We study general over-relaxation
Markov chain Monte Carlo samplers 
for multivariate Gaussian densities.
We provide conditions
for convergence based on 
the spectral radius of the 
transition matrix and on 
detailed balance.  We
illustrate these algorithms
using an image analysis example.