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About Classification Methods Based on Tensor Modelling for Hyperspectral Images
[chapter]
2009
Communications in Computer and Information Science
Denoising and Dimensionality Reduction (DR) are key issue to improve the classifiers efficiency for Hyper spectral images (HSI). The multi-way Wiener filtering recently developed is used, Principal and independent component analysis (PCA; ICA) and projection pursuit (PP) approaches to DR have been investigated. These matrix algebra methods are applied on vectorized images. Thereof, the spatial rearrangement is lost. To jointly take advantage of the spatial and spectral information, HSI has been
doi:10.1007/978-3-642-10546-3_34
fatcat:76g54ro3sna7rmhkzx6dypc7nu