Abstract

In this paper, we present an infrared small target detection method based on Boolean map visual theory. The scheme is inspired by the phenomenon that small targets can often attract human attention due to two characteristics: brightness and Gaussian-like shape in the local context area. Motivated by this observation, we perform the task under a visual attention framework with Boolean map theory, which reveals that an observer’s visual awareness corresponds to one Boolean map via a selected feature at any given instant. Formally, the infrared image is separated into two feature channels, including a color channel with the original gray intensity map and an orientation channel with the orientation texture maps produced by a designed second order directional derivative filter. For each feature map, Boolean maps delineating targets are computed from hierarchical segmentations. Small targets are then extracted from the target enhanced map, which is obtained by fusing the weighted Boolean maps of the two channels. In experiments, a set of real infrared images covering typical backgrounds with sky, sea, and ground clutters are tested to verify the effectiveness of our method. The results demonstrate that it outperforms the state-of-the-art methods with good performance.

© 2014 Optical Society of America

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  1. J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
    [CrossRef]
  2. J. Shaik and K. Iftekharuddin, “Detection and tracking of targets in infrared images using Bayesian techniques,” Opt. Laser Technol. 41, 832–842 (2009).
    [CrossRef]
  3. S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
    [CrossRef]
  4. S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
    [CrossRef]
  5. G. Wang, C. Chen, and X. Shen, “Facet-based infrared small target detection,” Electron. Lett. 41, 1244–1246 (2005).
    [CrossRef]
  6. W. Meng, T. Jin, and X. Zhao, “Adaptive method of dim small object detection with heavy clutter,” Appl. Opt. 52, D64–D74 (2013).
    [CrossRef]
  7. E. Vasquez, F. Galland, G. Delyon, and P. Réfrégier, “Mixed segmentation-detection-based technique for point target detection in nonhomogeneous sky,” Appl. Opt. 49, 1518–1527 (2010).
    [CrossRef]
  8. L. Yang, J. Yang, and K. Yang, “Adaptive detection for infrared small target under sea-sky complex background,” Electron. Lett. 40, 1083–1085 (2004).
    [CrossRef]
  9. Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
    [CrossRef]
  10. H. Deng, Y. Wei, and M. Tong, “Small target detection based on weighted self-information map,” Infrared Phys. Technol. 60, 197–206 (2013).
    [CrossRef]
  11. P. Wang, J. Tian, and C. Gao, “Infrared small target detection using directional highpass filters based on ls-svm,” Electron. Lett. 45, 156–158 (2009).
    [CrossRef]
  12. L. Huang and H. Pashler, “A Boolean map theory of visual attention,” Psychol. Rev. 114, 599–631 (2007).
    [CrossRef]
  13. R. Haralick, “Digital step edges from zero crossing of second directional derivatives,” in IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE, 1984), pp. 58–68.
  14. J. Suykens and J. Vandewalle, “Least squares support vector machine classifiers,” Neural Proc. Lett. 9, 293–300 (1999).
  15. S. Kim, “Min-local-log filter for detecting small targets in cluttered background,” Electron. Lett. 47, 105–106 (2011).
    [CrossRef]
  16. S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
    [CrossRef]
  17. T. Bae, “Small target detection using bilateral filter and temporal cross product in infrared image,” Infrared Phys. Technol. 54, 403–411 (2011).
    [CrossRef]
  18. V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
    [CrossRef]
  19. X. Bai and F. Zhou, “Analysis of new top-hat transformation and the application for infrared dim small target detection,” Pattern Recognition 43, 2145–2156 (2010).
    [CrossRef]
  20. X. Bai, F. Zhou, and B. Xue, “Infrared dim small target enhancement using toggle contrast operator,” Infrared Phys. Technol. 55, 177–182 (2012).
    [CrossRef]
  21. X. Bai, F. Zhou, and B. Xue, “Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform,” Opt. Express 19, 8444–8457 (2011).
    [CrossRef]
  22. X. Bai and F. Zhou, “Hit-or-miss transform based infrared dim small target enhancement,” Opt. Laser Technol. 43, 1084–1090 (2011).
    [CrossRef]
  23. J. Guo and G. Chen, “Analysis of selection of structural element in mathematical morphology with application to infrared point target detection,” Proc. SPIE 6835, 68350P (2007).
  24. A. Borji and L. Itti, “State-of-the-art in visual attention modeling,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 185–207 (2013).
    [CrossRef]
  25. B. Alexe, T. Deselaers, and V. Ferrari, “What is an object?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2010), pp. 73–80.
  26. U. Rutishauser, D. Walther, C. Koch, and P. Perona, “Is bottom-up attention useful for object recognition?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2004), pp. II37–II44.
  27. X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
    [CrossRef]
  28. X. Wang, G. Lv, and L. Xu, “Infrared dim target detection based on visual attention,” Infrared Phys. Technol. 55, 513–521 (2012).
    [CrossRef]
  29. D. Chan, D. Langan, and D. Staver, “Spatial processing techniques for the detection of small targets in IR clutter,” Proc. SPIE 1305, 53–62 (1990).
    [CrossRef]
  30. T. Soni, J. Zeidler, and W. Ku, “Performance evaluation of 2-d adaptive prediction filters for detection of small objects in image data,” IEEE Trans. Image Process. 2, 327–340 (1993).
    [CrossRef]
  31. L. Huang, A. Treisman, and H. Pashler, “Characterizing the limits of human visual awareness,” Science 317, 823–825 (2007).
    [CrossRef]
  32. C. Healey and J. Enns, “Attention and visual memory in visualization and computer graphics,” IEEE Trans. Vis. Comput. Graph. 18, 1170–1188 (2012).
    [CrossRef]
  33. J. Zhang and S. Sclaroff, “Saliency detection: a Boolean map approach,” in IEEE International Conference on Computation Vision (IEEE, 2013).
  34. C. I. Hilliard, “Selection of a clutter rejection algorithm for real-time target detection from an airborne platform,” Proc. SPIE 4048, 74–84 (2000).
    [CrossRef]

