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PIER PIER B PIER C PIER M PIER Letters
2013-03-08
Modeling SAR Images Based on a Generalized Gamma Distribution for Texture Component
By
Gui Gao,

    Dr. Gui Gao

    College of Electronic Science

    National University of Defense Technology

    China

    Homepage

Xianxiang Qin,

    Dr. Xianxiang Qin

    College of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Shilin Zhou

    Dr. Shilin Zhou

    College of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Progress In Electromagnetics Research, Vol. 137, 669-685, 2013
doi:10.2528/PIER13011807
Abstract
In the applications of synthetic aperture radar (SAR) data, a crucial problem is to develop precise models for the statistics of the pixel amplitudes or intensities. In this paper, a new statistical model, called simply here GΓΓ, is proposed based on the product model by assuming the radar cross section (RCS) components (texture components) of the return obey a recently empirical generalized Gamma distribution. Meanwhile, we demonstrate theoretically that the proposed GΓΓ model has the well-known K and g0 distributions as special cases. We also derived analytically the estimators of the presented GΓΓ model by applying the "method-of-log-cumulants" (MoLC). Finally, the performance of the proposed model is tested by using some measured SAR images.
Citation
Gui Gao, Xianxiang Qin, and Shilin Zhou, "Modeling SAR Images Based on a Generalized Gamma Distribution for Texture Component," Progress In Electromagnetics Research, Vol. 137, 669-685, 2013.
doi:10.2528/PIER13011807
References

1. Chan, Y. K. and V. C. Koo, "An introduction to synthetic aperture radar (SAR)," Progress In Electromagnetics Research B, Vol. 2, 27-60, 2008.
doi:10.2528/PIERB07110101

2. Feng, L., H. P. Xu, C. S. Li, S. Li, and H. Gao, "A novel estimation approach of dynamic and coupling baseline for distributed satellite SAR," Progress In Electromagnetics Research, Vol. 123, 467-484, 2012.
doi:10.2528/PIER11083105

3. Koo, V. C., Y. K. Chan, V. Gobi, M. Y. Chua, C. H. Lim, C. S. Lim, C. C. Thum, T. S. Lim, Z. Bin Ahmad, K. A. Mahmood, M. H. Bin Shahid, C. Y. Ang, W. Q. Tan, P. N. Tan, K. S. Yee, W. G. Cheaw, H. S. Boey, A. L. Choo, and B. C. Sew, "A new unmanned aerial vehicle synthetic aperture radar for environmental monitoring," Progress In Electromagnetics Research, Vol. 122, 245-268, 2012.
doi:10.2528/PIER11092604

5. Du, Y., Y. L. Luo, W. Z. Yan, and J. A. Kong, "An electromagnetic scattering model for soybean canopy," Progress In Electromagnetics Research, Vol. 79, 209-223, 2008.
doi:10.2528/PIER07101603

6. Zhao, Y. W., M. Zhang, X. P. Geng, and P. Zhou, "A comprehensive facet model for bistatic SAR imagery of dynamic ocean scene," Progress In Electromagnetics Research, Vol. 123, 427-445, 2012.
doi:10.2528/PIER11100910

7. Albert, M. D., Y. J. Lee, H. T. Ewe, and H. T. Chuah, "Multilayer model formulation and analysis of radar backscattering from sea ice," Progress In Electromagnetics Research, Vol. 128, 267-290, 2012.

8. Bausssard, A., M. Rochdi, and A. Khenchaf, "Po/mec-based scattering model for complex objects on a sea surface," Progress In Electromagnetics Research, Vol. 111, 229-251, 2011.
doi:10.2528/PIER10083005

9. Mohammadpoor, M., R. S. A. Raja Abdullah, A. Ismail, and A. F. Abas, "A circular synthetic aperture radar for on-the-ground object detection," Progress In Electromagnetics Research, Vol. 122, 269-292, 2012.
doi:10.2528/PIER11082201

10. Tian, B., D. Y. Zhu, and Z. D. Zhu, "A novel moving target detection approach for dual-channel SAR system," Progress In Electromagnetics Research, Vol. 115, 191-206, 2011.

11. Park, S. H., J. H. Lee, and K. T. Kim, "Performance analysis of the scenario-based construction method for real target ISAR recognition progress," Progress In Electromagnetics Research, Vol. 128, 137-151, 2012.

