【摘要】 提出了一种结合Freeman分解和模糊聚类的极化干涉合成孔径雷达(polarimetric interferometric synthetic aperture radar,PolInSAR)数据非监督分类方法。针对基于Freeman分解的极化SAR图像分类方法中提取的3种散射机理:表面散射、体散射、偶次散射占主导的区域之间存在模糊的缺点,利用PolInSAR处理中的最优干涉相干系数引入的参数——最优相干熵HInt和最优相干各项异性度AInt,将每种散射机理主导区域划分为单个散射机制或多个散射机制共同作用的区域。并将模糊理论引入到HInt/AInt平面的区域边界划分,得到初始分割图像。对初始分割图像进行合并,模糊聚类等操作,得到最终分类结果。采用ESAR Oberpfaffenhofen地区PolInSAR数据实验的结果验证了本文方法的有效性。更多还原

【Abstract】 An unsupervised classification method using Freeman decomposition and fuzzy clustering is proposed to solve the ambiguity problem among surface,volume and double-bounce scattering dominated region,which is extracted from polarimetric synthetic aperture radar(PolSAR) data with Freeman decomposition.A fuzzy clustering method of polarimetric interferometric SAR(PolInSAR) data making use of two parameters describing optimum coherence which are optimum coherence entropy HInt and optimum coherence anisotropy AInt is proposed to partition different scattering mechanisms dominated region.Fuzzy theory is introduced to the partition of HInt/AInt plane to get intial partition of the image.Then cluster merging and fuzzy clustering operations are introduced to obtain the final classification result.Experiment results making use of full polarimetric interferometric data of Oberpfaffenhofen area acquired by ESAR confirm the validity of the presented method.更多还原