Abstract

Infrared (IR) imagery sequences are commonly used for detecting moving targets in the presence of evolving cloud clutter or background noise. This research concentrates on slow-moving point targets that are less than one pixel in size, such as aircraft at long ranges from a sensor. Because transmitting IR imagery sequences to a base unit or storing them consumes considerable time and resources, a compression method that maintains the point-target detection capabilities is highly desirable. In our previous work, we introduced two temporal compression methods that preserve the temporal profile properties of the point target in the form of discrete cosine transform (DCT) quantization and parabola fit. In the present work, we extend the compression task method of DCT quantization by applying spatial compression over the temporally compressed coefficients, which is followed by bit encoding. We evaluate the proposed compression method using a signal-to-noise ratio (SNR)–based measure for point target detection and find that it yields better results than the compression standard H.264. Furthermore, we introduce an automatic detection algorithm that extracts the target location from the SNR scores image, which is acquired during the evaluation process and has a probability of detection and a probability of false alarm close to those of the original sequences. We previously determined that it is necessary to establish a minimal noise level in the SNR-based measure to compensate for smoothing that is induced by the compression. Here, the noise level calculation process is modified in order to allow detection of targets traversing all background types.

© 2013 Optical Society of America

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References

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  1. R. Huber-Shalem, O. Hadar, S. R. Rotman, and M. Huber-Lerner, “Compression of infrared imagery sequences containing a slow moving point target,” Appl. Opt. 49, 3798–3813 (2010).
    [CrossRef]
  2. M. Bar-Tal and S. R. Rotman, “Performance measurement in point source target detection,” Infrared Phys. Technol. 37, 231–238 (1996).
    [CrossRef]
  3. S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
    [CrossRef]
  4. N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.
  5. R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
    [CrossRef]
  6. I. E. G. Richardson, Video Codec Design (Wiley, 2004), Chaps. 3, 4, 5, 7.
  7. http://www.sn.afrl.af.mil/pages/SNH/ir_sensor_branch/sequences.html .
  8. L. Varsano Rozenberg, “Point target tracking in hyperspectral images,” M. Sc. thesis, Ben-Gurion University of the Negev, June2005.
  9. C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
    [CrossRef]
  10. C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
    [CrossRef]
  11. C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
    [CrossRef]
  12. L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
    [CrossRef]
  13. C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
    [CrossRef]
  14. O. Nichtern and S. R. Rotman, “Parameter adjustment for a dynamic programming track-before-detect-based target detection algorithm,” EURASIP J. Appl. Signal Process. 2008, 146925 (2008).
    [CrossRef]
  15. B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
    [CrossRef]
  16. N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
    [CrossRef]
  17. G. Strang, “The discrete cosine transform,” SIAM Rev. 41, 135–147 (1999).
    [CrossRef]
  18. Z. Wang and B. Hunt, “The discrete W-transform,” Appl. Math. Comput. 16, 19–48 (1985).
    [CrossRef]
  19. D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. Inst. Radio Eng. 40, 1098–1101 (1952).
    [CrossRef]
  20. S. P. Lloyd, “Least squares quantization in PCM,” IEEE Trans. Inf. Theory 28(2), 129–137 (1982).
    [CrossRef]
  21. J. Max, “Quantizing for minimum distortion,” IRE Trans. Inf. Theory 6(1), 7–12 (1960).
    [CrossRef]
  22. R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
    [CrossRef]
  23. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Mathematics in Science and Engineering (Academic, 1988), Vol. 179, Chap. 4, pp. 123–149.

