A Markov Chain Monte Carlo (MCMC) procedure is presented for the identification of clutter in weather‐radar images. The key attributes of the image are the spatial coherence of the areas of clutter (noise) and cloud and the high spatial autocorrelation of the values in areas of cloud. A form of simulated annealing provides the possibility of fast clutter removal. © 2003 American Institute of Physics