A new image denoising method based on Bayesian estimation is proposed. Normal inverse Guassian (NIG) model is used to describe the distributions of the wavelet coefficients of image,and Bayesian maximum a posteriori probability (MAP) estimator is used to estimate the noisy wavelet coefficients. In order to improve the behavior of Bayesian estimation,wavelet coefficients with different correlation are calculated with different ways. What′s more,Cycle Spinning algorithm is used to modify the Gibbs phenomenon which is caused by wavelet transform without translation invariance. The experimental results prove that this new method can remove Gaussian white noise effectively,reserve the edges better and improve the peak signal-to-noise ratio of the image.