Compressive Source Separation: Theory and Methods for Hyperspectral Imaging

@article{Golbabaee2013CompressiveSS,
  title={Compressive Source Separation: Theory and Methods for Hyperspectral Imaging},
  author={Mohammad Golbabaee and Simon Arberet and Pierre Vandergheynst},
  journal={IEEE Transactions on Image Processing},
  year={2013},
  volume={22},
  pages={5096-5110}
}
We propose and analyze a new model for hyperspectral images (HSIs) based on the assumption that the whole signal is composed of a linear combination of few sources, each of which has a specific spectral signature, and that the spatial abundance maps of these sources are themselves piecewise smooth and therefore efficiently encoded via typical sparse models. We derive new sampling schemes exploiting this assumption and give theoretical lower bounds on the number of measurements required to… CONTINUE READING

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