• Mathematics, Computer Science
  • Published in
    IEEE Trans. Geoscience and…
    1998
  • DOI:10.1109/36.655328

A fast two-stage classification method for high-dimensional remote sensing data

@article{Tu1998AFT,
  title={A fast two-stage classification method for high-dimensional remote sensing data},
  author={Te-Ming Tu and Chin-Hsing Chen and Jiunn-Lin Wu and Chein-I Chang},
  journal={IEEE Trans. Geoscience and Remote Sensing},
  year={1998},
  volume={36},
  pages={182-191}
}
Classification for high-dimensional remotely sensed data generally requires a large set of data samples and enormous processing time, particularly for hyperspectral image data. In this paper, the authors present a fast two-stage classification method composed of a band selection (BS) algorithm with feature extraction/selection (FSE) followed by a recursive maximum likelihood classifier (MLC). The first stage is to develop a BS algorithm coupled with FSE for data dimensionality reduction. The… CONTINUE READING

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