In this paper a new low-complexity algorithm for the denoising of video sequences is presented. The proposed fuzzy-rule based algorithm is first explained in the pixel domain and later extended to the wavelet domain. The method can be seen as a fuzzy variant of a recent multiple class video denoising method that automatically adapts to detail and motion. Experimental results show that the proposed algorithm efficiently removes Gaussian noise from digital greyscale image sequences. These results also show that our method outperforms other state-of-the-art filters of comparable complexity for different video sequences.