Abstract

This paper investigates an adaptive method of dim small target detection in infrared images with a complex background. We analyze in depth the characteristics of the background, the target, and the noise in the gray intensity, space and frequency domain of the images. The modified top-hat transformation using interrelated structuring elements is adopted to adaptively detect the darker and the brighter targets and greatly suppress the cluttered background. Lateral pattern inhibition enhances the local contrast ratio and simultaneously identifies the targets of interest. The automatic threshold is used to enhance real dim targets in the cluttered background. A simulation based on the proposed algorithm is carried out and the results prove that the algorithm is effective and valid.

© 2013 Optical Society of America

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    [CrossRef]
  2. J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
    [CrossRef]
  3. R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).
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    [CrossRef]
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    [CrossRef]
  7. Z. Wu and S. Tao, “A recursive Bayesian method for multi-target detection and tracking using particle swarms,” Procedia Eng. 29, 4282–4286 (2012).
    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
  22. J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
    [CrossRef]
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    [CrossRef]
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  25. M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
    [CrossRef]

2012

Z. Wu and S. Tao, “A recursive Bayesian method for multi-target detection and tracking using particle swarms,” Procedia Eng. 29, 4282–4286 (2012).
[CrossRef]

H. Huang and T. Jin, “Dim small targets detection with noise suppression utilizing adjacent relevant pixels information,” Acta Photonica Sinica 41, 596–601 (2012).
[CrossRef]

X. Bai, F. Zhou, and B. Xue, “Multiple linear feature detection based on multiple structuring element center surround top-hat transform,” Appl. Opt. 51, 5201–5211 (2012).
[CrossRef]

2011

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]

A. Mehmood and N. M. Nasrabadi, “Kernel wavelet-Reed–Xiaoli: an anomaly detection for forward-looking infrared imagery,” Appl. Opt. 50, 2744–2751 (2011).
[CrossRef]

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

Z. Shao and D. Li, “Adaptive target detection based on improved genetic algorithm in infrared images,” Geomatics and Information Science of Wuhan University 36, 535–539 (2011).
[CrossRef]

J. A. Ratches, “Review of current aided/automatic target acquisition technology for military target acquisition tasks,” Opt. Eng. 50, 072001 (2011).
[CrossRef]

R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).

2010

2009

F. Chen and W. Wang, “Target recognition in clutter scene based on wavelet transform,” Opt. Commun. 282, 523–526 (2009).
[CrossRef]

2008

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

2007

P. Kaewkasi, J. Widjaja, and J. Uozumi, “Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator,” Opt. Commun. 271, 48–58 (2007).
[CrossRef]

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
[CrossRef]

S.-G. Sun, “Target detection using local fuzzy thresholding and binary template matching in forward-looking infrared images,” Opt. Eng. 46, 036402 (2007).
[CrossRef]

2006

M. Zeng, J. Li, and Z. Peng, “The design of top-hat morphological filter and application to infrared target detection,” Infrared Phys. & Technology 48, 67–76 (2006).
[CrossRef]

2004

F. A. Sadjadi, “Infrared target detection with probability density functions of wavelet transform subbands,” Appl. Opt. 43, 315–323 (2004).
[CrossRef]

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

1999

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

1967

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Bai, X.

Boucher, C.

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

Chan, P.

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

Chaojian, S.

R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).

Chen, F.

F. Chen and W. Wang, “Target recognition in clutter scene based on wavelet transform,” Opt. Commun. 282, 523–526 (2009).
[CrossRef]

Corbane, C.

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

Delgado, A. E.

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

Delyon, G.

Demagistri, L.

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

Desai, U. B.

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
[CrossRef]

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Air-borne approaching target detection and tracking in infrared image sequence,” in International Conference on Image Processing (ICIP) (2004), 2, 1025–1028.
[CrossRef]

Deshpande, S. D.

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

Er, M. H.

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

Fernández, M. A.

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

Fernández-Caballero, A.

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

Galland, F.

Hartline, H. K.

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Harvey, N. R.

P. Kraft, S. Marshall, J. J. Soraghan, and N. R. Harvey, “Parallel genetic algorithms for optimizing morphological filters,” in Proceedings of the Fifth International Conference on Image Processing and Its Applications (1995), 762, CP410.
[CrossRef]

Huang, H.

H. Huang and T. Jin, “Dim small targets detection with noise suppression utilizing adjacent relevant pixels information,” Acta Photonica Sinica 41, 596–601 (2012).
[CrossRef]

Jin, T.

