A sparse self-representation method for band selection in hyperspectral imagery classification

@article{Sun2015ASS,
  title={A sparse self-representation method for band selection in hyperspectral imagery classification},
  author={Weiwei Sun and Liangpei Zhang and Bo Du},
  journal={2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
  year={2015},
  pages={1-4}
}
In this manuscript, we propose a sparse self-representation (SSR) method to select a band subset in hyperspectral imagery (HSI) classification. The SSR method improves from multiple measurement vectors (MMV) with the measurement matrix equals to the observation matrix. The SSR regards that each band could be represented as a linear combination of the representatives of all bands and accordingly all band vectors are reconstructed by themselves accompanied with a sparse coefficient matrix. The… CONTINUE READING
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