logo

SCIENCE CHINA Information Sciences, Volume 59, Issue 6: 062309(2016) https://doi.org/10.1007/s11432-015-5480-x

Novel estimators of equivalent number of looks in polarimetric SAR imagery based on sub-matrices

More info
  • ReceivedJul 30, 2015
  • AcceptedSep 14, 2015
  • PublishedApr 18, 2016

Abstract

The equivalent number of looks (ENL) is an important parameter in the multilook statistical model of polarimetric synthetic aperture radar (Pol-SAR). Recently, the maximum likelihood (ML) method was proposed and gave a good performance in the Gaussian model case by using the full covariance matrix instead of the intensity of Pol-SAR data, but it generated underestimates in the product model case. In this paper several novel ENL estimators are presented via certain cumulants of the log-determinant of the sub-matrices of the multilook polarimetric covariance matrix. The texture effect to the ENL estimates is eliminated, and the analytic estimators are derived. The estimators use the full covariance matrix and sub-matrices information, rather than the intensities of polarization channels. All the novel estimators are suitable for any texture model and thus provide more accurate results than many existing ones. Experiments using simulated data and real data are presented to evaluate the performance of different estimators. The results show that the second log-determinant moment (SLDM3)-based method is the best one among the novel estimators. At the same time this estimator has much less computational complexity. In addition, a novel distribution classification method is proposed by coloring the image via second- and third-order log-cumulants of the covariance matrix (MLC), which is helpful to assess the estimation result.


Funded by

National Natural Science Foundation of China(61372165)


Acknowledgment

Acknowledgments

The work was supported by National Natural Science Foundation of China (Grant No. 61372165).


References

[1] Anfinsen S N, Doulgeris A P, Eltoft T. IEEE Trans Geosci Remote Sens, 2009, 47: 3795-3809 Google Scholar

[2] Oliver C, Quegan S. Understanding Synthetic Aperture Radar Images. 2nd ed. Raleigh: Sci Tech Publishing, 2004. Google Scholar

[3] Cumming I G, Wong F H. Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Norwood: Artech House, 2005. Google Scholar

[4] Lee J-S, Grunes M R, Kwok R. Int J Remote Sens, 1994, 15: 229-231 Google Scholar

[5] Lee J-S, Grunes M R, Ainsworth T L, et al. IEEE Trans Geosci Remote Sens, 1999, 37: 2249-2259 Google Scholar

[6] Kersten P R, Lee J-S, Ainsworth T L. IEEE Trans Geosci Remote Sens, 2005, 43: 519-527 Google Scholar

[7] Frery A C, Correia A H, Freitas C C. IEEE Trans Geosci Remote Sens, 2007, 45: 3098-3109 Google Scholar

[8] Doulgeris A P, Anfinsen S N, Eltoft T. IEEE Trans Geosci Remote Sens, 2008, 46: 2999-3009 Google Scholar

[9] Conradsen K, Nielsen A A, Schou J, et al. IEEE Trans Geosci Remote Sens, 2003, 41: 4-19 Google Scholar

[10] Lee J-S, Schuler D L, Lang R H, et al. K-distribution for multi-look processed polarimetric SAR imagery. In: Proceedings of the IEEE International Geoscience Remote Sensing Symposium (IGARSS'94), Pasadena, 1994, 4: 2179--2181. Google Scholar

[11] Liu T, Cui H G, Xi Z M X, et al. IEEE Geosci Remote Sens Lett, 2014, 11: 1129-1133 Google Scholar

[12] Doulgeris A P, Anfinsen S N, Eltoft T. IEEE Trans Geosci Remote Sens, 2011, 49: 3665-3676 Google Scholar

[13] Liu T, Cui H G, Gao J. Acta Electron Sinica, 2013, 41: 1231-1237 Google Scholar

[14] Anfinsen S N, Eltoft T. IEEE Trans Geosci Remote Sens, 2011, 49: 2281-2295 Google Scholar

[15] Eltoft T, Anfinsen S N, Doulgeris A P. IEEE Trans Geosci Remote Sens, 2013, 52: 2910-2919 Google Scholar

[16] Maaref A, Aissa S. IEEE Trans Wirel Commun, 2007, 6: 3607-3619 Google Scholar

[17] Lee J-S, Hoppel K, Mango S A. Int J Imaging Syst Tech, 1992, 4: 298-305 Google Scholar

[18] Foucher S, Boucher J M, Benie G B. Maximum likelihood estimation of the number of looks in SAR images. In: Proceedings of the International Conference of Microwave, Radar and Wireless Communications, Wroclaw, 2000, 2: 657--660. Google Scholar

[19] Cui Y, Zhou G, Yang J, et al. IEEE Geosci Remote Sens Letts, 2011, 8: 710-714 Google Scholar

[20] Xu B, Cui Y, Zhou G, et al. IEICE Trans Commun, 2014, 97: 691-698 Google Scholar

[21] Anfinsen S N, Doulgeris A D, Eltoft T. IEEE Trans Geosci Remote Sens, 2011, 49: 2281-2295 Google Scholar

Copyright 2019 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1