Abstract

The small infrared target against a great movement background can be detected by calculating its optical flow field to estimate and compensate for the movement background, but the target against gentle movement background has a large computational complexity for calculating its optical flow field. Therefore, this paper proposed a simplified method for detecting a small infrared target against a gentle movement background, considering that the background has no rotational movement and perspective relationship. It uses the translational motions in the horizontal and vertical directions to represent background movement. It uses the minimum variance of the difference in the gray scale between previous and posterior frames to estimate the background movement in the horizontal and vertical directions; it then uses the differential method and the morphological process to detect a moving small target. The results from measurement sequences show that the proposed method can detect infrared targets against gentle background movement and that its computational complexity is greatly reduced.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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  1. Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
    [Crossref]
  2. S. Deshapande, M. H. Er, R. Venkateswarlu, and P. Chan, “Max-mean and max median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).
    [Crossref]
  3. L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
    [Crossref]
  4. T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
    [Crossref]
  5. J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
    [Crossref]
  6. H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
    [Crossref]
  7. M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
    [Crossref]
  8. J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
    [Crossref]
  9. Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
    [Crossref]
  10. B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
    [Crossref]
  11. A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
    [Crossref]
  12. Y. Li and Y. Zhang, “Robust infrared small target detection using local steering kernel reconstruction,” Pattern Recogn. 77, 113–125 (2018).
    [Crossref]
  13. L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
    [Crossref]
  14. A. P. Tzannes and D. H. Brooks, “Temporal filters for point target detection in IR imagery,” Proc. SPIE 3061, 508–520 (1997).
    [Crossref]
  15. K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
    [Crossref]
  16. X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
    [Crossref]
  17. H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
    [Crossref]
  18. C. M. Huang and M. H. Hung, “Target motion compensation with optical flow clustering during visual tracking,” 2014 IEEE 11th International conference on networking, sensing and control (ICNSC), Miami, FL, USA, 7-9 April, 96–101 (2014).
  19. K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

2018 (6)

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
[Crossref]

Y. Li and Y. Zhang, “Robust infrared small target detection using local steering kernel reconstruction,” Pattern Recogn. 77, 113–125 (2018).
[Crossref]

2017 (5)

L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
[Crossref]

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
[Crossref]

Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
[Crossref]

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

2016 (1)

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

2015 (2)

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
[Crossref]

2012 (1)

T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
[Crossref]

1999 (1)

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

1997 (1)

A. P. Tzannes and D. H. Brooks, “Temporal filters for point target detection in IR imagery,” Proc. SPIE 3061, 508–520 (1997).
[Crossref]

Bae, T.-W.

T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
[Crossref]

Brooks, D. H.

A. P. Tzannes and D. H. Brooks, “Temporal filters for point target detection in IR imagery,” Proc. SPIE 3061, 508–520 (1997).
[Crossref]

Cao, E.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Chan, P.

S. Deshapande, M. H. 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, Y.

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

Chen, Y.-S.

Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
[Crossref]

Cheng, K.

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

Deng, L.

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Deng, X.

L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
[Crossref]

Deshapande, S.

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

Dong, L.

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

Enokidani, M.

K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

Er, M. H.

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

Gu, G.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Guan, Y.

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

Guo, L.

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

He, Y.

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

Hu, J.

J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
[Crossref]

Hu, X.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Huang, C. M.

C. M. Huang and M. H. Hung, “Target motion compensation with optical flow clustering during visual tracking,” 2014 IEEE 11th International conference on networking, sensing and control (ICNSC), Miami, FL, USA, 7-9 April, 96–101 (2014).

Hung, M. H.

C. M. Huang and M. H. Hung, “Target motion compensation with optical flow clustering during visual tracking,” 2014 IEEE 11th International conference on networking, sensing and control (ICNSC), Miami, FL, USA, 7-9 April, 96–101 (2014).

Izumida, M.

K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

Kinoshita, K.

K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

Kweon, I.-S.

T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
[Crossref]

Li, Y.

