A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Sixth International Conference of Information Fusion, 2003. Proceedings of the
This paper introduces two novel approaches to estimate the clique potentials in discrete and multilevel realizations of Gibbs Markov random field (GMRF) models. The first approach employs a genetic algorithm (GA) in order to arrive at the closest synthesized image that resembles the original "observed" image. The Second approach is used to estimate the parameters of Gaussian Markov random field. Given an image formed of a number of classes, an initial class density is assumed and the parametersdoi:10.1109/icif.2003.177340 fatcat:parsa3uisre55lveku5mjhnvpe