Use of sub-aperture decomposition for supervised PolSAR classification in urban area

Remote Sensing

Volumn 7, Issue 2, 2015, Pages 1380-1396

  Deng, Lei ^a   Yan, Ya Nan ^a   Sun, Chen ^a  

^a CAPITAL NORMAL UNIVERSITY   (China)

Author keywords

Decision tree; Polarimetric decomposition; Polarimetric SAR; Sub aperture decomposition

Indexed keywords

DATA MINING; DECISION TREES; EXTRACTION; FEATURE EXTRACTION; IMAGE CLASSIFICATION; POLARIMETERS; SUPPORT VECTOR MACHINES; SYNTHETIC APERTURE RADAR;

DECISION TREE CLASSIFICATION; DECISION TREE CLASSIFIERS; DECISION-TREE ALGORITHM; FEATURE SELECTION AND CONSTRUCTION; POLARIMETRIC DECOMPOSITION; POLARIMETRIC SAR; SUB-APERTURES; SUPERVISED CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 84928809938     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs70201380     Document Type: Article

References (31)

1. Yu, J.; Yan, Q.; Zhang, Z.; Ke, H.; Zhao, Z.; Wang, W. Unsupervised classification of polarimetric synthetic aperture radar images using kernel fuzzy c-means clustering. Int. J. Image Data Fusion 2012, 3, 319-332.
2. Brook, A.; Ben-Dor, E.; Richter, R. Modelling and monitoring urban built environment via multi-source integrated and fused remote sensing data. Int. J. Image Data Fusion 2013, 4, 2-32.
3. Dickinson, C.; Siqueira, P.; Clewley, D.; Richard, L. Classification of forest composition using polarimetric decomposition in multiple landscapes. Remote Sens. Environ. 2013, 131, 206-214.
4. Boerner, W.M.; Yan, W.-L.; Xi, A.Q.; Yamaguchi, Y. On the basic principles of radar polarimetry: The target characteristic polarization state theory of kennaugh, huynen's polarization fork concept, and its extension to the partially polarized case. IEEE Proc. 1991, 79, 1538-1550.
5. Del Frate, F.; Latini, D.; Pratola, C.; Palazzo, F. Pcnn for automatic segmentation and information extraction from x-band sar imagery. Int. J. Image Data Fusion 2013, 4, 75-88.
6. Vanzyl, J.J. Unsupervised classification of scattering behavior using radar polarimetry data. IEEE Trans. Geosci. Remote Sens. 1989, 27, 36-45.
7. Park, S.E.; Moon, W.M. Unsupervised classification of scattering mechanisms in polarimetric sar data using fuzzy logic in entropy and alpha plane. IEEE Trans. Geosci. Remote Sens. 2007, 45, 2652-2664.
8. Kourgli, A.; Ouarzeddine, M.; Oukil, Y.; Belhadj-Aissa, A. Texture modelling for land cover classification of fully polarimetric sar images. Int. J. Image Data Fusion 2012, 3, 129-148.
9. Cloude, S.R.; Pottier, E. A review of target decomposition theorems in radar polarimetry. IEEE Trans. Geosci. Remote Sens. 1996, 34, 498-518.
10. Trisasongko, B.H. The use of polarimetric SAR data for forest disturbance monitoring. Sens. Imaging: Int. J. 2010, 11, 1-13.
11. Potier, E.; Lee, J.S. Unsupervised classification scheme of polSAR images based on the complex Wishart distribution and the "H/A/alpha" polarimetric decomposition theorem. In Proceedings of the EUSAR 2000, Munich, Germany, 23-25 May 2000; pp. 265-268.
12. Conradsen, K.; Nielsen, A.A.; Sehou, J.; Skriver, H. A test statistic in the complex wishart distribution and its application to change detection in polarimetric sar data. IEEE Trans. Geosci. Remote Sens. 2003, 41, 4-19.
13. Lee, J.S.; Grunes, M.R. Classification of multi-look polarimetric SAR data based on complex Wishart distribution. In Proceedings of the 1992 IEEE National Telesystems Conference, George Washington University, Virginia Campus, Washington, DC, USA, 19-20 May 1992; pp. 21-24.