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

Y. Li and Y. Zhang, “Robust infrared small target detection using local steering kernel reconstruction,” Pattern Recogn. 77, 113–125 (2018).
[Crossref]

Lin, Z.

L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
[Crossref]

Liu, F.

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
[Crossref]

Liu, S.

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

Mo, B.

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

Murakami, K.

K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

Nie, J.

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Ning, C.

X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
[Crossref]

Pei, J.

A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
[Crossref]

Qi, H.

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

Qian, K.

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

Qian, W.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Qu, S.

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Ren, K.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Rong, S.

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

Song, B.

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

Tzannes, A. P.

A. P. Tzannes and D. H. Brooks, “Temporal filters for point target detection in IR imagery,” Proc. SPIE 3061, 508–520 (1997).
[Crossref]

Venkateswarlu, R.

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

Wan, M.

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

Wang, B.

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

Wang, D.

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

Wang, L.

L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
[Crossref]

Wang, X.

X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
[Crossref]

Wei, Y.

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Xie, W.

A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
[Crossref]

Xin, Y.-H.

Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
[Crossref]

Xu, W.

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

Yu, Y.

J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
[Crossref]

Zhang, F.

T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
[Crossref]

Zhang, L.

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Zhang, Y.

Y. Li and Y. Zhang, “Robust infrared small target detection using local steering kernel reconstruction,” Pattern Recogn. 77, 113–125 (2018).
[Crossref]

X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
[Crossref]

Zhao, M.

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

Zhou, A.

A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
[Crossref]

Zhou, H.

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

Zhou, J.

Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
[Crossref]

Zhou, Q.

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

Zhu, H.

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

Comput. Electr. Eng. (1)

H. Zhu, Y. Guan, L. Deng, Y. Li, and Y. Li, “Infrared moving point target detection based on an anisotropic spatial-temporla fourth-order diffusion filter,” Comput. Electr. Eng. 68, 550–556 (2018).
[Crossref]

Infrared Phys. Technol. (12)

M. Wan, G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, “In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds,” Infrared Phys. Technol. 76, 455–467 (2016).
[Crossref]

J. Nie, S. Qu, Y. Wei, L. Zhang, and L. Deng, “An infrared small target detection method based on multiscale local homogeneity measure,” Infrared Phys. Technol. 90, 186–194 (2018).
[Crossref]

Y.-H. Xin, J. Zhou, and Y.-S. Chen, “Dual multi-scale filter with SSS and GW for infrared small target detection,” Infrared Phys. Technol. 81, 97–108 (2017).
[Crossref]

B. Wang, L. Dong, M. Zhao, and W. Xu, “Fast infrared maritime target detection: Binarization via hisrogram curve transformation,” Infrared Phys. Technol. 83, 32–44 (2017).
[Crossref]

A. Zhou, W. Xie, and J. Pei, “Infrared maritime target detection using the high order statistic filtering in fractional Fourier domain,” Infrared Phys. Technol. 91, 123–136 (2018).
[Crossref]

Y. Chen, B. Song, D. Wang, and L. Guo, “An effective infrared small target detection method based on the human visual attention,” Infrared Phys. Technol. 95, 128–135 (2018).
[Crossref]

T.-W. Bae, F. Zhang, and I.-S. Kweon, “Edge directional 2D LMS filter for infrared small target detection,” Infrared Phys. Technol. 55(1), 137–145 (2012).
[Crossref]

J. Hu, Y. Yu, and F. Liu, “Small and dim target detection by background estimation,” Infrared Phys. Technol. 73, 141–148 (2015).
[Crossref]

K. Qian, H. Zhou, S. Rong, B. Wang, and K. Cheng, “Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter,” Infrared Phys. Technol. 82, 18–27 (2017).
[Crossref]

X. Wang, Y. Zhang, and C. Ning, “A novel visual saliency detection method for infrared video sequences,” Infrared Phys. Technol. 87, 91–103 (2017).
[Crossref]