H. Huang and T. Jin, “Dim small targets detection with noise suppression utilizing adjacent relevant pixels information,” Acta Photonica Sinica 41, 596–601 (2012).
[CrossRef]

Kaewkasi, P.

P. Kaewkasi, J. Widjaja, and J. Uozumi, “Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator,” Opt. Commun. 271, 48–58 (2007).
[CrossRef]

Kim, S.-H.

Knight, B. W.

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Kraft, P.

P. Kraft, S. Marshall, J. J. Soraghan, and N. R. Harvey, “Parallel genetic algorithms for optimizing morphological filters,” in Proceedings of the Fifth International Conference on Image Processing and Its Applications (1995), 762, CP410.
[CrossRef]

Lee, D.-S.

Lei, R.

R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).

Li, D.

Z. Shao and D. Li, “Adaptive target detection based on improved genetic algorithm in infrared images,” Geomatics and Information Science of Wuhan University 36, 535–539 (2011).
[CrossRef]

Li, J.

M. Zeng, J. Li, and Z. Peng, “The design of top-hat morphological filter and application to infrared target detection,” Infrared Phys. & Technology 48, 67–76 (2006).
[CrossRef]

Mao, S.

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

Marshall, S.

P. Kraft, S. Marshall, J. J. Soraghan, and N. R. Harvey, “Parallel genetic algorithms for optimizing morphological filters,” in Proceedings of the Fifth International Conference on Image Processing and Its Applications (1995), 762, CP410.
[CrossRef]

Mehmood, A.

Merchant, S. N.

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
[CrossRef]

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Air-borne approaching target detection and tracking in infrared image sequence,” in International Conference on Image Processing (ICIP) (2004), 2, 1025–1028.
[CrossRef]

Mira, J.

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

Nasrabadi, N. M.

Pecoul, E.

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

Peng, Z.

M. Zeng, J. Li, and Z. Peng, “The design of top-hat morphological filter and application to infrared target detection,” Infrared Phys. & Technology 48, 67–76 (2006).
[CrossRef]

Petit, M.

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

Podobna, Y.

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

Qian, X.

Z. Zhang, H. Sun, L. Yan, and X. Qian, “A synchronous imaging system for moving-target detection with bionic compound eyes,” in 2011 4th International Congress on Image and Signal Processing (CISP) (2011), 4, 1809–1812.
[CrossRef]

Ratches, J. A.

J. A. Ratches, “Review of current aided/automatic target acquisition technology for military target acquisition tasks,” Opt. Eng. 50, 072001 (2011).
[CrossRef]

Ratliff, F.

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Reed, S.

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

Réfrégier, Ph.

Ronda, V.

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

Sadjadi, F. A.

Schoonmaker, J.

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

Shao, Z.

Z. Shao and D. Li, “Adaptive target detection based on improved genetic algorithm in infrared images,” Geomatics and Information Science of Wuhan University 36, 535–539 (2011).
[CrossRef]

Son, J.-Y.

Soraghan, J. J.

P. Kraft, S. Marshall, J. J. Soraghan, and N. R. Harvey, “Parallel genetic algorithms for optimizing morphological filters,” in Proceedings of the Fifth International Conference on Image Processing and Its Applications (1995), 762, CP410.
[CrossRef]

Sun, H.

Z. Zhang, H. Sun, L. Yan, and X. Qian, “A synchronous imaging system for moving-target detection with bionic compound eyes,” in 2011 4th International Congress on Image and Signal Processing (CISP) (2011), 4, 1809–1812.
[CrossRef]

Sun, S.-G.

S.-G. Sun, “Target detection using local fuzzy thresholding and binary template matching in forward-looking infrared images,” Opt. Eng. 46, 036402 (2007).
[CrossRef]

Tao, S.

Z. Wu and S. Tao, “A recursive Bayesian method for multi-target detection and tracking using particle swarms,” Procedia Eng. 29, 4282–4286 (2012).
[CrossRef]

Toyoda, J.

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Uozumi, J.

P. Kaewkasi, J. Widjaja, and J. Uozumi, “Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator,” Opt. Commun. 271, 48–58 (2007).
[CrossRef]

Vasquez, E.

Vazquez, J.

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

Wang, W.

F. Chen and W. Wang, “Target recognition in clutter scene based on wavelet transform,” Opt. Commun. 282, 523–526 (2009).
[CrossRef]

Wang, X.

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

Widjaja, J.

P. Kaewkasi, J. Widjaja, and J. Uozumi, “Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator,” Opt. Commun. 271, 48–58 (2007).
[CrossRef]

Wu, J.