2011 (1)

B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
[CrossRef]

2010 (1)

2009 (1)

R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
[CrossRef]

2008 (1)

O. Nichtern and S. R. Rotman, “Parameter adjustment for a dynamic programming track-before-detect-based target detection algorithm,” EURASIP J. Appl. Signal Process. 2008, 146925 (2008).
[CrossRef]

2006 (1)

L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
[CrossRef]

2005 (1)

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

2001 (1)

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

2000 (2)

C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

1999 (1)

G. Strang, “The discrete cosine transform,” SIAM Rev. 41, 135–147 (1999).
[CrossRef]

1998 (1)

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

1996 (1)

M. Bar-Tal and S. R. Rotman, “Performance measurement in point source target detection,” Infrared Phys. Technol. 37, 231–238 (1996).
[CrossRef]

1995 (1)

C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
[CrossRef]

1985 (1)

Z. Wang and B. Hunt, “The discrete W-transform,” Appl. Math. Comput. 16, 19–48 (1985).
[CrossRef]

1982 (1)

S. P. Lloyd, “Least squares quantization in PCM,” IEEE Trans. Inf. Theory 28(2), 129–137 (1982).
[CrossRef]

1974 (1)

N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
[CrossRef]

1960 (1)

J. Max, “Quantizing for minimum distortion,” IRE Trans. Inf. Theory 6(1), 7–12 (1960).
[CrossRef]

1952 (1)

D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. Inst. Radio Eng. 40, 1098–1101 (1952).
[CrossRef]

Agrawal, A. K.

N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.

Ahmed, N.

N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
[CrossRef]

Aminov, B.

B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
[CrossRef]

Babu, H.

R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
[CrossRef]

Bar-Shalom, Y.

Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Mathematics in Science and Engineering (Academic, 1988), Vol. 179, Chap. 4, pp. 123–149.

Bar-Tal, M.

M. Bar-Tal and S. R. Rotman, “Performance measurement in point source target detection,” Infrared Phys. Technol. 37, 231–238 (1996).
[CrossRef]

Caefer, C. E.

C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
[CrossRef]

Chellappa, R.

N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.

Cohen, A.

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

DiSalvo, S.

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

Fortmann, T. E.

Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Mathematics in Science and Engineering (Academic, 1988), Vol. 179, Chap. 4, pp. 123–149.

Hadar, O.

Huber-Lerner, M.

Huber-Shalem, R.

Huffman, D. A.

D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. Inst. Radio Eng. 40, 1098–1101 (1952).
[CrossRef]

Hunt, B.

Z. Wang and B. Hunt, “The discrete W-transform,” Appl. Math. Comput. 16, 19–48 (1985).
[CrossRef]

Kumar, A.

R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
[CrossRef]

Lloyd, S. P.

S. P. Lloyd, “Least squares quantization in PCM,” IEEE Trans. Inf. Theory 28(2), 129–137 (1982).
[CrossRef]

Max, J.

J. Max, “Quantizing for minimum distortion,” IRE Trans. Inf. Theory 6(1), 7–12 (1960).
[CrossRef]

Mills, J. A.

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

Mooney, J. M.

C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
[CrossRef]

Natrajan, T.

N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
[CrossRef]

Nichtern, O.

B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
[CrossRef]

O. Nichtern and S. R. Rotman, “Parameter adjustment for a dynamic programming track-before-detect-based target detection algorithm,” EURASIP J. Appl. Signal Process. 2008, 146925 (2008).
[CrossRef]

Rao, K. R.

N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
[CrossRef]

Richard, S.

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

Richardson, I. E. G.

I. E. G. Richardson, Video Codec Design (Wiley, 2004), Chaps. 3, 4, 5, 7.

Rotman, S. R.

B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
[CrossRef]

R. Huber-Shalem, O. Hadar, S. R. Rotman, and M. Huber-Lerner, “Compression of infrared imagery sequences containing a slow moving point target,” Appl. Opt. 49, 3798–3813 (2010).
[CrossRef]

O. Nichtern and S. R. Rotman, “Parameter adjustment for a dynamic programming track-before-detect-based target detection algorithm,” EURASIP J. Appl. Signal Process. 2008, 146925 (2008).
[CrossRef]

L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
[CrossRef]

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

M. Bar-Tal and S. R. Rotman, “Performance measurement in point source target detection,” Infrared Phys. Technol. 37, 231–238 (1996).
[CrossRef]

Saran, R.

