A novel watermarking algorithm based on Contourlet transform is proposed in this paper. The watermark composed of pseudo-random sequence is embedded in the selected Contourlet transform coefficients by means of multiplicative method. The Contourlet coefficients are modeled with Generalized Gaussian Distribution with zero mean, and then watermark detection method is proposed based on maximum likelihood detection. Furthermore the decision rule is optimized via Neyman-Pearson criterion. Experimental results show that the fidelity of the watermarked image is good and robust to signal processing and small geometrical attacks.