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- W2366701306 abstract "High data dimensionality of hyperspectral image results in many difficulties for effective information extraction and classification. Taken into consideration of this, adaptive subspace decomposition (ASD) is introduced in this paper. Then, hyperspectral image classification on the basis of information fusion is studied. Information fusion on the subspaces obtained by ASD is beneficial to the features concentration and extraction. The experiments on AVIRIS images show that it is effective to divide data sources by ASD and feature fusion based on wavelet and decision fusion based on consensus theory are suitable to hyperspectral image classification." @default.
- W2366701306 created "2016-06-24" @default.
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- W2366701306 date "2002-01-01" @default.
- W2366701306 modified "2023-09-25" @default.
- W2366701306 title "Hyperspectral image classification based on information fusion" @default.
- W2366701306 hasPublicationYear "2002" @default.
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