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

Wu, Z.

Z. Wu and S. Tao, “A recursive Bayesian method for multi-target detection and tracking using particle swarms,” Procedia Eng. 29, 4282–4286 (2012).
[CrossRef]

Xin, R.

R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).

Xue, B.

Yan, L.

Z. Zhang, H. Sun, L. Yan, and X. Qian, “A synchronous imaging system for moving-target detection with bionic compound eyes,” in 2011 4th International Congress on Image and Signal Processing (CISP) (2011), 4, 1809–1812.
[CrossRef]

Yeom, S.

Zaveri, M. A.

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
[CrossRef]

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Air-borne approaching target detection and tracking in infrared image sequence,” in International Conference on Image Processing (ICIP) (2004), 2, 1025–1028.
[CrossRef]

Zeng, M.

M. Zeng, J. Li, and Z. Peng, “The design of top-hat morphological filter and application to infrared target detection,” Infrared Phys. & Technology 48, 67–76 (2006).
[CrossRef]

Zhang, T.

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

Zhang, Z.

Z. Zhang, H. Sun, L. Yan, and X. Qian, “A synchronous imaging system for moving-target detection with bionic compound eyes,” in 2011 4th International Congress on Image and Signal Processing (CISP) (2011), 4, 1809–1812.
[CrossRef]

Zhou, F.

Acta Photonica Sinica

H. Huang and T. Jin, “Dim small targets detection with noise suppression utilizing adjacent relevant pixels information,” Acta Photonica Sinica 41, 596–601 (2012).
[CrossRef]

Appl. Opt.

Expert Systems with Applications

J. Mira, A. E. Delgado, A. Fernández-Caballero, and M. A. Fernández, “Knowledge modelling for the motion detection task: the algorithmic lateral inhibition method,” Expert Systems with Applications 27, 169–185 (2004).
[CrossRef]

Geomatics and Information Science of Wuhan University

Z. Shao and D. Li, “Adaptive target detection based on improved genetic algorithm in infrared images,” Geomatics and Information Science of Wuhan University 36, 535–539 (2011).
[CrossRef]

IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Wavelet-based detection and its application to tracking in an IR sequence,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Review 37, 1269–1286 (2007).
[CrossRef]

Infrared Phys. & Technology

M. Zeng, J. Li, and Z. Peng, “The design of top-hat morphological filter and application to infrared target detection,” Infrared Phys. & Technology 48, 67–76 (2006).
[CrossRef]

Natural Computation (ICNC)

R. Lei, S. Chaojian, and R. Xin, “Salient target detection method under sea surface environment based on multi-scale phase spectrum,” Natural Computation (ICNC) 2, 977–981 (2011).

Opt. Commun.

F. Chen and W. Wang, “Target recognition in clutter scene based on wavelet transform,” Opt. Commun. 282, 523–526 (2009).
[CrossRef]

P. Kaewkasi, J. Widjaja, and J. Uozumi, “Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator,” Opt. Commun. 271, 48–58 (2007).
[CrossRef]

Opt. Eng.

J. Wu, S. Mao, X. Wang, and T. Zhang, “Ship target detection and tracking in cluttered infrared imagery,” Opt. Eng. 50, 057207 (2011).
[CrossRef]

J. A. Ratches, “Review of current aided/automatic target acquisition technology for military target acquisition tasks,” Opt. Eng. 50, 072001 (2011).
[CrossRef]

S.-G. Sun, “Target detection using local fuzzy thresholding and binary template matching in forward-looking infrared images,” Opt. Eng. 46, 036402 (2007).
[CrossRef]

Opt. Express

Proc. SPIE

C. Corbane, E. Pecoul, L. Demagistri, and M. Petit, “Fully automated procedure for ship detection using optical satellite imagery,” Proc. SPIE 7150, 71500R (2008).
[CrossRef]

J. Schoonmaker, S. Reed, Y. Podobna, J. Vazquez, and C. Boucher, “A multispectral automatic target recognition application for maritime surveillance, search and rescue,” Proc. SPIE 7666, 76661V (2010).
[CrossRef]

S. D. Deshpande, M. H. Er, V. Ronda, and P. Chan, “Max-mean and max-median filters for detection of small targets,” Proc. SPIE 3809, 74–83 (1999).

Procedia Eng.

