jourlin and J.-C. Pinoli, “Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model,” Signal Process. 41, 225-237 (1995).
[CrossRef]

Karali, A. O.

A. O. Karalı and T. Aytaç, “A comparison of different infrared image enhancement techniques for sea surface targets,” in Conference on Signal Processing, Communications and Applications (IEEE, 2009), pp. 765-768.
[CrossRef]

Knox, K. T.

Lee, H.

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Li, Q.

Lischinski, D.

R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compression,” in Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (ACM Press, 2002), pp. 249-256.

Littfin, K. M.

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

Liu, G.

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

Liu, X.

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

Ma, S.

M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
[CrossRef]

Mahalanobis, A.

R. Muise and A. Mahalanobis, “Image enhancement for automatic target detection,” Proc. SPIE 4726, 267-272 (2002).
[CrossRef]

Manville, D.

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Mathews, V. J.

A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
[CrossRef]

McCann, J.

B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
[CrossRef]

McCauley, H.

H. McCauley and J. E. Auborn, “Image enhancement of infrared uncooled focal plane array imagery,” Proc. SPIE 1479, 416-422 (1991).
[CrossRef]

McGrath, C. P.

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

Muise, R.

R. Muise and A. Mahalanobis, “Image enhancement for automatic target detection,” Proc. SPIE 4726, 267-272 (2002).
[CrossRef]

O'Connor, J. D.

J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
[CrossRef]

Pace, T.

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Peleg, S.

M. Irani and S. Peleg, “Motion analysis for image enhancement: resolution, occlusion, and transparency,” J. Visual Commun. Image Represent. 4, 324-335 (1993).
[CrossRef]

Pinoli, J. -C.

M. Jourlin and J.-C. Pinoli, “Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model,” Signal Process. 41, 225-237 (1995).
[CrossRef]

Polesel, A.

A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
[CrossRef]

Porta, A.

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

Pratt, W. K.

W. K. Pratt, Digital Image Processing (Wiley, 2001).
[CrossRef]

Puritz, J.

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Qidwai, U.

U. Qidwai, “Infrared image enhancement using H∞ bounds for surveillance applications,” IEEE Trans. Image Process. 17, 1274-1282 (2008).
[CrossRef] [PubMed]

Ramponi, G.

A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
[CrossRef]

Romagnoli, M.

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

Rotman, S. R.

G. Aviram and S. R. Rotman, “Evaluating the effect of infrared image enhancement on human target detection performance and image quality judgment,” Opt. Eng. (Bellingham) 38, 1433-1440 (1999).
[CrossRef]

Salvaggio, C.

S. Weith-Glushko and C. Salvaggio, “Quantitative analysis of infrared contrast enhancement algorithms,” Proc. SPIE 6543, 1-12 (2007).

Shao, M.

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

Stork, D. G.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley, 2001).

Strickland, R. N.

R. N. Strickland and H. I. Hahn, “Wavelet transform methods for object detection and recovery,” IEEE Trans. Image Process. 6, 724-735 (1997).
[CrossRef] [PubMed]

Tang, M.

M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
[CrossRef]

Vollmerhausen, R. H.

J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
[CrossRef]

Weith-Glushko, S.

S. Weith-Glushko and C. Salvaggio, “Quantitative analysis of infrared contrast enhancement algorithms,” Proc. SPIE 6543, 1-12 (2007).

Werman, M.

R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compression,” in Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (ACM Press, 2002), pp. 249-256.

Wilson, D. L.

Woods, R. E.

R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, 2002).

Xiao, J.

M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
[CrossRef]

Yu, T.

Zeisse, C. R.

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

Zhang, C.

Zhao, W.

Zhu, D.

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

Chin. Opt. Lett. (1)

IEEE Trans. Image Process. (3)

R. N. Strickland and H. I. Hahn, “Wavelet transform methods for object detection and recovery,” IEEE Trans. Image Process. 6, 724-735 (1997).
[CrossRef] [PubMed]

A. Polesel, G. Ramponi, and V. J. Mathews, “Image enhancement via adaptive unsharp masking,” IEEE Trans. Image Process. 9, 505-510 (2000).
[CrossRef]

U. Qidwai, “Infrared image enhancement using H∞ bounds for surveillance applications,” IEEE Trans. Image Process. 17, 1274-1282 (2008).
[CrossRef] [PubMed]

