Zhao Li-Wen, Zhou Xiao-Guang, Jiang Yong-Mei, Kuang Gang-Yao. Iterative Classification of Polarimetric SAR Image Based on Freeman Decomposition and Scattering Entropy[J]. Journal of Electronics & Information Technology, 2008, 30(11): 2698-2701. doi: 10.3724/SP.J.1146.2007.00701
Citation:
Zhao Li-Wen, Zhou Xiao-Guang, Jiang Yong-Mei, Kuang Gang-Yao. Iterative Classification of Polarimetric SAR Image Based on Freeman Decomposition and Scattering Entropy[J]. Journal of Electronics & Information Technology, 2008, 30(11): 2698-2701. doi: 10.3724/SP.J.1146.2007.00701
Zhao Li-Wen, Zhou Xiao-Guang, Jiang Yong-Mei, Kuang Gang-Yao. Iterative Classification of Polarimetric SAR Image Based on Freeman Decomposition and Scattering Entropy[J]. Journal of Electronics & Information Technology, 2008, 30(11): 2698-2701. doi: 10.3724/SP.J.1146.2007.00701
Citation:
Zhao Li-Wen, Zhou Xiao-Guang, Jiang Yong-Mei, Kuang Gang-Yao. Iterative Classification of Polarimetric SAR Image Based on Freeman Decomposition and Scattering Entropy[J]. Journal of Electronics & Information Technology, 2008, 30(11): 2698-2701. doi: 10.3724/SP.J.1146.2007.00701
In this paper, a new iterative classification of polarimetric SAR image based on Freeman decomposition and scattering entropy is proposed. This technique extracts the powers of three scattering mechanism components through Freeman decomposition and scattering entropy through H/ decomposition first; Then using the four parameters which can characterize terrain divides the terrains of polarimetric SAR image into nine initial classes, and the final result is obtained by iterative classification with Wishart classifier. This method utilizes polarimetric scattering information of terrain with reason, can acquire good effect of classification and requires a little operation. The effectiveness of this method is demonstrated with the experimental results of polarimetric SAR datas measured practically.
[1] Cloude S R and Pottier E. An entropy based classificationscheme for land applications of polarimetric SAR [J]. IEEETrans. on GRS, 1997, 35(1): 68-78. [2] Lee J S, Grunes M R, and Ainsworth T L. Unsupervisedclassification using polarimetric decomposition and thecomplex Wishart classifier [J]. IEEE Trans. on GRS, 1999,37(5): 2249-2258. [3] Lee J S, Grunes M R, and Pottier E. Unsupervised terrainclassification preserving polarimetric scatteringcharacteristics [J]. IEEE Trans. on GRS, 2004, 42(4):722-731. [4] Putignano C, Schiavon G, and Solimini D. Unsupervisedclassification of a central Italy landscape by polarimetricL-band SAR data [C]. IEEE IGARSS Proceedings, 2005:1291-1294. [5] Lumsdon P, Cloude S R, and Wright G. Polarimetricclassification of land cover for Glen Affric radar project [J].IEE Proceedings. on Radar Sonar Navigation.2005, 152(6):404-412 [6] Freeman A and Durden S L. A three-component scatteringmodel for polarimetric SAR data [J]. IEEE Trans. on GRS,1998, 36(3): 963-973. [7] Van Zyl J J. Unsupervised classification of scatteringbehavior using radar polarimetry data [J]. IEEE Trans. onGRS, 1989, 27(1): 36-45.