Classical vectorbased or matrixbased denoising methods for remote sensing images (RSIs) may cause distortion both in spatial domain and spectral domain. To improve denoising performance and reduce the distortion, a denoising method based on multi-linear weighted nuclear norm is proposed. Firstly, by considering spectral continuity and interdependency of three unfolding matrices along three modes of RSI, a multi-linear rank is constructed to model the spatial and spectral nonlocal similarity. Then, to make the proposed method more tractable, a variable splittingbased technique is used to solve the optimization problem. Experiment results reveal that the proposed method can provide substantial improvements over the current stateoftheart methods in terms of both objective metric and subjective visual quality.