2014 (1)

S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

2013 (5)

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

H. Deng, Y. Wei, and M. Tong, “Small target detection based on weighted self-information map,” Infrared Phys. Technol. 60, 197–206 (2013).
[CrossRef]

W. Meng, T. Jin, and X. Zhao, “Adaptive method of dim small object detection with heavy clutter,” Appl. Opt. 52, D64–D74 (2013).
[CrossRef]

A. Borji and L. Itti, “State-of-the-art in visual attention modeling,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 185–207 (2013).
[CrossRef]

2012 (4)

X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
[CrossRef]

X. Wang, G. Lv, and L. Xu, “Infrared dim target detection based on visual attention,” Infrared Phys. Technol. 55, 513–521 (2012).
[CrossRef]

X. Bai, F. Zhou, and B. Xue, “Infrared dim small target enhancement using toggle contrast operator,” Infrared Phys. Technol. 55, 177–182 (2012).
[CrossRef]

C. Healey and J. Enns, “Attention and visual memory in visualization and computer graphics,” IEEE Trans. Vis. Comput. Graph. 18, 1170–1188 (2012).
[CrossRef]

2011 (4)

X. Bai, F. Zhou, and B. Xue, “Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform,” Opt. Express 19, 8444–8457 (2011).
[CrossRef]

X. Bai and F. Zhou, “Hit-or-miss transform based infrared dim small target enhancement,” Opt. Laser Technol. 43, 1084–1090 (2011).
[CrossRef]

S. Kim, “Min-local-log filter for detecting small targets in cluttered background,” Electron. Lett. 47, 105–106 (2011).
[CrossRef]

T. Bae, “Small target detection using bilateral filter and temporal cross product in infrared image,” Infrared Phys. Technol. 54, 403–411 (2011).
[CrossRef]

2010 (3)

Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

X. Bai and F. Zhou, “Analysis of new top-hat transformation and the application for infrared dim small target detection,” Pattern Recognition 43, 2145–2156 (2010).
[CrossRef]

E. Vasquez, F. Galland, G. Delyon, and P. Réfrégier, “Mixed segmentation-detection-based technique for point target detection in nonhomogeneous sky,” Appl. Opt. 49, 1518–1527 (2010).
[CrossRef]

