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For the non-local denoising approach presented by Buades et al., remarkable denoising results are obtained at high expense of computational cost. In this paper, a new algorithm that reduces the computational cost for calculating the similarity of neighborhood windows is proposed. We first introduce an approximate measure about the similarity of neighborhood windows, then we use an efficient summed square image (SSI) scheme and fast Fourier transform (FFT) to accelerate the calculation of this measure. Our algorithm is about fifty times faster than the original non-local algorithm both theoretically and experimentally, yet produces comparable results in terms of mean-squared error (MSE) and perceptual image quality.