  We investigate the posterior rate of convergence for wavelet shrinkage using
a Bayesian approach in general Besov spaces. Instead of studying the Bayesian
estimator related to a particular loss function, we focus on the posterior
distribution itself from a nonparametric Bayesian asymptotics point of view and
study its rate of convergence. We obtain the same rate as in
\citet{abramovich04} where the authors studied the convergence of several
Bayesian estimators.
