@string{icassp="Proceedings of International Conference on Acoustics, Speech and Signal Processing"}
@InProceedings{Kato-etal93c,
  author =	 {Kato, Zoltan and Berthod, Mark and Zerubia, Josiane},
  title =	 {Parallel Image Classification using Multiscale
                  {M}arkov Random Fields},
  booktitle =	 icassp,
  pages =	 {137-140},
  year =	 1993,
  volume =	 5,
  address =	 {Minneapolis, USA},
  month =	 apr,
  organization = {IEEE},
  ps =		 {../papers/icassp93.ps},
  abstract =	 {In this paper, we are interested in massively
                  parallel multiscale relaxation algorithms applied to
                  image classification. First, we present a classical
                  multiscale model applied to supervised image
                  classification.The model consists of a label pyramid
                  and a whole observation field. The potential
                  functions of the coarse grid are derived by simple
                  computations. Then, we propose another scheme
                  introducing a local interaction between two neighbor
                  grids in the label pyramid. This is a way to
                  incorporate cliques with far apart sites for a
                  reasonable price. Finally we present the results on
                  noisy synthetic data and on a SPOT image obtained by
                  different relaxation methods using these models. }
}