Abstract: A novel image denoising method based on region segmentation is proposed in this paper.Hard thresholding with linear shift invariant Discrete Wavelet Transform（DWT） and NeighShrink with Stein’s Unbiased Risk Estimate（SURE） are most important and efficient methods for image denoising.The former is much fitter than the later for the smooth image denoising，and it is opposite for the texture.The proposed algorithm based on the two methods.Firstly，the noisy image is denoised by hard thresholding with linear shift invariant DWT and by NeighShrink with SURE respectively，then two denoised images are obtained.Secondly，the noisy image is divided to be smooth region，non-smooth region and transitional region.The final denoising image is that the three regions are respectively determined by the two denoised images with the certain proportional divisor.The experimental result shows that the proposed algorithm can absorb the advantages of the two methods，a denoised image，with higher PSNR，rich texture details and better vision and quality，is obtained.