Analysis and Optimizations of Global and Local Versions of the RX Algorithm for Anomaly Detection in Hyperspectral Data

@article{Molero2013AnalysisAO,
  title={Analysis and Optimizations of Global and Local Versions of the RX Algorithm for Anomaly Detection in Hyperspectral Data},
  author={J. M. Molero and Ester M. Garz{\'o}n and Inmaculada Garc{\'i}a and Antonio J. Plaza},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year={2013},
  volume={6},
  pages={801-814}
}
Anomaly detection is an important task for hyperspectral data exploitation. A standard approach for anomaly detection in the literature is the method developed by Reed and Xiaoli, also called RX algorithm. A variation of this algorithm consists of applying the same concept to a local sliding window centered around each image pixel. The computational cost is very high for RX algorithm and it strongly increases for its local versions. However, current advances in high performance computing help… CONTINUE READING
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