H. Qi, B. Mo, F. Liu, Y. He, and S. Liu, “Small infrared target detection utilizing Local Region Similarity Difference map,” Infrared Phys. Technol. 71, 131–139 (2015).
[Crossref]

L. Wang, Z. Lin, and X. Deng, “Infrared point target detection based on multi-label generative MRF model,” Infrared Phys. Technol. 83, 188–194 (2017).
[Crossref]

Multimed. Tool Appl. (1)

L. Deng, H. Zhu, Q. Zhou, and Y. Li, “Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection,” Multimed. Tool Appl. 77(9), 10539–10551 (2018).
[Crossref]

Pattern Recogn. (1)

Y. Li and Y. Zhang, “Robust infrared small target detection using local steering kernel reconstruction,” Pattern Recogn. 77, 113–125 (2018).
[Crossref]

Proc. SPIE (2)

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

A. P. Tzannes and D. H. Brooks, “Temporal filters for point target detection in IR imagery,” Proc. SPIE 3061, 508–520 (1997).
[Crossref]

Other (2)

C. M. Huang and M. H. Hung, “Target motion compensation with optical flow clustering during visual tracking,” 2014 IEEE 11th International conference on networking, sensing and control (ICNSC), Miami, FL, USA, 7-9 April, 96–101 (2014).

K. Kinoshita, M. Enokidani, M. Izumida, and K. Murakami, “Tracking of a moving object using one-dimensional optical flow with a rotating observer,” 2006 9th International conference on control, automation, robotics and vision, Singapore, Singapore, 5–8 Dec. 2006, pp. 1–6 (2006).

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Figures (2)

Fig. 1.
Fig. 1. The target detection results by the simplification method
Fig. 2.
Fig. 2. Time consumption results for Seq 4.

Tables (4)

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Table 1. Details of the proposed method

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Table 2. Details of the proposed method

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Table 3. Details of the fou sequences

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Table 4. Time consumption results for quantitative evaluation

Equations (16)

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E ( u , v ) = ( x , y ) I k ( x u , y v ) I k + 1 | I k ( x , y ) I k + 1 ( x u , y v ) | 2
( u ^ , v ^ ) = arg min u = [ n , n ] , v = [ m , m ] E ( u , v )
I k + 1 ( x , y ) = I k + 1 ( x u ^ , y v ^ )
I d i f f ( x , y ) = I k ( x , y ) I k + 1 ( x , y )
I d i f f 2 ( x , y ) = { 255 I d i f f ( x , y ) T d 0 I d i f f ( x , y ) < T d , T d = 0 .35 max ( I d i f f ( x , y ) )
I d i f f 3 = I d i f f 2 B = ( I d i f f 2 B ) Θ B
I d i f f 4 = I d i f f 3 B = ( I d i f f 3 Θ B ) B
x k + 1 = ( max I ( x k + 1 i , y k + 1 i ) = 1 ( x k + 1 i ) + min I ( x k + 1 i , y k + 1 i ) = 1 ( x k + 1 i ) ) / ( max I ( x k + 1 i , y k + 1 i ) = 1 ( x k + 1 i ) + min I ( x k + 1 i , y k + 1 i ) = 1 ( x k + 1 i ) ) 2 2
y k + 1 = ( max I ( x k + 1 i , y k + 1 i ) = 1 ( y k + 1 i ) + min I ( x k + 1 i , y k + 1 i ) = 1 ( y k + 1 i ) ) / ( max I ( x k + 1 i , y k + 1 i ) = 1 ( y k + 1 i ) + min I ( x k + 1 i , y k + 1 i ) = 1 ( y k + 1 i ) ) 2 2
x k + 1 = x k + 1 + u ^
y k + 1 = y k + 1 + v ^
I x u + I y v + I t = 0
E = ω ( I x u + I y v + I t ) 2
[ u ^ v ^ ] = [ ω I x I x ω I x I y ω I x I y ω I y I y ] 1 [ ω I x I t ω I y I t ]
[ 1 1 1 1 1 1 1 1 1 ]
[ 1 1 1 1 ]

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