R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
[CrossRef]

Silverman, J.

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
[CrossRef]

Sims, F.

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

Strang, G.

G. Strang, “The discrete cosine transform,” SIAM Rev. 41, 135–147 (1999).
[CrossRef]

Succary, R.

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

Taylor, R. W.

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

Topiwala, P. N.

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

Varsano, L.

L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
[CrossRef]

Varsano Rozenberg, L.

L. Varsano Rozenberg, “Point target tracking in hyperspectral images,” M. Sc. thesis, Ben-Gurion University of the Negev, June2005.

Vaswani, N.

N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.

Wang, Z.

Z. Wang and B. Hunt, “The discrete W-transform,” Appl. Math. Comput. 16, 19–48 (1985).
[CrossRef]

Yaractzi, P.

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

Yatsker, I.

L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
[CrossRef]

Zheng, Q.

N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.

Appl. Math. Comput. (1)

Z. Wang and B. Hunt, “The discrete W-transform,” Appl. Math. Comput. 16, 19–48 (1985).
[CrossRef]

Appl. Opt. (1)

Def. Sci. J. (1)

R. Saran, H. Babu, and A. Kumar, “Median predictor-based lossless video compression algorithm for IR image sequences,” Def. Sci. J. 59, 183–188 (2009).
[CrossRef]

EURASIP J. Appl. Signal Process. (2)

O. Nichtern and S. R. Rotman, “Parameter adjustment for a dynamic programming track-before-detect-based target detection algorithm,” EURASIP J. Appl. Signal Process. 2008, 146925 (2008).
[CrossRef]

B. Aminov, O. Nichtern, and S. R. Rotman, “Spatial and temporal point tracking in real hyperspectral images,” EURASIP J. Appl. Signal Process. 2011, 30 (2011).
[CrossRef]

IEEE Trans. Aerosp. Electron. Syst. (1)

C. E. Caefer, J. Silverman, and J. M. Mooney, “Optimization of point target tracking filters,” IEEE Trans. Aerosp. Electron. Syst. 36, 15–25 (2000).
[CrossRef]

IEEE Trans. Comput. (1)

N. Ahmed, T. Natrajan, and K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput. C-23, 90–93 (1974).
[CrossRef]

IEEE Trans. Inf. Theory (1)

S. P. Lloyd, “Least squares quantization in PCM,” IEEE Trans. Inf. Theory 28(2), 129–137 (1982).
[CrossRef]

Infrared Phys. Technol. (1)

M. Bar-Tal and S. R. Rotman, “Performance measurement in point source target detection,” Infrared Phys. Technol. 37, 231–238 (1996).
[CrossRef]

IRE Trans. Inf. Theory (1)

J. Max, “Quantizing for minimum distortion,” IRE Trans. Inf. Theory 6(1), 7–12 (1960).
[CrossRef]

Opt. Eng. (2)

C. E. Caefer, J. M. Mooney, and J. Silverman, “Point target detection in consecutive frame staring IR imagery with evolving cloud clutter,” Opt. Eng. 34, 2772–2784 (1995).
[CrossRef]

L. Varsano, I. Yatsker, and S. R. Rotman, “Temporal target tracking in hyperspectral images,” Opt. Eng. 45, 126201 (2006).
[CrossRef]

Proc. Inst. Radio Eng. (1)

D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. Inst. Radio Eng. 40, 1098–1101 (1952).
[CrossRef]

Proc. SPIE (3)

C. E. Caefer, J. Silverman, J. M. Mooney, S. DiSalvo, and R. W. Taylor, “Temporal filtering for point target detection in staring IR imagery part I: damped sinusoid filters,” Proc. SPIE 3373, 111–122 (1998).
[CrossRef]

S. Richard, F. Sims, J. A. Mills, and P. N. Topiwala, “Evaluation of video compression for 8 and 12 bit IR data with H.264 fidelity range extensions,” Proc. SPIE 5807, 329–340 (2005).
[CrossRef]

