In this paper, we introduce a new soft-threshold wavelet shrinkage estimator based on the Stein’s unbiased risk estimate (SURE) for matrix-variate normal distribution in a high dimensional case. We focus on particular thresholding rules to obtain a new SURE threshold, and thus produce new estimators under quadratic loss function. Finally, we present a simulation study to test the validity of the proposed estimator.