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- W2384911609 abstract "Hyperspectral image linear feature extraction methods often cause information loss and distortion.In view of this,a new kernel minimum noise fraction(KMNF) transform hyperspectral image nonlinear feature extraction method is proposed that introduces a kernel method to minimum noise fraction(MNF) transform.Hyperspectral image KMNF feature extraction experiments were carried out.CUPRITE AVIRIS data experimental results show that sample number influences KMNF slightly,a small number of samples can get almost the same result as a large number of samples;KMNF feature extraction reflects the nonlinear characteristics of hyperspectral images,and endmember extraction effects based on KMNF images outweigh MNF images." @default.
- W2384911609 created "2016-06-24" @default.
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- W2384911609 date "2013-01-01" @default.
- W2384911609 modified "2023-10-12" @default.
- W2384911609 title "Hyperspectral Image Feature Extraction via Kernel Minimum Noise Fraction Transform" @default.
- W2384911609 hasPublicationYear "2013" @default.
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