2009 (2)

P. Wang, J. Tian, and C. Gao, “Infrared small target detection using directional highpass filters based on ls-svm,” Electron. Lett. 45, 156–158 (2009).
[CrossRef]

J. Shaik and K. Iftekharuddin, “Detection and tracking of targets in infrared images using Bayesian techniques,” Opt. Laser Technol. 41, 832–842 (2009).
[CrossRef]

2007 (3)

L. Huang and H. Pashler, “A Boolean map theory of visual attention,” Psychol. Rev. 114, 599–631 (2007).
[CrossRef]

J. Guo and G. Chen, “Analysis of selection of structural element in mathematical morphology with application to infrared point target detection,” Proc. SPIE 6835, 68350P (2007).

L. Huang, A. Treisman, and H. Pashler, “Characterizing the limits of human visual awareness,” Science 317, 823–825 (2007).
[CrossRef]

2005 (1)

G. Wang, C. Chen, and X. Shen, “Facet-based infrared small target detection,” Electron. Lett. 41, 1244–1246 (2005).
[CrossRef]

2004 (1)

L. Yang, J. Yang, and K. Yang, “Adaptive detection for infrared small target under sea-sky complex background,” Electron. Lett. 40, 1083–1085 (2004).
[CrossRef]

2000 (1)

C. I. Hilliard, “Selection of a clutter rejection algorithm for real-time target detection from an airborne platform,” Proc. SPIE 4048, 74–84 (2000).
[CrossRef]

1999 (2)

S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
[CrossRef]

J. Suykens and J. Vandewalle, “Least squares support vector machine classifiers,” Neural Proc. Lett. 9, 293–300 (1999).

1993 (2)

V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
[CrossRef]

T. Soni, J. Zeidler, and W. Ku, “Performance evaluation of 2-d adaptive prediction filters for detection of small objects in image data,” IEEE Trans. Image Process. 2, 327–340 (1993).
[CrossRef]

1990 (1)

D. Chan, D. Langan, and D. Staver, “Spatial processing techniques for the detection of small targets in IR clutter,” Proc. SPIE 1305, 53–62 (1990).
[CrossRef]

Alexe, B.

B. Alexe, T. Deselaers, and V. Ferrari, “What is an object?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2010), pp. 73–80.

Bae, T.

T. Bae, “Small target detection using bilateral filter and temporal cross product in infrared image,” Infrared Phys. Technol. 54, 403–411 (2011).
[CrossRef]

Bai, X.

X. Bai, F. Zhou, and B. Xue, “Infrared dim small target enhancement using toggle contrast operator,” Infrared Phys. Technol. 55, 177–182 (2012).
[CrossRef]

X. Bai, F. Zhou, and B. Xue, “Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform,” Opt. Express 19, 8444–8457 (2011).
[CrossRef]

X. Bai and F. Zhou, “Hit-or-miss transform based infrared dim small target enhancement,” Opt. Laser Technol. 43, 1084–1090 (2011).
[CrossRef]

X. Bai and F. Zhou, “Analysis of new top-hat transformation and the application for infrared dim small target detection,” Pattern Recognition 43, 2145–2156 (2010).
[CrossRef]

Bondaryk, J.

V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
[CrossRef]

Borji, A.

A. Borji and L. Itti, “State-of-the-art in visual attention modeling,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 185–207 (2013).
[CrossRef]

Chan, D.

D. Chan, D. Langan, and D. Staver, “Spatial processing techniques for the detection of small targets in IR clutter,” Proc. SPIE 1305, 53–62 (1990).
[CrossRef]

Chan, P.

S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
[CrossRef]

Chen, C.

G. Wang, C. Chen, and X. Shen, “Facet-based infrared small target detection,” Electron. Lett. 41, 1244–1246 (2005).
[CrossRef]

Chen, G.

J. Guo and G. Chen, “Analysis of selection of structural element in mathematical morphology with application to infrared point target detection,” Proc. SPIE 6835, 68350P (2007).

Delyon, G.

Deng, H.

