全极化合成孔径雷达多视图像的极化特征分析
Statistical analysis of multilook signatures for polarimetric SAR image
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摘要: 该文基于乘性相干斑模型,对全极化合成孔径雷达多视图像的极化特征参数(同极化比、交叉极化比和同极化相位差)进行了分析,利用实际的模拟数据对特征参数的PDF进行了拟合测试,分析了多视极化特征参数的统计特性对极化相干斑抑制算法的影响。利用极化比和相位差的特点,对地物进行分类,所得分类精度与利用最优极化分类法的分类精度具有可比性。Abstract: Based on the multiplication speckle model, the statistical characteristics of the polarimetric signatures are analyzed,which include co-polar and cross-polar ratios and co-polar phase difference for multi-look polarimetric SAR data. With the simulated data, the effect of the estimated accuracy of the polarimetric signatures on the performance of the algorithm for suppressing the speckle is analyzed. in addition, based on the features of the polarimetric signatures, applying them on the Bayes classifier, the accuracy of classification can be compared with the optimum polarimetric classifier.
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L.M. Novak, M. C. Burl, Optimal speckle reduction in polarimetric SAR imagery, IEEE Trans.on Aerospace and Electronic Systems, 1990, AES-26(2), 293-304.[2]Jong-Sen Lee, M. R. Grunes, Speckle reduction in multipolarization, multifrcquency SAR imagery,IEEE Trans. on Geoscicence and Remote Sensing, 1991, GRS-29(4), 535-544.[3]I.R. Joughin, D. P. Winebrenner, Probability density functions for multilook polarimetric signatrures, IEEE Trans. on Geoscience and Remote Sensing, 1994, GRS-32(3), 562-574.[4]M.C. Teich, P. Diament, Multiply stochastic representations for K distributions and their Poisson transforms, J. Opt. Soc. Amer., 1989, 6(1), 80-91.[5]L. M. Novak, Generating correlated Weibull random variables for digital simulations. In Proc. of IEEE Decision and Control Conference, San Diego, CA, 1973, 156-160.[6]L.M. Novak, R. T. Shin, Identification of terrain cover using the optimum polarimetric classifier,Journal of Electromagnetic Waves and Application, 1987, 2(2), 171-194. -
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