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

R. Highnam and M. Brady, “Model-based image enhancement of far infrared images,” IEEE Trans. Pattern Anal. Mach. Intell. 19, 410-415 (1997).
[CrossRef]

J. Electron. Imaging (2)

J. D. O'Connor, R. H. Vollmerhausen, and T. Corbin, “Performance evaluations of a manual display mapping method,” J. Electron. Imaging 13, 709-713 (2004).
[CrossRef]

B. Funt, F. Ciurea, and J. McCann, “Retinex in MATLAB,” J. Electron. Imaging 13, 48-57 (2004).
[CrossRef]

J. Opt. Soc. Am. A (3)

J. Opt. Soc. Am. A Opt. Image Sci. Vis (1)

C. R. Zeisse, C. P. McGrath, K. M. Littfin, and H. G. Hughes, “Infrared radiance of the wind-ruffled sea,” J. Opt. Soc. Am. A Opt. Image Sci. Vis 16, 1439-1452 (1999).
[CrossRef]

J. Visual Commun. Image Represent. (1)

M. Irani and S. Peleg, “Motion analysis for image enhancement: resolution, occlusion, and transparency,” J. Visual Commun. Image Represent. 4, 324-335 (1993).
[CrossRef]

Opt. Eng. (Bellingham) (3)

F. Branchitta, M. Diani, G. Corsini, and M. Romagnoli, “New technique for the visualization of high dynamic range infrared images,” Opt. Eng. (Bellingham) 48, 096401 (2009).
[CrossRef]

G. Aviram and S. R. Rotman, “Evaluating the effect of infrared image enhancement on human target detection performance and image quality judgment,” Opt. Eng. (Bellingham) 38, 1433-1440 (1999).
[CrossRef]

F. Branchitta, M. Diani, G. Corsini, and A. Porta, “Dynamic-range compression and contrast enhancement in infrared imaging systems,” Opt. Eng. (Bellingham) 47, 076401 (2008).
[CrossRef]

Pattern Recogn. Lett. (1)

M. Tang, S. Ma, and J. Xiao, “Model-based adaptive enhancement of far infrared image sequences,” Pattern Recogn. Lett. 21, 827-835 (2000).
[CrossRef]

Proc. SPIE (6)

H. McCauley and J. E. Auborn, “Image enhancement of infrared uncooled focal plane array imagery,” Proc. SPIE 1479, 416-422 (1991).
[CrossRef]

J. C. W. Beck, “Image enhancement and moving target detection in IR image sequences,” Proc. SPIE 2020, 187-195 (1993).
[CrossRef]

R. Muise and A. Mahalanobis, “Image enhancement for automatic target detection,” Proc. SPIE 4726, 267-272 (2002).
[CrossRef]

M. Shao, G. Liu, X. Liu, and D. Zhu, “A new approach for infrared image contrast enhancement,” Proc. SPIE 6150, 1-6 (2006).

S. Weith-Glushko and C. Salvaggio, “Quantitative analysis of infrared contrast enhancement algorithms,” Proc. SPIE 6543, 1-12 (2007).

T. Pace, D. Manville, H. Lee, G. Cloud, and J. Puritz, “A multiresolution approach to image enhancement via histogram shaping and adaptive wiener filtering,” Proc. SPIE 6978, 1-11 (2008).

Signal Process. (1)

M. Jourlin and J.-C. Pinoli, “Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model,” Signal Process. 41, 225-237 (1995).
[CrossRef]

Other (5)

W. K. Pratt, Digital Image Processing (Wiley, 2001).
[CrossRef]

R. Fattal, D. Lischinski, and M. Werman, “Gradient domain high dynamic range compression,” in Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (ACM Press, 2002), pp. 249-256.

A. O. Karalı and T. Aytaç, “A comparison of different infrared image enhancement techniques for sea surface targets,” in Conference on Signal Processing, Communications and Applications (IEEE, 2009), pp. 765-768.
[CrossRef]

R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, 2002).

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (Wiley, 2001).

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Figures (11)

Fig. 1
Fig. 1

(a) Sample image and (b) its histogram.

Fig. 2
Fig. 2

Fourier transform of the blocks given in (a): (b) target (c) target-sea transition, (d) sea, and (e) sky.

Fig. 3
Fig. 3

Distribution of the image blocks according to their clusters.

