  We consider a stochastic image restoration model proposed by A. Gibbs (2004),
and give an upper bound on the time it takes for a Markov chain defined by this
model to be \epsilon - close in total variation to equilibrium. We use Gibbs'
result for convergence in the Wasserstein metric to arrive at our result. Our
bound for the time to equilibrium of similar order to that of Gibbs.
