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Markov Random Field Models in Image Remote Sensing

  • Vincent Granville
  • Jean-Paul Rasson
Conference paper
Part of the Statistics and Computing book series (SCO)

Abstract

During the last few years, Markov Random Field (Mrf) models have already been successfully applied in some applications in image remote sensing in a context of conditional maximum likelihood estimation. Here, in the same context, we propose some original uses of Mrf, especially in image segmentation, noise filtering and discriminant analysis. For instance, we propose a Mrf model on the spectral signatures space, a strongly unified approach to classification and noise filtering as well as a particular model of noise.

Keywords

Supervised classification segmentation noise filtering Markov random field ICM algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Vincent Granville
    • 1
  • Jean-Paul Rasson
    • 1
  1. 1.Département de MathématiqueF.U.N.D.P.NamurBelgium

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