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- W2388396926 abstract "Comparing with traditional remote sensing data,high dimension,the large amount of information,data redundancy and strong band relevant are prevalent in the hyperspetral remote sensing data. On the combination of data dimension reduction methods, this paper puts forward a hyperspectral remote sensing image classification method based on optimum band combination. Taking AVIRIS data in Indiana area as an example,we analyze the spectrum information and the adjacent band correlation. Then we use subspace division and band index,select the feature band. For the classes difficult to distinguish,we apply J-M distance model for its separability criterion to point out the optimal band combination. Finally,we use SVM classifier for classification. The experimental results show that using the optimal band combination can effectively improve the classification accuracy of hyperspectral remote sensing data." @default.
- W2388396926 created "2016-06-24" @default.
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- W2388396926 date "2014-01-01" @default.
- W2388396926 modified "2023-09-26" @default.
- W2388396926 title "Optimum Band Combination Based Hyperspectral Remote Sensing Image Classification" @default.
- W2388396926 hasPublicationYear "2014" @default.
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