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基于Beta-Prime统计模型和QGD分类器的SAR图像地物分类方法 被引量：2

The SAR Image Terrain Classification Algorithm Combining Quadratic Gamma Discrimination Classifier and Beta-Prime Statistic Model
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摘要 本文融合了Beta prime(BP)统计模型和QuadraticGammadiscrimination(QGD)分类器各自的优点 ,给出了一个完整的合成孔径雷达 (SAR)图像地物分类算法 .通过利用BP模型区分背景杂波和目标 ,利用QGD分类器区分自然目标和人造目标 ,可以精确地把SAR图像分成阴影、背景杂波、自然目标和人造目标 ,在为目标识别过程提供潜在目标切片的同时 。 The synthetic aperture radar(SAR)image terrain classification algorithm combining the respective characteristics of Beta-prime(BP)statistic model and quadratic Gamma discrimination(QGD)classifier is presented.Through classifying background clutter and target by BP model,and classifying natural target and man-made target by QGD classifier,this algorithm can cluster the SAR image into shadow,background clutter,natural target and man-made target.It can offer not only the information of background clutter and natural target,but also the potential target chips for target recognition process.
作者 付琨 孙真真 吴一戎
机构地区 中国科学院电子学研究所 北京系统工程研究所
出处 《电子学报》 EI CAS CSCD 北大核心 2003年第z1期2163-2166,共4页 Acta Electronica Sinica
关键词 合成孔径雷达图像 QGD分类器 BP统计模型 地物分类 SAR image QGD classifier BP statistic model terrain classification
分类号 TN951 [电子电信—信号与信息处理]
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参考文献8

  • 1[1]Stewart D, Blacknell D, et al . Optimal approach to SAR image segmentation and classification[J] .Radar,Sonar and Navigation,IEE Proceedings,2000,147(6): 134 - 142.
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  • 8付琨,匡纲要,郁文贤.基于改进相关邻域模型的SAR图像RCS重构[J].系统工程与电子技术,2001,23(4):48-53. 被引量：3

二级参考文献8

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电子学报
2003年 第z1期

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