01076nas a2200109   4500008004100000245007200041210006900113260002800182300001400210520069500224856004700919       1993                        eng d00aParallel image classification using multiscale Markov random fields0 aParallel image classification using multiscale Markov random fie  aNew YorkbIEEEc1993///  a137 - 1403 aIn 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.  uhttps://tisat.inf.u-szeged.hu/en/node/1243