Integrating multiple nonlinear estimators into hyperspectral unmixing

@article{Marinoni2014IntegratingMN,
  title={Integrating multiple nonlinear estimators into hyperspectral unmixing},
  author={Andrea Marinoni and Javier Plaza and Antonio J. Plaza and Paolo Gamba},
  journal={2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
  year={2014},
  pages={1-4}
}
Linear spectral unmixing has been widely used for hyperspectral data interpretation. However, there is a need for nonlinear unmixing methods that can model more complex geometries without the need to resort to prior knowledge about the objects in the scene. In this paper, we present a novel strategy for nonlinear spectral unmixing which combines polytope decomposition (POD) with artificial neural network (ANN)-based learning. Even if no ground-truth information is available, the ANN can still… CONTINUE READING

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