Z. Wu and S. Tao, “A recursive Bayesian method for multi-target detection and tracking using particle swarms,” Procedia Eng. 29, 4282–4286 (2012).
[CrossRef]

Science

F. Ratliff, B. W. Knight, J. Toyoda, and H. K. Hartline, “Enhancement of flicker by lateral inhibition,” Science 158, 392–393 (1967).
[CrossRef]

Other

M. A. Zaveri, S. N. Merchant, and U. B. Desai, “Air-borne approaching target detection and tracking in infrared image sequence,” in International Conference on Image Processing (ICIP) (2004), 2, 1025–1028.
[CrossRef]

Z. Zhang, H. Sun, L. Yan, and X. Qian, “A synchronous imaging system for moving-target detection with bionic compound eyes,” in 2011 4th International Congress on Image and Signal Processing (CISP) (2011), 4, 1809–1812.
[CrossRef]

P. Kraft, S. Marshall, J. J. Soraghan, and N. R. Harvey, “Parallel genetic algorithms for optimizing morphological filters,” in Proceedings of the Fifth International Conference on Image Processing and Its Applications (1995), 762, CP410.
[CrossRef]

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Figures (13)

Fig. 1.
Fig. 1.

Shape of constructed structuring elements b0, b1, and Δb.

Fig. 2.
Fig. 2.

Effect of size changing of structuring elements: (a) statistic of size changing of Δb (b1 is sized by fixed scale 12×12) and (b) statistic of size changing of b1 (Δb is sized by fixed scale 5×5).

Fig. 3.
Fig. 3.

Comparison of background estimation and suppression using different methods: (a) original image; (b) max-median filter (5×5); (c) classical top-hat transformation based on single structure element (5×5); (d) top-hat transformation using center-surround multiple structure elements at directions 0°, 45°, 90°, and 135°; and (e) our method.

Fig. 4.
Fig. 4.

Typical examples of the infrared image: (a) original image and (b) 3D plot image.

Fig. 5.
Fig. 5.

Weighted average guard operation (5×5).

Fig. 6.
Fig. 6.

Comparison of different methods: (a) bimodal Gaussian distribution, (b) anisotropic Gaussian distribution, and (c) LPI.

Fig. 7.
Fig. 7.

Results of relatively dark and bright target detection using our method. The second row and the fourth row are the corresponding 3D target intensity plots. (a), (e) Original image with dark and bright targets, respectively. (b), (f) Background suppression using modified top-hat reconstruction operation. (c), (g) LPI. (d), (h) Final results.

Fig. 8.
Fig. 8.

Results of target detection under sea and sky background with low clutter and super high clutter. The second row is the corresponding 3D target intensity plots. (a), (d) Original image with low clutters and high clutters, respectively. (b), (e) LPI. (c), (f) Results obtained by our method.

Fig. 9.
Fig. 9.

Comparison of results obtained from different methods: (a) Original image, (b) conventional top-hat transformation, (c) top-hat transformation with eight-neighborhood clustering, and (d) ARPD method.

Fig. 10.
Fig. 10.

(a) Result after modified top-hat reconstruction and LPI operation. (b) Final result obtained by our method.

Fig. 11.
Fig. 11.

Comparison of results obtained from different methods: (a) original image, (b) top-hat transformation, (c) APRD method, and (d) our method.

Fig. 12.
Fig. 12.

Comparison of results obtained from different methods: (a) original image; (b) top-hat transformation; (c) result of region grow method; (d), (e) 3D plot of (a), (b); and (f) seed image in region grow method.

Fig. 13.
Fig. 13.

(a) Results after modified top-hat reconstruction and LPI operation. (b) Final result obtained by our method.

Tables (2)

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Table 1. Comparison of SCR and GSCR

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Table 2. Comparison of Computation Complexity with Different Nwi (s)

Equations (15)

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f(x,y)=B(x,y)+T(x,y)+n(x,y),(1xM,1yN),
fΘb=min(f(x+u,y+v)b(u,v)),
fb=max(f(xu,yv)+b(u,v)),
(fb)=(fΘb)b,and
(fb)=(fb)Θb.
f(fb)=f(fΘb)b,
(fb)f=(fb)Θbf.
ftophat(x,y)=max(f(x,y)min(f(x,y),(fΔb)Θb1),0).
SCR=gtg¯localσlocal2,GSCR=SCR0SCRi,
H=(u,v)Nwi(M(u,v)m(u,v))2*C,
fLPI(x,y)=H*ftophat(x,y),
fLPI(x,y)=255*fLPI(x,y)minfLPI(x,y)maxfLPI(x,y)minfLPI(x,y).
μ=1N×Mi=1Nj=1MfLPI(i,j),
σ2=1N×Mi=1Nj=1M[fLPI(i,j)μ]2,
Δth=μ+σ×ε,

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