A Contextual Multiscale Unsupervised Method for Change Detection with Multitemporal Remote-Sensing Images

@article{Serpico2009ACM,
  title={A Contextual Multiscale Unsupervised Method for Change Detection with Multitemporal Remote-Sensing Images},
  author={Sebastiano B. Serpico and Elena Angiati},
  journal={2009 Ninth International Conference on Intelligent Systems Design and Applications},
  year={2009},
  pages={572-577}
}
Change-detection represents a powerful tool for monitoring the evolution of the Earth's surface by multitemporal remote-sensing imagery. Here, a multiscale approach is proposed, in which observations at coarser and finer scales are jointly exploited, and a multiscale contextual unsupervised change-detection method is developed for optical images. Discrete wavelet transforms are applied to extract multiscale features that discriminate changed and unchanged areas and Markovian data fusion is used… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 20 references

A bayesian approach to classification of multiresolution remote sensing data

  • G. Storvik, R. Fjortoft, A.H.S. Solberg
  • IEEE Trans. Geosci. Remote Sensing, vol. 43, no…
  • 2005
Highly Influential
10 Excerpts

Digital change detection techniques using remotely-sensed data

  • A. Singh
  • Int. J. Remote Sens., vol. 10, pp. 989– 1003…
  • 1989
Highly Influential
6 Excerpts

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