Vol. 31
Latest Volume
All Volumes
PIER 179 [2024] PIER 178 [2023] PIER 177 [2023] PIER 176 [2023] PIER 175 [2022] PIER 174 [2022] PIER 173 [2022] PIER 172 [2021] PIER 171 [2021] PIER 170 [2021] PIER 169 [2020] PIER 168 [2020] PIER 167 [2020] PIER 166 [2019] PIER 165 [2019] PIER 164 [2019] PIER 163 [2018] PIER 162 [2018] PIER 161 [2018] PIER 160 [2017] PIER 159 [2017] PIER 158 [2017] PIER 157 [2016] PIER 156 [2016] PIER 155 [2016] PIER 154 [2015] PIER 153 [2015] PIER 152 [2015] PIER 151 [2015] PIER 150 [2015] PIER 149 [2014] PIER 148 [2014] PIER 147 [2014] PIER 146 [2014] PIER 145 [2014] PIER 144 [2014] PIER 143 [2013] PIER 142 [2013] PIER 141 [2013] PIER 140 [2013] PIER 139 [2013] PIER 138 [2013] PIER 137 [2013] PIER 136 [2013] PIER 135 [2013] PIER 134 [2013] PIER 133 [2013] PIER 132 [2012] PIER 131 [2012] PIER 130 [2012] PIER 129 [2012] PIER 128 [2012] PIER 127 [2012] PIER 126 [2012] PIER 125 [2012] PIER 124 [2012] PIER 123 [2012] PIER 122 [2012] PIER 121 [2011] PIER 120 [2011] PIER 119 [2011] PIER 118 [2011] PIER 117 [2011] PIER 116 [2011] PIER 115 [2011] PIER 114 [2011] PIER 113 [2011] PIER 112 [2011] PIER 111 [2011] PIER 110 [2010] PIER 109 [2010] PIER 108 [2010] PIER 107 [2010] PIER 106 [2010] PIER 105 [2010] PIER 104 [2010] PIER 103 [2010] PIER 102 [2010] PIER 101 [2010] PIER 100 [2010] PIER 99 [2009] PIER 98 [2009] PIER 97 [2009] PIER 96 [2009] PIER 95 [2009] PIER 94 [2009] PIER 93 [2009] PIER 92 [2009] PIER 91 [2009] PIER 90 [2009] PIER 89 [2009] PIER 88 [2008] PIER 87 [2008] PIER 86 [2008] PIER 85 [2008] PIER 84 [2008] PIER 83 [2008] PIER 82 [2008] PIER 81 [2008] PIER 80 [2008] PIER 79 [2008] PIER 78 [2008] PIER 77 [2007] PIER 76 [2007] PIER 75 [2007] PIER 74 [2007] PIER 73 [2007] PIER 72 [2007] PIER 71 [2007] PIER 70 [2007] PIER 69 [2007] PIER 68 [2007] PIER 67 [2007] PIER 66 [2006] PIER 65 [2006] PIER 64 [2006] PIER 63 [2006] PIER 62 [2006] PIER 61 [2006] PIER 60 [2006] PIER 59 [2006] PIER 58 [2006] PIER 57 [2006] PIER 56 [2006] PIER 55 [2005] PIER 54 [2005] PIER 53 [2005] PIER 52 [2005] PIER 51 [2005] PIER 50 [2005] PIER 49 [2004] PIER 48 [2004] PIER 47 [2004] PIER 46 [2004] PIER 45 [2004] PIER 44 [2004] PIER 43 [2003] PIER 42 [2003] PIER 41 [2003] PIER 40 [2003] PIER 39 [2003] PIER 38 [2002] PIER 37 [2002] PIER 36 [2002] PIER 35 [2002] PIER 34 [2001] PIER 33 [2001] PIER 32 [2001] PIER 31 [2001] PIER 30 [2001] PIER 29 [2000] PIER 28 [2000] PIER 27 [2000] PIER 26 [2000] PIER 25 [2000] PIER 24 [1999] PIER 23 [1999] PIER 22 [1999] PIER 21 [1999] PIER 20 [1998] PIER 19 [1998] PIER 18 [1998] PIER 17 [1997] PIER 16 [1997] PIER 15 [1997] PIER 14 [1996] PIER 13 [1996] PIER 12 [1996] PIER 11 [1995] PIER 10 [1995] PIER 09 [1994] PIER 08 [1994] PIER 07 [1993] PIER 06 [1992] PIER 05 [1991] PIER 04 [1991] PIER 03 [1990] PIER 02 [1990] PIER 01 [1989]
0000-00-00
Dual Frequency Polarimetric SAR Data Classification and Analysis
By
, Vol. 31, 247-272, 2001
Abstract
In this paper, we introduce a new classification scheme for dual frequency polarimetric SAR data sets. A (6×6) polarimetric coherency matrix is defined to simultaneously take into account the full polarimetric information from both images. This matrix is composed of the two coherency matrices and their cross-correlation. A decomposition theorem is applied to both images to obtain 64 initial clusters based on their scattering characteristics. The data sets are then classified by an iterative algorithm based on a complex Wishart density function of the 6 by 6 matrix. A class number reduction technique is then applied on the 64 resulting clusters to improve the efficiency of the interpretation and representation of each class characteristics. An alternative technique is also proposed which introduces the polarimetric cross-correlation information to refine the results of classification to a small number of clusters using the conditional probability of the crosscorrelation matrix. The analysis of the resulting clusters is realized by determining the rigorous change in polarimetric properties from one image to the other. The polarimetric variations are parameterized by 8 real coefficients derived from the decomposition of a special unitary operator on the Gell-Mann basis. These classification and analysis schemes are applied to full polarimetric P, L, and C bands SAR images of the Nezer forest acquired by NASA/JPL AIRSAR sensor (1989).
Citation
Laurent Ferro-Famil, and Eric Pottier, "Dual Frequency Polarimetric SAR Data Classification and Analysis," , Vol. 31, 247-272, 2001.
doi:10.2528/PIER00081601
References

