In this paper, we propose a variational model for Polarimetric synthetic aperture radar (PolSAR) data speckle reduction. Since the statistical characteristic of covariance matrix can be well described by the complex Wishart distribution, a data fitting term can be derived according to the maximum likelihood rule. Combining it with the total variation (TV) regularization gives a variational model for PolSAR image speckle reduction. An algorithm based on the alternating minimization technique is used to solve the variational problem. Experimental results on real PolSAR images demonstrate the validity of the proposed method.