Class-Specific Sparse Multiple Kernel Learning for Spectral-Spatial Hyperspectral Image Classification.
IEEE Transactions on Geoscience and Remote Sensing(2016)
摘要
In recent years, many studies on hyperspectral image classification have shown that using multiple features can effectively improve the classification accuracy. As a very powerful means of learning, multiple kernel learning (MKL) can conveniently be embedded in a variety of characteristics. This paper proposes a class-specific sparse MKL (CS-SMKL) framework to improve the capability of hyperspectr...
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关键词
Kernel,Hyperspectral imaging,Feature extraction,Data mining,Image reconstruction,Principal component analysis
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