R. Succary, A. Cohen, P. Yaractzi, and S. R. Rotman, “A dynamic programming algorithm for point target detection: practical parameters for DPA,” Proc. SPIE 4473, 96–100 (2001).
[CrossRef]

Proc. SPlE (1)

C. E. Caefer, J. Silverman, S. DiSalvo, and R. W. Taylor, “Post-processing of point target detection sinusoidal filters,” Proc. SPlE 4048, 104–111 (2000).
[CrossRef]

SIAM Rev. (1)

G. Strang, “The discrete cosine transform,” SIAM Rev. 41, 135–147 (1999).
[CrossRef]

Other (5)

N. Vaswani, A. K. Agrawal, Q. Zheng, and R. Chellappa, “Moving object detection and compression in IR sequences,” in Computer Vision beyond the Visible Spectrum (Springer, 2004), Chap. 5, pp. 141–165.

I. E. G. Richardson, Video Codec Design (Wiley, 2004), Chaps. 3, 4, 5, 7.

http://www.sn.afrl.af.mil/pages/SNH/ir_sensor_branch/sequences.html .

L. Varsano Rozenberg, “Point target tracking in hyperspectral images,” M. Sc. thesis, Ben-Gurion University of the Negev, June2005.

Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Mathematics in Science and Engineering (Academic, 1988), Vol. 179, Chap. 4, pp. 123–149.

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Figures (5)

Fig. 1.
Fig. 1.

STD of each pixel after zeroing the first DCT coefficients and calculating IDCT, for J13C. The STD values are bounded between 1 and 10. The target is at (138,200).

Fig. 2.
Fig. 2.

Block diagram for automatic detection of the target tracks.

Fig. 3.
Fig. 3.

J2A target pixel (203,267) profiles before and after DCT0.2 and DCT0.16 quantizations. The numbers in parentheses are the pixel locations (row, column).

Fig. 4.
Fig. 4.

Irregular noise pixel (6,1) of NA23A profiles before and after DCT0.2 and DCT0.16 quantizations. The numbers in parentheses are the pixel location (row, column).

Fig. 5.
Fig. 5.

Automatic target track detection of NA23A TMF using a pixel-score percentile threshold of 0.998.

Tables (9)

Tables Icon

Table 1. IR Imagery Sequence Characteristics

Tables Icon

Table 2. Movie Scores After Temporal DCT Quantization and Added WGN_DCT

Tables Icon

Table 3. Movie Size, Score, and TCR Before and After Temporal DCT Quantization, Followed by Spatial Quantization With and Without Spatial Differences, for J2A

Tables Icon

Table 4. Movie Scores After Temporal DCT Quantization, Followed by Spatial Uniform Quantization, and Adding WGN_DCT for Score Calculation

Tables Icon

Table 5. Movie Scores After Temporal DCT Quantization, Followed by Spatial L-M Quantization, and Adding WGN_DCT for Score Calculation

Tables Icon

Table 6. H.264 Compression Results With WGN_DCT Addition

Tables Icon

Table 7. Proposed Compression Results, Q=3

Tables Icon

Table 8. PD of Target-Track Detection Algorithm

Tables Icon

Table 9. PFA of Target-Track Detection Algorithm

Equations (7)

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

scorepixel=σ^max2/1Ki=1Kσ˜i2.
scoreblock(i)=E[v(iM)]E[v(iM)]std[v(iM)].
scoremovie=E[Scoreblock(iTB)]E[scoreblock(iTB)]std[scoreblock(iTB)].
TCR=Original_movie_sizeCompressed_movie_size.
vec_DCT=DCT(temporal_profile)vec_DCT_0=[0,,0,vec_DCT(q:end)]vec_IDCT=IDCT(vec_DCT_0)STD_of_WGN=inv(STD(vec_IDCT)).
Xq=X/Q·Q.
AR=WidthLength.

Metrics