Multiscale Unsupervised Change Detection on Optical Images by Markov Random Fields and Wavelets

  title={Multiscale Unsupervised Change Detection on Optical Images by Markov Random Fields and Wavelets},
  author={Sebastiano B. Serpico and Elena Angiati},
  journal={IEEE Geoscience and Remote Sensing Letters},
Change-detection methods represent powerful tools for monitoring the evolution of the Earth's surface. In order to optimize the accuracy of the change maps, a multiscale approach can be adopted that jointly exploits observations at coarser and finer scales. In this letter, a multiscale contextual unsupervised change-detection method is proposed for optical images. It is based on discrete wavelet transforms and Markov random fields. Wavelets are applied to the difference image to extract… CONTINUE READING
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A Bayesian approach to classification of multiresolution remote sensing data

  • G. Storvik, R. Fjortoft, A.H.S. Solberg
  • IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3…
  • 2005
Highly Influential
10 Excerpts

MTFtailored multiscale fusion of high-resolution MS and Pan imagery

  • B. Aiazzi, L. Alparone, S. Baronti, A. Garzelli, M. Selva
  • Photogramm. Eng. Remote Sens., vol. 72, no. 5, pp…
  • 2006
1 Excerpt

A multiscale object-specific approach to digital change detection

  • O. Hall, G. J. Hay
  • Int. J. Appl. Earth Obs. Geoinf., vol. 4, no. 4…
  • 2003
2 Excerpts

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