1. Rignot, E., R. Chellappa, and P. Dubois, "Unsupervised segmentation of polarimetric SAR data using the covariance matrix," IEEE Transactions on Geoscience and Remote Sensing, Vol. 30, No. 4, 697-705, July 1992.
doi:10.1109/36.158863

2. Zebker, H. A., J. J. van Zyl, S. L. Durden, and L. Norikane, "Calibrated imaging radar Polarimetry: techniques examples and applications," IEEE Transactions on Geoscience and Remote Sensing, Vol. 29, 942-961, 1991.
doi:10.1109/36.101373

3. Hara, R., G. Atkins, S. H. Yueh, R. T. Shin, and J. A. Kong, "Application of neural networks to radar image classification," IEEE Transactions on Geoscience and Remote Sensing, Vol. 32, 100-110, January 1994.
doi:10.1109/36.285193

4. van Zyl, J. J. and C. F. Burnette, "Bayesian classification of polarimetric SAR images using adaptive a-priori probabilities," International Journal of Remote Sensing, Vol. 13, 835-840, 1992.
doi:10.1080/01431169208904157

5. Pottier, E., "On full polarimetric target decomposition theorems with application to classification and identification of real target cross section," Proceedings of International Radar Conference, 330-335, Paris, May 1994.

6. van Zyl, J. J., "Unsupervised classification of scattering behavior using radar polarimetry data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 27, 36-45, 1989.
doi:10.1109/36.20273

7. Boerner, W. M., et al. "Polarimetry in radar remote sensing: basic and applied concepts," Chapter 5 Principles and Applications of Imaging Radar, The Manual of Remote Sensing, 3rd Edition, The American Society for Photogrammetry and Remote Sensing, March 1998.

8. Huynen, J. R., "Phenomenological theory of radar targets,", Ph.D. dissertation, Drukkerij Bronder-offset, N. V. Rotterdam, 1970.

9. Cloude, S. R. and E. Pottier, "A review of target decomposition theorems in radar polarimetry," IEEE Transactions on Geoscience and Remote Sensing, Vol. 34, No. 2, 498-518, September 1995.
doi:10.1109/36.485127

10. Cloude, S. R. and E. Pottier, "An entropy based classification scheme for land applications of polarimetric SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 35, No. 1, 68-78, January 1997.
doi:10.1109/36.551935

11. Freeman, A. and S. Durden, "A three component scattering model to describe polarimetric SAR data," SPIE, Vol. 1748, 213-225, Radar Polarimetry, 1992.

