Classification of hyperspectral data with ensemble of subspace ICA and edge-preserving filtering

@article{Xia2016ClassificationOH,
  title={Classification of hyperspectral data with ensemble of subspace ICA and edge-preserving filtering},
  author={Junshi Xia and Lionel Bombrun and T{\"u}lay Adalı and Yannick Berthoumieu and Christian Germain},
  journal={2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2016},
  pages={1422-1426}
}
Conventional feature extraction methods cannot fully exploit both the spectral and spatial information of hyperspectral imagery. In this paper, we propose an ensemble method of subspace independent component analysis (ICA) and edge-preserving filtering (EPF) for the classification of hyper-spectral data to achieve this task. First, several subsets are randomly selected from the original feature space. Second, ICA is used to extract spectral independent components followed by a recent and… CONTINUE READING

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