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- W2355441625 abstract "The wavelet packet transformation has better time-frequency localization ability compared with the wavelet transformation. The pixel spectral curves of hyperspectral images as one dimension signals were decomposed by multi-scale wavelet packet transformations, and acquired different-scale component vectors in low and high frequency signals. According to the fact that the pixel spectra of different objects have different bases of best wavelet packet but the pixel spectra of same features are identical ones in the first some best wavelet packet groups, and by means of the wavelet packet decomposition of the spectral features of some objects such as vegetation, water, rock and shadow, a new target identification method has been probed for mapping features based on the composition of the characteristic parameters of the first several best wavelet packet bases for each pixel spectrum. The experiment results show that the features to vegetation, water, rock and shadow on AVIRIS image can be identified and mapped." @default.
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- W2355441625 date "2008-01-01" @default.
- W2355441625 modified "2023-09-28" @default.
- W2355441625 title "Feature Mapping of Hyperspectral Images Based on Best Basis of Wavelet Packet Decomposition" @default.
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