Fully Constrained Least Squares Spectral Unmixing by Simplex Projection

@article{Heylen2011FullyCL,
  title={Fully Constrained Least Squares Spectral Unmixing by Simplex Projection},
  author={Rob Heylen and Dzevdet Burazerovic and Paul Scheunders},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2011},
  volume={49},
  pages={4112-4122}
}
We present a new algorithm for linear spectral mixture analysis, which is capable of supervised unmixing of hyperspectral data while respecting the constraints on the abundance coefficients. This simplex-projection unmixing algorithm is based upon the equivalence of the fully constrained least squares problem and the problem of projecting a point onto a simplex. We introduce several geometrical properties of high-dimensional simplices and combine them to yield a recursive algorithm for solving… CONTINUE READING
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