Hyperspectral Unmixing With $l_{q}$ Regularization

@article{Sigurdsson2014HyperspectralUW,
  title={Hyperspectral Unmixing With  \$l_\{q\}\$ Regularization},
  author={Jakob Sigurdsson and Magnus Orn Ulfarsson and Johannes R. Sveinsson},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2014},
  volume={52},
  pages={6793-6806}
}
Hyperspectral unmixing is an important technique for analyzing remote sensing images. In this paper, we consider and examine the ℓq, 0 ≤ q ≤ 1 penalty on the abundances for promoting sparse unmixing of hyperspectral data. We also apply a first-order roughness penalty to promote piecewise smooth end-members. A novel iterative algorithm for simultaneously estimating the end-members and the abundances is developed and tested both on simulated and two real hyperspectral data sets. We present an… CONTINUE READING

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