Unsupervised classification of sea-ice using synthetic aperture radar via an adaptive texture sparsifying transform

@article{Amelard2013UnsupervisedCO,
  title={Unsupervised classification of sea-ice using synthetic aperture radar via an adaptive texture sparsifying transform},
  author={Robert Amelard and Alexander Wong and Fan Li and David A. Clausi},
  journal={2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS},
  year={2013},
  pages={3958-3961}
}
A texture sparsifying transform for use in unsupervised classification of sea-ice in polarimetric synthetic aperture radar (SAR) imagery is presented. The goal of the sparsifying transform is to compactly represent the underlying information of the SAR imagery to eliminate sources of unwanted noise and complexities (e.g., banding effect on RADARSAT-2… CONTINUE READING

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