An approach of image denoising in multi-wavelet domain based on particle swarm optimization was proposed. Firstly, particle swarm optimization was used to construct the adaptive pre-filters of CL multi-wavelet transform. Then noised image was decomposed by multi-wavelet transform and the coefficients were processed using threshold scheme according to the energy distribution of coefficients. Finally, denoised image could be obtained by inverse multi-wavelet transform. Experiments show, the proposed approach outperforms traditional wavelet denoising methods in terms of PSNR and visual effects. Moreover, the approach is beyond median filter and Wiener filter obviously.