14. Ainsworth, T.L.; Lee, J.S. Polarimetric SAR image classification employing subaperture polarimetric analysis. In Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, Seoul, Korea, 25-29 July 2005; pp. 41-43.
15. Ainsworth, T.L.; Jansen, R.W.; Lee, J.S.; Fiedler, R. Sub-aperture analysis of high-resolution polarimetric SAR data. In Proceedings of the 1999 IEEE International Geoscience and Remote Sensing Symposium, Hamburg, Germany, 28 June-2 July 1999; pp. 41-43.
16. Ferro-Famil, L.; Reigber, A.; Pottier, E.; Boerner, W.M. Analysis of anisotropic behavior using sub-aperture polarimetric SAR data. In Proceedings of the 2003 IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 21-25 July 2003; pp. 434-436.
17. Ferro-Famil, L.; Reigber, A.; Pottier, E. Nonstationary natural media analysis from polarimetric sar data using a two-dimensional time-frequency decomposition approach. Can. J. Remote Sens. 2005, 31, 21-29.
18. Reigber, A.; Jager, M.; He, W.; Ferro-Famil, L.; Hellwich, O. Detection and classification of urban structures based on high-resolution SAR imagery. In Proceedings of the 2005 IEEE International Urban Remote Sensing Joint Event, Paris, France, 11-13 April 2007; pp. 1-6.
19. Runkle, P.; Nguyen, L.H.; McClellan, J.H.; Carin, L. Multi-aspect target detection for sar imagery using hidden markov models. IEEE Trans. Geosci. Remote Sens. 2001, 39, 46-55.
20. Chen, M. Comparing traditional statistics, decision tree classification and support vector machine techniques for financial bankruptcy prediction. Intell. Autom. Soft Comput. 2012, 18, 65-73.
21. Kimura, H. Radar polarization orientation shifts in built-up areas. IEEE Trans. Geosci. Remote Sens. 2008, 5, 217-221.
22. Cloude, S.R. Target decomposition theorems in radar scattering. Electron. Lett. 1985, 21, 22-24.
23. Cloude, S.R.; Pottier, E. An entropy based classification scheme for land applications of polarimetric sar. IEEE Trans. Geosci. Remote Sens. 1997, 35, 68-78.
24. Wang, Y.Y.; Li, J. Feature-selection ability of the decision-tree algorithm and the impact of feature-selection/extraction on decision-tree results based on hyperspectral data. Int. J. Remote Sens. 2008, 29, 2993-3010.
25. Pang, S.L.; Gong, J.Z. C5.0 classification algorithm and application on individual credit evaluation of banks. Syst. Eng.-Theory Pract. 2009, 29, 94-104.
26. Freund, Y.; Schapire, R.E. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 1997, 55, 119-139.
27. Story, M.; Congalton, R.G. Accuracy assessment-a user's perspective. Photogramm. Eng. Remote Sens. 1986, 52, 397-399.
28. Qia, Z.; Yeh, A.G.O.; Li, X.; Zheng, L. A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data. Remote Sens. Environ. 2012, 118, 21-39.
29. Lee, J.S.; Ainsworth, T.L. The effect of orientation angle compensation on coherency matrix and polarimetric target decompositions. IEEE Trans. Geosci. Remote Sens. 2011, 49, 53-64.
30. Lardeux, C.; Frison, P.L.; Rudant, J.P.; Souyris, J.C. Use of the SVM classification with polarimetric SAR data for land use cartography. In Proceedings of the 2006 IEEE International Geoscience and Remote Sensing Symposium, Denver, CO, USA, 31 July-4 August 2006; pp. 493-496.
31. Lim, T.S.; Loh, W.Y.; Shih, Y.S. A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learning 2000, 40, 203-228.