In order to overcome the aliasing phenomenon commonly existing in real contourlet transform image denoising, some characters of complex contourlet transform whose structure is a cascading of dual tree complex wavelet and directional filter banks are discussed. It is proved that the transform performs well at division and restraining ability under white Gaussian noise condition. Then, an image denoising algorithm was proposed based on the transform. Furthermore, Mento-Carlo method was used to find convergence factors for modifying the 3σ rule, and hard threshold method was carried on complex contourlet tranform domain coefficients. Experimental results show that the image denoising algorithm proposed in this paper is superior to that using real contourlet transform both at Peak Signal-to-noise Ratio (PSNR) values and visual quality.