In this paper, performance analysis of digital image watermarking using contourlet transform is proposed. The ease of digital media modification and dissemination necessitates content protection beyond encryption.So information's are hidden as digital watermarks in multimedia enables protection mechanism in decrypted contents. Among emergent applications of digital watermarking, owner identification, proof of ownership and transaction tracking are applications that protect data by embedding the owner’s information in it.The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Many literature have reported about Discrete Wavelet Transform watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks and the shift variance of Wavelet Packet Transform causes inaccurate extraction. In Contourlet transformation, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image.In DWT-SVD watermarking technique, firstly original image is decomposed according to DWT and then watermark is embedded in singular values obtained by applying SVD.To extract the watermark, ICA-ML is used, it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that contourlet based watermarking scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with SVD algorithm to prove the robustness of the scheme. Simulations are carried out using Matlab Software.