Local Sparsity Divergence for Hyperspectral Anomaly Detection

@article{Yuan2014LocalSD,
  title={Local Sparsity Divergence for Hyperspectral Anomaly Detection},
  author={Zongze Yuan and Hao Sun and Kefeng Ji and Zhiyong Li and Huanxin Zou},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2014},
  volume={11},
  pages={1697-1701}
}
Anomaly detection (AD) has increasingly become important in hyperspectral imagery (HSI) owing to its high spatial and spectral resolutions. Many anomaly detectors have been proposed, and most of them are based on a Reed-Xiaoli (RX) detector, which assumes that the spectrum signature of HSI pixels can be modeled with Gaussian distributions. However, recent studies show that the Gaussian and other unimodal distributions are not a good fit to the data and often lead to many false alarms. This… CONTINUE READING

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