A Low-Computational-Complexity Algorithm for Hyperspectral Endmember Extraction: Modified Vertex Component Analysis

@article{Lpez2012ALA,
  title={A Low-Computational-Complexity Algorithm for Hyperspectral Endmember Extraction: Modified Vertex Component Analysis},
  author={Sebasti{\'a}n L{\'o}pez and Pablo Horstrand and Gustavo Marrero Callic{\'o} and Jos{\'e} Francisco L{\'o}pez and Roberto Sarmiento},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2012},
  volume={9},
  pages={502-506}
}
Endmember extraction represents one of the most challenging aspects of hyperspectral image processing. In this letter, a new algorithm for endmember extraction, named modified vertex component analysis (MVCA), is presented. This new technique outperforms the popular vertex component analysis (VCA) by applying a low-complexity orthogonalization method and by utilizing integer instead of floating-point arithmetic when dealing with hyperspectral data. The feasibility of this technique is… CONTINUE READING

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