Semi-supervised change detection method for multi-temporal hyperspectral images

@article{Yuan2015SemisupervisedCD,
  title={Semi-supervised change detection method for multi-temporal hyperspectral images},
  author={Yuan Yuan and Haobo Lv and Xiaoqiang Lu},
  journal={Neurocomputing},
  year={2015},
  volume={148},
  pages={363-375}
}
Abstract Change detection is one of the most important open topics for multi-temporal remote sensing technology to observe the earth. Recently, many methods are proposed to detect the land-cover change information by multi-temporal hyperspectral images. However, many existing traditional change detection methods failed to utilize the spectral information effectively. Hence the models are not robust enough for more widely applications with “noise” bands. In this case, a semi-supervised distance… CONTINUE READING

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A Coarse-to-Fine Semi-Supervised Change Detection for Multispectral Images

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  • 2018
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Questions of Concern in Drawing Up a Remote Sensing Change Detection Plan

  • Journal of the Indian Society of Remote Sensing
  • 2019
VIEW 2 EXCERPTS
CITES BACKGROUND