Polarimetric SAR urban classification using the Touzi target scattering decomposition
Polarimetric SAR urban classification using the Touzi target scattering decomposition
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DOI：
10.5589/m11-042
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发表时间：
2011-08
影响因子：
2.6
通讯作者：
A. Bhattacharya;R. Touzi
中科院分区：
文献类型：
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作者：
A. Bhattacharya;R. Touzi
Touzi分解是近年来提出的一种新的目标散射非相干分解方法。与Cloude-Pottier非相干目标散射分解不同，不进行散射参数平均，并且目标散射完全通过对三个（主要，中等和低散射）单散射中的每个的五个参数的深入分析来表征。出于实际原因，有一个直接需要的程序，允许排名和选择的最小Touzi分解参数子集，允许一个准确的图像分类。在这项研究中，一个过滤器的互信息准则的基础上，介绍了选择和排名最合适的分解参数子集的分类在渥太华，安大略省安大略的城市网站。两种方法被认为是合适的参数子集的选择：最大的互信息和最大的相关性和最小的冗余。在特征选择和类别判别方面对两种方法进行了比较，并将所选择的最优子集用于基于支持向量机的城市场地分类。极化Convair 580合成孔径雷达在渥太华的城市站点收集的数据被用来评估和验证的选择和分类结果。
The Touzi decomposition was recently introduced for a roll and unique incoherent decomposition of target scattering. Unlike the Cloude–Pottier incoherent target scattering decomposition, no scattering parameter averaging is performed and target scattering is fully characterized by an in-depth analysis of five parameters for each of the three (dominant, medium, and low scattering) single scattererings. For practical reasons, there is an immediate need for a procedure that permits the ranking and selection of the smallest Touzi decomposition parameter subset that permits an accurate image classification. In this study, a filter method based on mutual information criteria was introduced to select and rank the most suitable decomposition parameter subset for the classification of an urban site in Ottawa, Ontario. Two approaches are considered for the selection of the suitable parameter subset: the maximum mutual information and the maximum relevancy and minimum redundancy. The two approaches were compared in terms of feature selection and class discrimination, and the optimum subsets selected were used to perform an urban site classification based on a support vector machine. Polarimetric Convair 580 synthetic aperature radar data collected over an urban site in Ottawa were used to assess and validate the selection and classification results.