Semi-supervised hyperspectral image segmentation

  title={Semi-supervised hyperspectral image segmentation},
  author={Jun Li and Josx00E9 M. Bioucas-Dias and Antonio J. Plaza},
  journal={2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing},
This paper presents a new semi-supervised segmentation algorithm, suited to high dimensional data, of which hyperspectral images are an example. The algorithm implements two main steps: (a) semisupervised learning, used to infer the class distributions, followed by (b) segmentation, by inferring the labels from a posterior density built on the learned class distributions and on a Markov random field. The class distributions are modeled with a multinomial logistic regression, where the… CONTINUE READING
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