The problem of Bayesian estimation of a signal contaminated by white noise is
investigated. Restricting the unknown signal to a compact subset of L2([0, 1]), the existence of a unique Bayes estimator for the squared-error loss and its robustness with respect to the prior used are established; for sufficiently diffuse priors, the Bayes estimator is shown to be uniformly L1-consistent.