Fast Constrained Least Squares Spectral Unmixing Using Primal-Dual Interior-Point Optimization

@article{Chouzenoux2014FastCL,
  title={Fast Constrained Least Squares Spectral Unmixing Using Primal-Dual Interior-Point Optimization},
  author={Emilie Chouzenoux and Maxime Legendre and Said Moussaoui and J{\'e}r{\^o}me Idier},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year={2014},
  volume={7},
  pages={59-69}
}
Hyperspectral data unmixing aims at identifying the components (endmembers) of an observed surface and at determining their fractional abundances inside each pixel area. Assuming that the spectral signatures of the surface components have been previously determined by an endmember extraction algorithm, or to be part of an available spectral library, the main problem is reduced to the estimation of the fractional abundances. For large hyperspectral image data sets, the estimation of the… CONTINUE READING
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