Digital watermarking is the act of hiding a message related to a digital signal (i.e. an image, song, video) within the signal itself. In recent years, the phenomenal growth of the internet has highlighted the need for a mechanism to protect ownership of digital media. Digital watermarking is a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. The authors propose a robust quantization-based image watermarking method, called the Gradient Direction Water Marking (GDWM), and based on the uniform quantization of the direction of gradient vectors. In GDWM, the watermark bits are embedded by quantizing the angles of significant gradient vectors at multiple wavelet scales. The proposed method has the following advantages: 1) Increased invisibility of the embedded watermark, 2) Robustness to amplitude scaling attacks, and 3) Increased watermarking capacity. To quantize the gradient direction, the DWT coefficients are modified based on the derived relationship between the changes in coefficients and the change in the gradient direction. In this paper, they propose fourdifferent denoising techniques for checking of the watermarking efficiency [15]. In various noise scenarios, the performance of the proposed denoised methods are compared in terms of PSNR and Correlation Coefficient. The Contourlet transform provides better PSNR when compared to other filter methods. The Correlation Coefficient observed that the Contourlet transform provides almost near to 1 which is ideal.