Abstract

We present what we believe to be a novel method based on pseudo-Wigner–Ville distribution (PWVD) and Rényi entropy for salient targets detection. In the foundation of studying the statistical property of Rényi entropy via PWVD, the residual entropy-based saliency map of an input image can be obtained. From the saliency map, target detection is completed by the simple and convenient threshold segmentation. Experimental results demonstrate the proposed method can detect targets effectively in complex ground scenes.

© 2010 Optical Society of America

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    [CrossRef]
  7. S. Gabarda and G. Cristóbal, J. Opt. Soc. Am. A 24, B42 (2007).
    [CrossRef]
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    [CrossRef]
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  10. S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.
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    [CrossRef]
  12. http://www.saliencytoolbox.net.
  13. http://bcmi.sjtu.edu.cn/~houxiaodi/.

2008 (1)

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

2007 (2)

2006 (1)

2005 (1)

2003 (1)

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

2001 (2)

L. Stankovic, Signal Process. 81, 621 (2001).
[CrossRef]

L. Itti, C. Gold, and C. Koch, Opt. Eng. (Bellingham) 40, 1784 (2001).
[CrossRef]

1998 (1)

L. Itti, C. Koch, and E. Niebur, IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254 (1998).
[CrossRef]

1991 (1)

W. J. Williams, M. L. Brown, and A. O. Hero, Proc. SPIE 1566, 144 (1991).
[CrossRef]

Brown, M. L.

W. J. Williams, M. L. Brown, and A. O. Hero, Proc. SPIE 1566, 144 (1991).
[CrossRef]

Cristóbal, G.

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

S. Gabarda and G. Cristóbal, J. Opt. Soc. Am. A 24, B42 (2007).
[CrossRef]

S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.

Fischer, S.

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

Gabarda, S.

S. Gabarda and G. Cristóbal, J. Opt. Soc. Am. A 24, B42 (2007).
[CrossRef]

S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.

Gold, C.

L. Itti, C. Gold, and C. Koch, Opt. Eng. (Bellingham) 40, 1784 (2001).
[CrossRef]

Hero, A. O.

W. J. Williams, M. L. Brown, and A. O. Hero, Proc. SPIE 1566, 144 (1991).
[CrossRef]

Hou, X.

X. Hou and L. Zhang, Proc. IEEE 1, 1 (2007).

Itti, L.

L. Itti, C. Gold, and C. Koch, Opt. Eng. (Bellingham) 40, 1784 (2001).
[CrossRef]

L. Itti, C. Koch, and E. Niebur, IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254 (1998).
[CrossRef]

Ko, B. C.

Koch, C.

L. Itti, C. Gold, and C. Koch, Opt. Eng. (Bellingham) 40, 1784 (2001).
[CrossRef]

L. Itti, C. Koch, and E. Niebur, IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254 (1998).
[CrossRef]

Kovács, L.

Lee, A. B.

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

Martínez-Alajarín, J.

S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.

Nam, J. Y.

Niebur, E.

L. Itti, C. Koch, and E. Niebur, IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254 (1998).
[CrossRef]

Redondo, R.

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

Ruiz-Merino, R.

S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.

Simoncelli, E. P.

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

Srivastava, A.

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

Šroubek, F.

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

Stankovic, L.

L. Stankovic, Signal Process. 81, 621 (2001).
[CrossRef]

Szirányi, T.

Williams, W. J.

W. J. Williams, M. L. Brown, and A. O. Hero, Proc. SPIE 1566, 144 (1991).
[CrossRef]

Zhang, L.

X. Hou and L. Zhang, Proc. IEEE 1, 1 (2007).

Zhu, S. C.

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

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

L. Itti, C. Koch, and E. Niebur, IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254 (1998).
[CrossRef]

J. Math. Imaging Vision (1)

A. Srivastava, A. B. Lee, E. P. Simoncelli, and S. C. Zhu, J. Math. Imaging Vision 18, 17 (2003).
[CrossRef]

J. Opt. Soc. Am. A (2)

J. Visual Commun. Image Represent (1)

R. Redondo, S. Fischer, F. Šroubek, and G. Cristóbal, J. Visual Commun. Image Represent 19, 12 (2008).
[CrossRef]

Opt. Eng. (Bellingham) (1)

L. Itti, C. Gold, and C. Koch, Opt. Eng. (Bellingham) 40, 1784 (2001).
[CrossRef]

Opt. Lett. (1)

Proc. IEEE (1)

X. Hou and L. Zhang, Proc. IEEE 1, 1 (2007).

Proc. SPIE (1)

W. J. Williams, M. L. Brown, and A. O. Hero, Proc. SPIE 1566, 144 (1991).
[CrossRef]

Signal Process. (1)

L. Stankovic, Signal Process. 81, 621 (2001).
[CrossRef]

Other (3)

S. Gabarda, G. Cristóbal, J. Martínez-Alajarín, and R. Ruiz-Merino, in 14th European Signal Processing Conference (2006), pp. 1-5.

http://www.saliencytoolbox.net.

http://bcmi.sjtu.edu.cn/~houxiaodi/.

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Figures (3)

Fig. 1
Fig. 1

Example of relationship between normalized Rényi entropy using 1D PWVD and occurrence probability.

Fig. 2
Fig. 2

Averaged curves using 1D PWVD of 50 images.

Fig. 3
Fig. 3

Saliency maps and detection results: (a1)–(a4) original images; (b1)–(b4) saliency maps of Itti’s method; (c1)–(c4) detection results of Itti’s method; (d1)–(d4) saliency maps of Hou’s method; (e1)–(e4) detection results of Hou’s method; (f1)–(f4) saliency maps of our method using 1D PWVD; (g1)–(g4) detection results of our method using 1D PWVD; (h1)–(h4) saliency maps of our method using 2D PWVD; (i1)–(i4) detection results of our method using 2D PWVD.

Equations (8)

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W ( n , m ) = 2 k = N / 2 N / 2 z ( n + k ) z ( n k ) exp [ 2 i ( 2 π m N ) k ] ,
R 3 = 1 2 log 2 ( n m P 3 ( n , m ) ) ,
P ( n , m ) = W ( n , k ) W ( n , k ) ,     P ( n , m ) = P ( n , m ) / m P ( n , m ) .
R 3 ( n ) = 1 2 log 2 ( m P n 3 ( m ) ) .
R ( f ) = h a R ( f ) ,
Δ R ( f ) = abs ( R ( f ) R ( f ) ) ,
S ( f ) = h g Δ R ( f ) ,
O ( f ) = { 1 , S ( f ) > threshold 0 , otherwise } .

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