12. Dong, Y., B. Forster, and C. Ticehurst, "A new decomposition of radar polarization signatures," IEEE Trans. Geoscience and Remote Sensing, Vol. 36, No. 3, 933-939, 1998.
doi:10.1109/36.673684

13. Shi, J. and J. Dozier, "On estimation of snow water equivalence using SIR-C/X-SAR," proceedings of the Second International Workshop on Retrieval of Bio- and Geo-physical Parameters from SAR Data for Land Application, Noordwijk, The Netherlands, October 1998.

14. Floricioiu, D. M., "Polarimetric signatures and classification of alpine terrain by means of SIR-C/X-SAR,", Ph.D. dissertation, Innsbruck, Austria, 1997.

15. Chen, K. S., et al. "Classification of multifrequency polarimetric SAP, image using a dynamic learning neural network," IEEE Trans. Geoscience and Remote Sensing, Vol. 34, No. 3, 814-820, 1996.
doi:10.1109/36.499786

16. Freeman, A., S. Durden, and R. Zimmerman, "Mapping Sub- Tropical vegetation using Multi-Frequency Multi-Polarization SAR data," Proceedings of IGARSS, 1686-1689, Houston, USA, June 1992.

17. Lee, J. S., M. R. Grunes, and R. Kwok, "Classification of multilook polarimetric SAR imagery based on the complex Wishart distribution," International Journal of Remote Sensing, Vol. 15, No. 11, 2299-2311, 1994.
doi:10.1080/01431169408954244

18. Kong, J. A., S. H. Yueh, R. T. Shin, and J. J. van Zyl, "Classification of earth terrain using polarimetric synthetic aperture radar images," Chapter 6 in PIER, Vol. 3, J. A. Kong (Ed.), Elsevier 1990.

19. Lee, J. S., M. R. Grunes, T. L. Ainsworth, L. Du, D. L. Schuler, and S. R. Cloude, "Unsupervised classification of polarimetric SAR images by applying target decomposition and complex wishart distribution," IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 5, 2249-2258, Sept. 1999, also proceedings of the Fourth International Workshop on Radar Polarimetry, PIERS 1998, 13–17, Nantes, France, July 1998.
doi:10.1109/36.789621

20. Cloude, S. R. and K. P. Papathanassiou, "Polarimetric SAR interferometry," IEEE Trans. Geoscience and Remote Sensing, Vol. 36, No. 5, 1551-1565, 1998.
doi:10.1109/36.718859

21. Ferro-Famil, L., E. Pottier, J. P. Dedieu, C. Corgier, and J. Saillard, "Application of polarimetric SAR data processing to snow cover remote sensing. Validation using optical images and ground data," proceedings of the Committee on Earth Observing Satellites SAR Workshop, 26-29, CNES, Toulouse, France, October 1999.

22. Goodman, N. R., "Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction)," Ann. Math. Statist., Vol. 34, 152-177, 1963.
doi:10.1214/aoms/1177704250

23. Muirhead, R. J., Aspects of Multivariate Statistical Theory, John Wiley and Sons, New-York, ISBN 0-471-094442-0.

24. Pottier, E. and J. S. Lee, "Application of the H/A/alpha polarimetric decomposition theorem for unsupervised classification of fully polarimetric SAR data based on the wishart distribution," proceedings of the Committee on Earth Observing Satellites SAR Workshop, 26-29, CNES, Toulouse, France, October 1999.

25. Cloude, S. R., "Group theory and polarization algebra," OPTIK, Vol. 75, No. 1, 26-36, January 1986.

26. Joshi, A. W., Elements of Group Theory for Physicists, Wiley Eastern Limited, New Delhi, September 1988.

27. Cloude, S. R., "Lie groups in electromagnetic wave propagation and scattering," Journal of Electromagnetic Waves and Applications, Vol. 6, No. 8, 947-974, 1992.

28. Cloude, S. R. and E. Pottier, "Matrix difference operators as classifiers in polarimetric radar imaging," L’Onde Electrique, Vol. 74, No. 3, 34-40, May–June 1994.