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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 47, Iss. 16 — Jun. 1, 2008
  • pp: 3072–3079

Two-beam-coupling correlator for synthetic aperture radar image recognition with power-law scattering centers preenhancement

Bahareh Haji-saeed, Charles L. Woods, John Kierstead, and Jed Khoury  »View Author Affiliations


Applied Optics, Vol. 47, Issue 16, pp. 3072-3079 (2008)
http://dx.doi.org/10.1364/AO.47.003072


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Abstract

Synthetic radar image recognition is an area of interest for military applications including automatic target recognition, air traffic control, and remote sensing. Here a dynamic range compression two-beam-coupling joint transform correlator for detecting synthetic aperture radar targets is utilized. The joint input image consists of a prepower-law, enhanced scattering center of the input image and a linearly synthesized power-law-enhanced scattering center template. Enhancing the scattering center of both the synthetic template and the input image furnishes the conditions for achieving dynamic range compression correlation in two-beam coupling. Dynamic range compression (a) enhances the signal-to-noise ratio, (b) enhances the high frequencies relative to low frequencies, and (c) converts the noise to high frequency components. This improves the correlation-peak intensity to the mean of the surrounding noise significantly. Dynamic range compression correlation has already been demonstrated to outperform many optimal correlation filters in detecting signals in severe noise environments. The performance is evaluated via established metrics such as peak-to-correlation energy, Horner efficiency, and correlation-peak intensity. The results showed significant improvement as the power increased.

© 2008 Optical Society of America

OCIS Codes
(070.4550) Fourier optics and signal processing : Correlators
(100.5010) Image processing : Pattern recognition
(100.6740) Image processing : Synthetic discrimination functions

ToC Category:
Fourier Optics and Signal Processing

History
Original Manuscript: March 3, 2008
Revised Manuscript: April 10, 2008
Manuscript Accepted: April 18, 2008
Published: May 26, 2008

Citation
Bahareh Haji-saeed, Charles L. Woods, John Kierstead, and Jed Khoury, "Two-beam-coupling correlator for synthetic aperture radar image recognition with power-law scattering centers preenhancement," Appl. Opt. 47, 3072-3079 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-16-3072


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References

  1. B. G. Boone, Signal Processing Using Optics: Fundamentals, Devices, Architecture and Applications (Oxford U. Press, 1998), Chap. 11, pp. 281-311.
  2. R. Shenoy and D. P. Casasent, “Multiclass SAR feature space trajectory FST neural net class and pose estimation results,” Proc. SPIE 3070, 121-124 (1997). [CrossRef]
  3. R. Murenzi, D. Semwogerere, D. Johnson, L. M. Kaplan, and K. R. Namuduri, “Detection/recognition of targets in low-resolution FLIR images using 2D directional wavelets,” SPIE Automatic Target Recognition VIII AeroSense Conference(1998).
  4. S. A. Stanhope, E. Keydel, W. Williams, V. Rajilic, and R. Sieron, “The use of the mean squared error matching metric in a model based automatic target recognition system,” Proc. SPIE 3370, 360-368 (1998). [CrossRef]
  5. M. Boshra and B. Bhanu, “Performance modeling of feature-based classification in SAR imagery,” Proc. SPIE 3370, 661-674 (1998). [CrossRef]
  6. D. K. Barton, Modern Radar Systems Analysis (Artech House, 1988), p. 209.
  7. H. Urkowitz, Modern Radar Analysis Evaluation and System Design, R. S. Berkowitz, ed. (Wiley, 1965), Chap. 1, pp. 197-215.
  8. J. Khoury, P. D. Gianino, and C. L. Woods, “Synthetic aperture radar image correlation by use of preprocessing for enhancement of scattering centers,” Opt. Lett. 25, 1544-1546 (2000). [CrossRef]
  9. J. Khoury, P. D. Gianino, and C. L. Woods, “Optimal synthetic aperture radar image correlation using enhanced scattering centers in holographic data storage,” Opt. Eng. 40, 2624-2637 (2001). [CrossRef]
  10. J. L. Horner and P. D. Gianino, “Phase-only matched filtering,” Appl. Opt. 23, 812-816 (1984). [CrossRef] [PubMed]
  11. J. L. Horner and J. R. Leger, “Pattern recognition with binary phase-only filters,” Appl. Opt. 24, 609-611 (1985). [CrossRef] [PubMed]
  12. J. Khoury, J. Fu, M. Cronin-Golomb, and C. Woods, “Quadratic processing and nonlinear optical phase rectification in noise reduction,” J. Opt. Soc. Am. B 11, 1960-1971 (1994). [CrossRef]
  13. J. Khoury, M. Cronin-Golomb, P. Gianino, and C. Woods, “Photorefractive two-beam coupling nonlinear joint transform correlator,” J. Opt. Soc. Am. B 11, 2167-2174 (1994). [CrossRef]
  14. G. Asimellis, J. Khoury, and C. Woods, “Effects of saturation on the nonlinear incoherent-erasure joint-transform correlator,” J. Opt. Soc. Am. A 13, 1345-1356 (1996). [CrossRef]
  15. J. Khoury, G. Asimellis, P. D. Gianino, and C. L. Woods, “Nonlinear compansive noise reduction in joint transform correlators,” Opt. Eng. 37, 66-74 (1998). [CrossRef]
  16. M. S. Alam and J. S. Khoury, “Fringe-adjusted incoherent erasure joint transform correlator,” Opt. Eng. 37, 75-82 (1998). [CrossRef]
  17. B. Haji-saeed, S. K. Sengupta, W. D. Goodhue, J. Khoury, C. L. Woods, and J. Kierstead, “Dynamic range compression deconvolution using A-law and μ-law algorithms,” Proc. SPIE 65740, 65740D (2007). [CrossRef]
  18. B. Haji-saeed, S. K. Sengupta, W. Goodhue, J. Khoury, C. L. Woods, and J. Kierstead, “Nonlinear dynamic range compression deconvolution,” Opt. Lett. 31, 1969-1971 (2006). [CrossRef] [PubMed]
  19. B. Haji-saeed, W. D. Goodhue, J. Khoury, C. L. Woods, and J. Kierstead, “Dynamic range compression deconvolution,” in Frontiers in Optics (Optical Society of America, 2007).
  20. D. Casasent and S. Ashizawa, “Synthetic aperture radar detection, recognition and clutter rejection with minimum noise and correlation energy filters,” Opt. Eng. 36, 2729-2736(1997). [CrossRef]
  21. R. Shenoy and D. Casasent, “Eigen-MINACE detection filter with improved capacity,” Proc. SPIE 3370, 435-447 (1998). [CrossRef]
  22. J. G. Proakis and M. Salehi, Communication Systems Engineering (Prentice-Hall, 2002).
  23. W. B. Davenport and W. L. Root, An Introduction to the Theory of Random Signal and Noise (McGraw-Hill, 1958), Chap. 12-13, pp. 255-311.
  24. R. C. Gonzalez and R. E. Woods, Digital Image Processing (Prentice-Hall, 2002).
  25. http://hyperphysics.phy-astr.gsu.edu/hbase/audio/tape4.html#c2.

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