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Unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization
In hyperspectral imaging, hundreds of images are taken at narrow and contiguous spectral bands providing us with high spectral resolution spectral signatures that can be used to discriminate between objects. In many ...
An adaptive spectrally weighted structure tensor applied to tensor anisotropic nonlinear diffusion for hyperspectral images
The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount ...
Geometric scale-space framework for the analysis of hyperspectral imagery
This work introduces a framework for a fast and algorithmically scalable multiscale representation and segmentation of hyperspectral imagery. The framework is based on the scale-space representation generated by geometric ...