Abstract
该文提出了一种基于Freeman分解与散射熵的极化SAR图像迭代分类新方法。该方法首先通过Freeman分解提取3种散射机理成分的功率，同时通过H/ 分解提取地物的散射熵；再利用这4个表征地物特性的参数将极化SAR图像中的地物划分为9个初始类，最后使用Wishart分类器对初始类进行迭代分类得到最终的结果。该方法合理利用了地物的极化散射信息，能够取得较好的分类效果，同时运算量也比较小。实测极化SAR数据的实验结果验证了该方法的有效性。
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