H. Deng, Y. Wei, and M. Tong, “Small target detection based on weighted self-information map,” Infrared Phys. Technol. 60, 197–206 (2013).
[CrossRef]

Deselaers, T.

B. Alexe, T. Deselaers, and V. Ferrari, “What is an object?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2010), pp. 73–80.

Deshpande, S.

S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
[CrossRef]

Enns, J.

C. Healey and J. Enns, “Attention and visual memory in visualization and computer graphics,” IEEE Trans. Vis. Comput. Graph. 18, 1170–1188 (2012).
[CrossRef]

Er, M.

S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
[CrossRef]

Fan, H.

X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
[CrossRef]

Feng, H.

J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

Ferrari, V.

B. Alexe, T. Deselaers, and V. Ferrari, “What is an object?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2010), pp. 73–80.

Galland, F.

Gao, C.

P. Wang, J. Tian, and C. Gao, “Infrared small target detection using directional highpass filters based on ls-svm,” Electron. Lett. 45, 156–158 (2009).
[CrossRef]

Gu, Y.

Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

Guo, J.

J. Guo and G. Chen, “Analysis of selection of structural element in mathematical morphology with application to infrared point target detection,” Proc. SPIE 6835, 68350P (2007).

Haralick, R.

R. Haralick, “Digital step edges from zero crossing of second directional derivatives,” in IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE, 1984), pp. 58–68.

Healey, C.

C. Healey and J. Enns, “Attention and visual memory in visualization and computer graphics,” IEEE Trans. Vis. Comput. Graph. 18, 1170–1188 (2012).
[CrossRef]

Hilliard, C. I.

C. I. Hilliard, “Selection of a clutter rejection algorithm for real-time target detection from an airborne platform,” Proc. SPIE 4048, 74–84 (2000).
[CrossRef]

Huang, L.

L. Huang, A. Treisman, and H. Pashler, “Characterizing the limits of human visual awareness,” Science 317, 823–825 (2007).
[CrossRef]

L. Huang and H. Pashler, “A Boolean map theory of visual attention,” Psychol. Rev. 114, 599–631 (2007).
[CrossRef]

Iftekharuddin, K.

J. Shaik and K. Iftekharuddin, “Detection and tracking of targets in infrared images using Bayesian techniques,” Opt. Laser Technol. 41, 832–842 (2009).
[CrossRef]

Itti, L.

A. Borji and L. Itti, “State-of-the-art in visual attention modeling,” IEEE Trans. Pattern Anal. Mach. Intell. 35, 185–207 (2013).
[CrossRef]

Jin, T.

Kim, S.

S. Kim, “Min-local-log filter for detecting small targets in cluttered background,” Electron. Lett. 47, 105–106 (2011).
[CrossRef]

Koch, C.

U. Rutishauser, D. Walther, C. Koch, and P. Perona, “Is bottom-up attention useful for object recognition?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2004), pp. II37–II44.

Ku, W.

T. Soni, J. Zeidler, and W. Ku, “Performance evaluation of 2-d adaptive prediction filters for detection of small objects in image data,” IEEE Trans. Image Process. 2, 327–340 (1993).
[CrossRef]

Langan, D.

D. Chan, D. Langan, and D. Staver, “Spatial processing techniques for the detection of small targets in IR clutter,” Proc. SPIE 1305, 53–62 (1990).
[CrossRef]

Leung, M.

V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
[CrossRef]

Li, H.

S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

Li, Q.

J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

Liu, B.

Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

Lu, G.

X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
[CrossRef]

Lv, G.

X. Wang, G. Lv, and L. Xu, “Infrared dim target detection based on visual attention,” Infrared Phys. Technol. 55, 513–521 (2012).
[CrossRef]

Ma, J.

S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

Meng, W.

Pashler, H.

L. Huang and H. Pashler, “A Boolean map theory of visual attention,” Psychol. Rev. 114, 599–631 (2007).
[CrossRef]

L. Huang, A. Treisman, and H. Pashler, “Characterizing the limits of human visual awareness,” Science 317, 823–825 (2007).
[CrossRef]

Peli, T.

V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
[CrossRef]

Peng, H.

J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

Perona, P.

