Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM

@inproceedings{Kayabol2011UnsupervisedCO,
  title={Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM},
  author={Koray Kayabol and Vladimir A. Krylov and Josiane Zerubia},
  booktitle={MUSCLE},
  year={2011}
}
We implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order selection, we combine the CEM algorithm with the hierarchical agglomeration strategy and a model order selection criterion called Integrated Completed Likelihood (ICL). We exploit amplitude statistics… CONTINUE READING

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