We have compared the results we obtain from the proposed variational model with
the ones obtained using a stochastic based on Markov Random Fields
theory (cf. [2] for instance).
Let be the solution of classification, i.e. an image of labels, and let
represent the observed data. We are
looking for the estimation
of
by
maximizing (Maximum A Posteriori) the probability P(
/
).
Using Bayes rule, and according to the properties of Markov Random
Fields, the solution is found thanks to :
stands for the temperature parameter.
The minimization of E is operated through a simulated annealing (with a Metropolis dynamic).