Robust Digital Image Watermarking Based on Gradient Vector Quantization and Denoising using Bilateral filter and its method noise Thresholding
Robust Digital Image Watermarking Based on Gradient Vector Quantization and Denoising using Bilateral filter and its method noise ThresholdingI. Kullayamma, P. Sathyanarayana,
Assistant Professor, Department of ECE, Professor, Department of ECE,
SV University, Tirupati, AITS, Tirupati, ikusuma96@gmail.com satyamp1@yahoo.com
Abstract- In this modern world Digital watermarking is of prime importance. This has increased the demand for copyright protection. Digital watermarking is a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. We propose a robust quantization-based image watermarking scheme, called the gradient direction watermarking (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 scheme 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. This watermarking technique is more robust to various sizes of watermark images. The Gaussian filter is a local and linear filter that smoothens the whole image irrespective of its edges or details, whereas the bilateral filter is also a local but non-linear, considers both gray level similarities and geometric closeness of the neighbouring pixels without smoothing edges. The extension of bilateral filter: multi-resolution bilateral filter, where bilateral
Assistant Professor, Department of ECE, Professor, Department of ECE,
SV University, Tirupati, AITS, Tirupati, ikusuma96@gmail.com satyamp1@yahoo.com
Abstract- In this modern world Digital watermarking is of prime importance. This has increased the demand for copyright protection. Digital watermarking is a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. We propose a robust quantization-based image watermarking scheme, called the gradient direction watermarking (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 scheme 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. This watermarking technique is more robust to various sizes of watermark images. The Gaussian filter is a local and linear filter that smoothens the whole image irrespective of its edges or details, whereas the bilateral filter is also a local but non-linear, considers both gray level similarities and geometric closeness of the neighbouring pixels without smoothing edges. The extension of bilateral filter: multi-resolution bilateral filter, where bilateral
References: [1] D. Kundur and D. Hatzinakos, “Digital watermarking for telltaletamper proofing and authentication,” Proc. IEEE, vol. 87, no. 7, pp.1167–1180, Jul. 1999. [2] B. Chen and G. W. Wornell, “Quantization index modulation: A classof provably good methods for digital watermarking and informationembedding,” IEEE Trans. Inf. Theory, vol. 47, no. 4, pp. 1423–1443,May 2001. [3]. Perez-Gonzlez and F. Balado, “Quantized projection data hiding,”in Proc. Int. Conf. Image Process., 2002, vol. 2, pp. 889–892. [4] L.-H. Chen and J.-J. Lin, “Mean quantization based image watermarking,”Image Vis. Comput., vol. 21, no. 8, pp. 717–727, 2003 [5] S.-H [6] P. Bao and X. Ma, “Image adaptive watermarking using wavelet domainsingular value decomposition,” IEEE Trans. Circuits Syst. VideoTechnol., vol. 15, no. 1, pp. 96–102, Jan. 2005.