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As one of the best image denoising methods, the Non-Local Means(NL-Means)algorithm proposed by Buades et al. generates state-of-the-art performance. However, due to the high computational complexity, it is difficult to be directly used in practical applications. In this paper, a novel fast algorithm based on the similarity of spatially sampled pixels is introduced. Compared with other fast approaches, the result has shown that our method always uses the shortest time. Meanwhile, it keeps a similar or even better visual results. A maximum of 0.9dB improvement can be attained in comparison with the original method when the noise variance is small.