Multicluster Spatial–Spectral Unsupervised Feature Selection for Hyperspectral Image Classification
作者： Haichang Li , Shiming Xiang , Zisha Zhong , Kun Ding , Chunhong Pan
DOI: 10.1109/LGRS.2015.2418232
关键词:
摘要: A new unsupervised spatial–spectral feature selection method for hyperspectral images has been proposed in this letter. The key idea is to select the features that better preserve multicluster structure of multiple features. Specifically, information obtained through spectral clustering utilizing a weighted combination Then, such preserved group-sparsity-based robust linear regression model. contribute more preserving are selected. Comparative experiments on two popular real validate effectiveness method, showing higher classification accuracy.
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irgrid.ac.cn参考文章(23)
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