12. Chang, Y. L., C. Y. Chiang, and K.-S. Chen, "SAR image simulation with application to target recognition," Progress In Electromagnetics Research, Vol. 119, 35-57, 2011.
doi:10.2528/PIER11061507

13. Park, J. I. and K. T. Kim, "A comparative study on ISAR imaging algorithms for radar target identification," Progress In Electromagnetics Research, Vol. 108, 155-175, 2010.
doi:10.2528/PIER10071901

14. Frery, A. C., H. J. Muller, C. D. Costa, C. D. C. F. Yanasse, and S. J. S. Sant' Anna, "A model for extremely heterogeneous clutter," IEEE Transactions on Geoscience and Remote Sensing, Vol. 35, No. 3, 648-659, 1997.
doi:10.1109/36.581981

15. Gao, G., "Statistical modeling of SAR images: A survey," Sensors , Vol. 10, 775-795, 2010.
doi:10.3390/s100100775

16. Zhang, Y. D., L. N. Wu, and G. Wei, "A new classiffer for polarimetric SAR images," Progress In Electromagnetics Research, Vol. 94, 83-104, 2009.
doi:10.2528/PIER09041905

17. Oliver, C. J., Understanding Synthetic Aperture Radar Images, Artech House Boston, London, USA, UK, 1998.

18. Tison, C., J. M. Nicolas, F. Tupin, and H. Maitre, "A new statistical model for Markovian classification of urban areas in high-resolution SAR images," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 10, 2046-2057, 2004.
doi:10.1109/TGRS.2004.834630

19. Gao, G., "A parzen-window-kernel-based CFAR algorithm for ship detection in SAR images," IEEE Geoscience and Remote Sensing Letters, Vol. 8, No. 3, 557-561, 2011.
doi:10.1109/LGRS.2010.2090492

20. Moser, G., J. Zerubia, and S. B. Serpico, "Dictionary-based stochastic expectation-maximization for SAR amplitude probability density function estimation," IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, No. 1, 188-200, 2006.
doi:10.1109/TGRS.2005.859349

21. Luo, M. and K. M. Huang, "Prediction of the electromagnetic field in metallic enclosures using artificial neural networks," Progress In Electromagnetics Research, Vol. 116, 171-184, 2011.

22. Castaldi, G., V. Galdi, and G. Gerini, "Evaluation of a neural network-based adaptive beamforming scheme with magnitude-only constraints," Progress In Electromagnetics Research B, Vol. 11, 1-14, 2009.
doi:10.2528/PIERB08092303

23. Li, X. and J. Gao, "Pad modeling by using artificial neural network," Progress In Electromagnetics Research, Vol. 74, 167-180, 2007.
doi:10.2528/PIER07041201

24. Tan, C. P., J. Y. Koay, K. S. Lim, H. T. Ewe, and H. T. Chuah, "Classification of multi-temporal SAR images for rice crops using combined entropy decomposition and support vector machine technique," Progress In Electromagnetics Research, Vol. 71, 19-39, 2007.
doi:10.2528/PIER07012903

25. McLachlan, G. J. and D. Peel, Finite Mixture Models, Wiely, New York, 2000.

26. Jin, Y. Q., "Polarimetric scattering modeling and information retrieval of SAR remote sensing - A review of FDU work," Progress In Electromagnetics Research, Vol. 104, 333-384, 2010.
doi:10.2528/PIER10020101

27. Liu, D., Y. Du, G. Sun, W. Z. Yan, and B. I. Wu, "Analysis of InSAR sensitivity to forest structure based on radar scattering model," Progress In Electromagnetics Research, Vol. 84, 149-171, 2008.
doi:10.2528/PIER08071802

28. Tan, C. P., J. Y. Koay, K. S. Lim, H. T. Ewe, and H. T. Chuah, "Classification of multi-temporal SAR images for rice crops using combined entropy decomposition and support vector machine technique," Progress In Electromagnetics Research, Vol. 71, 19-39, 2007.
doi:10.2528/PIER07012903

29. Li, H. C., W. Hong, Y. R. Wu, and P. Z. Fan, "On the Empirical-statistical modeling of SAR images with generalized gamma distribution," IEEE J. Sel. Top. Signal Process., Vol. 5, No. 3, 386-397, 2011.
doi:10.1109/JSTSP.2011.2138675

30. Nicolas, J. M., "Introduction to second kind statistic: Application of log-moments and log-cumulants to SAR image law analysis," Trait. Signal, Vol. 19, No. 3, 139-167, 2002.

31. Liu, Z. L. and J. Yang, "Analysis of electromagnetic scattering with higher-order moment method and nurbs model," Progress In Electromagnetics Research, Vol. 96, 83-100, 2009.
doi:10.2528/PIER09071704

32. Varmazyar, S. H, M. Naser-Moghadasi, and Z. Masouri, "A moment method simulation of electromagnetic scattering from conducting bodies," Progress In Electromagnetics Research, Vol. 81, 99-119, 2008.
doi:10.2528/PIER07122502

33. Wang, S., X. Guan, D. W. Wang, X. Ma, and Y. Su, "Electromagnetic scattering by mixed conducting/dielectric objects using higher-order MoM," Progress In Electromagnetics Research, Vol. 66, 51-63, 2006.
doi:10.2528/PIER06092101

34. Gradshteyn, S. I. and I. M. Ryzhik, "Table of Integrals, Series, and Products," 7th Edition, Academic Press, San Diego, CA, 2007.

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