Fig. 4
Fig. 4

Cluster centers.

Fig. 5
Fig. 5

Gain matrix.

Fig. 6
Fig. 6

(a) Original image and enhancement results ( α high = 10 , c = 6 , β mid = β high = 0.5 , and B 1 = B 2 = 16 ) for (b) α mid = 0.5 , (c) α mid = 1.5 , (d) α mid = 2.5 , and (e) α mid = 3.5 .

Fig. 7
Fig. 7

(a) Original image and enhancement results ( α mid = 0.5 , c = 6 , β mid = β high = 0.5 , and B 1 = B 2 = 16 ) for (b) α high = 1 , (c) α high = 5 , (d) α high = 10 , and (e) α high = 15 .

Fig. 8
Fig. 8

(a) Original image and enhancement results ( α high = 10 , α mid = β mid = β high = 0.5 , and B 1 = B 2 = 16 ) for (b) c = 2 , (c) c = 4 , (d) c = 6 , and (e) c = 8 .

Fig. 9
Fig. 9

[(a), (c), (e), (g), and (i)] Original images and enhancement results ( β mid = 0.5 ) for (b) α mid = 1.5 , α high = 10 , and β high = 0.5 , (d) α mid = 1.5 , α high = 10 , and β high = 0.5 , (f) α mid = 0.5 , α high = 10 , and β high = 0.5 , (h) α mid = 0.5 , α high = 10 , and β high = 0.5 , and (j) α mid = 1.5 , α high = 2 , and β high = 0.1 .

Fig. 10
Fig. 10

[(a), (c), and (e)] Original images and enhancement results ( β high = 0.5 ) for (b) α mid = 1.5 , α high = 10 , and β mid = 0.5 , (d) α mid = 1.5 , α high = 10 , and β mid = 0.5 , and (f) α mid = 0.5 , α high = 10 , and β mid = 0.1 .

Fig. 11
Fig. 11

Comparison results: (a) original image and enhanced images for (b) AMLFC, (c) APHE, (d) BCLAHE-CE, (e) MAM, and (f) AUM.

Tables (2)

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Table 1 Mean Scores of the Observers a

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Table 2 Contrast Results in the Target Region

Equations (17)

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F i ( u , v ) = 1 B 1 B 2 x = 0 B 1 1 y = 0 B 2 1 I i ( x , y ) e j 2 π [ ( u x / B 1 ) + ( v y / B 2 ) ] ,
d r s 2 = ( V r V s ) ( V r V s ) T .
T E j = n = 1 B 1 B 2 / 2 [ CC j ( n ) ] 2 ,
CC j ( n ) ¯ = [ CC j ( n 1 ) ] 2 + [ CC j ( n ) ] 2 + [ CC j ( n + 1 ) ] 2 T E j ,
w j = n = 1 B 1 B 2 / 2 CC j ( n ) ¯ n .
B W ( k ) = w j ,     k th   block cluster j ,
D k ( x , y ) = 1 ( BC k ( x c ) x ) 2 + ( BC k ( y c ) y ) 2 + ϵ ,
G ( x , y ) = k = 1 b D k ( x , y ) l = 1 b D l ( x , y ) B W ( k ) .
G mid ( x , y ) = ( G ( x , y ) G min ) α mid ( G max G min ) + β mid ,
G high ( x , y ) = ( G ( x , y ) G min ) α high ( G max G min ) + β high ,
I enh ( x , y ) = I low ( x , y ) + G mid ( x , y ) I mid ( x , y ) + G high ( x , y ) I high ( x , y ) .
I enh ( x , y ) = p ( I ( x , y ) ) [ I ( x , y ) I low ( x , y ) ] γ ,
I high ( x , y ) = { g 1 I high ( x , y ) , | I high ( x , y ) | < ν g 2 I high ( x , y ) , | I high ( x , y ) | ν , }
δ ( x , y ) = { 1 , V ( x , y ) < τ 1 δ mid , τ 1 V ( x , y ) < τ 2 δ high , V ( x , y ) τ 2 , }
I enh ( x , y ) = δ ( x , y ) I high ( x , y ) .
I UM ( x , y ) = I ( x , y ) + λ x I x ( x , y ) + λ y I y ( x , y ) ,
contrast = 1 R S x = 0 R 1 y = 0 S 1 ( I ( x , y ) I ¯ ) 2 ,

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