U. Rutishauser, D. Walther, C. Koch, and P. Perona, “Is bottom-up attention useful for object recognition?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2004), pp. II37–II44.

Qi, S.

S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

Réfrégier, P.

Rutishauser, U.

U. Rutishauser, D. Walther, C. Koch, and P. Perona, “Is bottom-up attention useful for object recognition?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2004), pp. II37–II44.

Sclaroff, S.

J. Zhang and S. Sclaroff, “Saliency detection: a Boolean map approach,” in IEEE International Conference on Computation Vision (IEEE, 2013).

Shaik, J.

J. Shaik and K. Iftekharuddin, “Detection and tracking of targets in infrared images using Bayesian techniques,” Opt. Laser Technol. 41, 832–842 (2009).
[CrossRef]

Shao, X.

X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
[CrossRef]

Shen, X.

G. Wang, C. Chen, and X. Shen, “Facet-based infrared small target detection,” Electron. Lett. 41, 1244–1246 (2005).
[CrossRef]

Soni, T.

T. Soni, J. Zeidler, and W. Ku, “Performance evaluation of 2-d adaptive prediction filters for detection of small objects in image data,” IEEE Trans. Image Process. 2, 327–340 (1993).
[CrossRef]

Staver, D.

D. Chan, D. Langan, and D. Staver, “Spatial processing techniques for the detection of small targets in IR clutter,” Proc. SPIE 1305, 53–62 (1990).
[CrossRef]

Suykens, J.

J. Suykens and J. Vandewalle, “Least squares support vector machine classifiers,” Neural Proc. Lett. 9, 293–300 (1999).

Tao, C.

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

Tian, J.

S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

P. Wang, J. Tian, and C. Gao, “Infrared small target detection using directional highpass filters based on ls-svm,” Electron. Lett. 45, 156–158 (2009).
[CrossRef]

Tom, V.

V. Tom, T. Peli, M. Leung, and J. Bondaryk, “Morphology-based algorithm for point target detection in infrared backgrounds,” Proc. SPIE 1954, 2–11 (1993).
[CrossRef]

Tong, M.

H. Deng, Y. Wei, and M. Tong, “Small target detection based on weighted self-information map,” Infrared Phys. Technol. 60, 197–206 (2013).
[CrossRef]

Treisman, A.

L. Huang, A. Treisman, and H. Pashler, “Characterizing the limits of human visual awareness,” Science 317, 823–825 (2007).
[CrossRef]

Vandewalle, J.

J. Suykens and J. Vandewalle, “Least squares support vector machine classifiers,” Neural Proc. Lett. 9, 293–300 (1999).

Vasquez, E.

Venkateswarlu, R.

S. Deshpande, M. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max-median filters for detection of small-targets,” Proc. SPIE 3809, 74–83 (1999).
[CrossRef]

Walther, D.

U. Rutishauser, D. Walther, C. Koch, and P. Perona, “Is bottom-up attention useful for object recognition?” in IEEE Conference on Computation Vision and Pattern Recognition (IEEE, 2004), pp. II37–II44.

Wang, C.

Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

Wang, G.

G. Wang, C. Chen, and X. Shen, “Facet-based infrared small target detection,” Electron. Lett. 41, 1244–1246 (2005).
[CrossRef]

Wang, P.

P. Wang, J. Tian, and C. Gao, “Infrared small target detection using directional highpass filters based on ls-svm,” Electron. Lett. 45, 156–158 (2009).
[CrossRef]

Wang, X.

X. Wang, G. Lv, and L. Xu, “Infrared dim target detection based on visual attention,” Infrared Phys. Technol. 55, 513–521 (2012).
[CrossRef]

Wei, Y.

H. Deng, Y. Wei, and M. Tong, “Small target detection based on weighted self-information map,” Infrared Phys. Technol. 60, 197–206 (2013).
[CrossRef]

Xu, J.

X. Shao, H. Fan, G. Lu, and J. Xu, “An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system,” Infrared Phys. Technol. 55, 403–408 (2012).
[CrossRef]

Xu, L.

