Most recent approaches have posed texture synthesis in a

statistical setting as a problem of sampling from a probability

distribution. Zhu et. al. [12] model texture as a Markov

Random Field and use Gibbs sampling for synthesis. Unfortunately,

Gibbs sampling is notoriously slow and in fact

it is not possible to assess when it has converged. Heeger

and Bergen [6] try to coerce a random noise image.