一种基于差异度的极化SAR图像迭代分类方法
Classification of Polarimetric SAR Images Based on Difference Degree
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摘要: 该文提出了一种用极化SAR数据协方差矩阵的相关性和回波功率差异来定义的目标间的差异度，并在这一差异度的基础上提出了一种新的迭代分类方法。该迭代方法与基于Wishart距离的迭代分类方法相比，不需要矩阵的求逆运算和矩阵的对数运算，降低了迭代过程的计算量，也不再需要目标的先验信息，扩展了其适用范围。该方法应用于NASA/JPL的SIR-C系统在香港地区的实测极化SAR数据，得到了很好的分类效果。
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关键词:
- 极化SAR; 差异度; 迭代分类
Abstract: A concept of difference degree which is based on the coherence of the covariance matrices and the power difference is given in this paper. An iterative method of classification is proposed based on difference degree. This new method not only reduces the compute, but also needs not apriority information of the targets compared with Wishart classifier. This new classifier is applied to the polarimetric SAR image of Hong Kong from the NSAS/JPL SIR-C data and gets an excellent classification result. -
刘秀清. 全极化合成孔径雷达极化信息处理[D]. [博士论文],北京: 中国科学院电子学研究所, 2004.[2]Cloude S R, Pottier E. An entropy based classification scheme for land applications of polarimetric SAR[J].IEEE Trans. on Geoscience and Remote Sensing.1997, 35(1):68-78[3]Lee J S, Grunes M R, Ainsworth T L, et al.. Unsupervised classification using polarimetric decomposition and the complex Wishart classifier[J].IEEE Trans. on Geoscience and Remote Sensing.1999, 37(5):2249-2258[4]Lee J S, Grunes M R. Classification of multi-look polarimetric SAR data based on complex Wishart distribution[C]. National Telesystems Conference, NTC-92. Washington：1992: 7-21-7-24.[5]Freeman A, Durden S L. A three-component scattering model for polarimetric SAR data[J].IEEE Trans. on Geoscience and Remote Sensing.1998, 36(3):963-973[6]Pottier E, Lee J S. Unsupervised classification scheme of polsar images based on the complex Wishart distribution and the H/A/ polarimetric decomposition theorem[C]. EUSAR2000. Munich: 2000: 265-268.[7]Lee J S, Grunes M R, Pottier E, Ferro-Famil L. Unsupervised terrain classification preserving polarimetric scattering characteristics[J].IEEE Trans. on Geoscience and Remote Sensing.2004, 42(4):722-731 -
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