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[CrossRef]

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J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

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X. Bai, F. Zhou, and B. Xue, “Infrared dim small target enhancement using toggle contrast operator,” Infrared Phys. Technol. 55, 177–182 (2012).
[CrossRef]

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[CrossRef]

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S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
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L. Yang, J. Yang, and K. Yang, “Adaptive detection for infrared small target under sea-sky complex background,” Electron. Lett. 40, 1083–1085 (2004).
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S. Qi, J. Ma, H. Li, S. Zhang, and J. Tian, “Infrared small target enhancement via phase spectrum of quaternion Fourier transform,” Infrared Phys. Technol. 62, 50–58 (2014).
[CrossRef]

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Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

Zhao, J.

J. Zhao, H. Feng, Z. Xu, Q. Li, and H. Peng, “Real-time automatic small target detection using saliency extraction and morphological theory,” Opt. Laser Technol. 47, 268–277 (2013).
[CrossRef]

Zhao, X.

Zhou, F.

X. Bai, F. Zhou, and B. Xue, “Infrared dim small target enhancement using toggle contrast operator,” Infrared Phys. Technol. 55, 177–182 (2012).
[CrossRef]

X. Bai, F. Zhou, and B. Xue, “Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform,” Opt. Express 19, 8444–8457 (2011).
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[CrossRef]

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[CrossRef]

Appl. Opt. (2)

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L. Yang, J. Yang, and K. Yang, “Adaptive detection for infrared small target under sea-sky complex background,” Electron. Lett. 40, 1083–1085 (2004).
[CrossRef]

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[CrossRef]

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[CrossRef]

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Y. Gu, C. Wang, B. Liu, and Y. Zhang, “A kernel-based nonparametric regression method for clutter removal in infrared small-target detection applications,” IEEE Geosci. Remote Sens. Lett. 7, 469–473 (2010).
[CrossRef]

S. Qi, J. Ma, C. Tao, C. Yang, and J. Tian, “A robust directional saliency-based method for infrared small-target detection under various complex backgrounds,” IEEE Geosci. Remote Sens. Lett. 10, 495–499 (2013).
[CrossRef]

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Figures (7)

Fig. 1.
Fig. 1.

Explanation for Boolean map visual theory in feature channels of (a) color and (b) orientation.

Fig. 2.
Fig. 2.

Illustration for the designed SODD filter: (a) the original map; (b) the primitive SODD map; and (c) the amended SODD map.

Fig. 3.
Fig. 3.

Framework of our proposed infrared small target detection method based on Boolean map visual theory.

Fig. 4.
Fig. 4.

Test infrared images and their target enhanced maps processed by our method and several state-of-the-art methods. For each row, maps from left to right are: the original image, Top-hat, Max-mean, Max-median, BHPF, Facet-model, MLL, and BMVT.

Fig. 5.
Fig. 5.

SCRG and BSF obtained by all compared methods for each test image in Fig. 4.

Fig. 6.
Fig. 6.

ROC curves obtained by all compared methods for each test image in Fig. 4.

Fig. 7.
Fig. 7.

Relationship between detection/false rate and the energy ratio γ.

Equations (12)

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

f(r,c)=i=110Ki·Pi(r,c),
2f(r,c)r2|(0,0)=2K4,2f(r,c)rc|(0,0)=K5,2f(r,c)c2|(0,0)=2K6.
W4=170[2222211111222221111122222],W5=1100[4202421012000002101242024],W6=W4T.
2f(x,y)l2|(x0,y0)=[fxx(x,y)cos2α+2fxy(x,y)×cosαcosβ+fyy(x,y)cos2β]|(x0,y0)=2K4(x0,y0)cos2α+2K5(x0,y0)×cosαcosβ+2K6(x0,y0)cos2β,
Bij(x,y)={1ifFi(x,y)Tj,0ifFi(x,y)<Tj,subject toTjT,TpT,
w=(NlabelNmap)1,
BiF=jwijBij,
BcF=1|Ωc|iΩcBiF,
Ie=cCBcF,
T=argmint|xyIet(x,y)xyIe(x,y)γ|,
Iet(x,y)={Iet(x,y)ifIe(x,y)t,0ifIe(x,y)<t,
SCRG=(S/C)out(S/C)in,BSF=CinCout,

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