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极化SAR影像分类方法研究 被引量:1

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摘要 极化SAR图像分类是SAR图像解译的重要内容,快速、准确的SAR图像分类是实现各种实际应用的前提。现基于极化SAR图像的特点,用H-?、Wishart分布及H-?-FCM三种方法对机载全极化SAR数据和星载全极化SAR数据做了分类实验研究。结果表明,由于H-?平面的划分过于简单,这不可避免的会导致分类结果的不稳定性;Wishart分类方法能够清楚地区分开自然地物的主要类型,更符合散射机制的自然分布,并考虑与后向散射强度有关的信息,以一种自适应的方式改变了H-?平面中的决策边界,改善了H-?分类结果;H-?-FCM分类方法能较好的克服H-?分类结果中地物类别的模糊问题。
作者 李军民 李欢
出处 《测绘技术装备》 2017年第3期22-27,共6页 Geomatics Technology and Equipment
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