In order to remove Gaussian noise and impulse noise from video data,a nonlocal video denoising algorithm based on S1/2 matrix norm is proposed.F irstly,using a diamond search algorithm for fast patch-matching,some patches similar to the given reference patch are found an d collected in the video data. Secondly,all of the columns of similarity patches are recombined to form a new matrix and the new matrix is decomposed into a low rank matrix and a sparse matrix based on S 1/2 matrix norm.The low rank matrix represents the scene information data of the original video and the sparse matr ix represents the impulse noise data and outliers existing in the noisy video.Lastly,the estimated values of a denoised reference patch are determined by taking the weighted average of all the data recovered from the low rank matrix,and the estimated values of the denoised frame are got based on the combinations o f all the recovered reference patches in a frame.Experimental results show that the proposed scheme can effec tively remove Gaussian noise and impulse noise from the video.Compared with two existing state-of-art al gorithms,the proposed algorithm has noticeable superiority in both visual effect and objective evaluation.