In consideration of the multi-scaled and multi-directional properties of contourlet transform and its better “sparse” representation of 2-D images,an image restoration algorithm based on contourlet transform is proposed. The algorithm adopts a bound optimization approach and is computed in the contourlet domain iteratively by an expectation-maximization-type (EM-type) method,and then reaches to the optimal result of the penalized likelihood function finally. The experimental results show that,compared with the traditional algorithms based on the wavelet transform,the proposed algorithm based on contourlet transform can protect the detail and edge information of the restored image much better,with the peak singnal-to-noise ratio (PSNR) improvement about 0.6 dB-0.8 dB,and at the same time,the computational efficiency is also retained.