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Use of mixed pixels as training samples for hyperspectral remote sensing image classification by SVM
Author(s): 
Pages: 127-129
Year: Issue:  3
Journal: Science of Surveying and Mapping

Keyword:  支持向量机(SVM)最优超平面混合像元遥感分类;
Abstract: 支持向量机(SVM)分类的关键是发现分类最优超平面及类别间隔,而混合像元比纯净像元更接近类别边界,更容易找出最优超平面.本文针对SVM分类器的特点,在高光谱数据分类中采用混合像元作为训练样本对SVM进行训练,试验表明采用类别边界上的混合像元作为训练样本是可行的,能够获得与纯净训练样本接近的分类精度,进一步验证了SVM分类对训练样本空间分布依赖度较低的特点.
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