Advanced Communication Research Institute, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
IEEE Trans Image Process. 2010 Apr;19(4):967-80. doi: 10.1109/TIP.2009.2038774. Epub 2009 Dec 18.
In this paper, an improved multiplicative image watermarking system is presented. Since human visual system is less sensitive to the image edges, watermarking is applied in the contourlet domain, which represents image edges sparsely. In the presented scheme, watermark data is embedded in directional subband with the highest energy. By modeling the contourlet coefficients with General Gaussian Distribution (GGD), the distribution of watermarked noisy coefficients is analytically calculated. The tradeoff between the transparency and robustness of the watermark data is solved in a novel fashion. At the receiver, based on the Maximum Likelihood (ML) decision rule, an optimal detector by the aid of channel side information is proposed. In the next step, a blind extension of the suggested algorithm is presented using the patchwork idea. Experimental results confirm the superiority of the proposed method against common attacks, such as Additive White Gaussian Noise (AWGN), JPEG compression, and rotation attacks, in comparison with the recently proposed techniques.
本文提出了一种改进的乘法图像水印系统。由于人类视觉系统对图像边缘的敏感度较低，因此水印应用于轮廓波域，该域稀疏地表示图像边缘。在所提出的方案中，水印数据嵌入具有最高能量的方向子带中。通过使用广义高斯分布 (GGD) 对轮廓波系数进行建模，分析计算了带有水印的噪声系数的分布。以新颖的方式解决了水印数据的透明度和稳健性之间的折衷。在接收器处，基于最大似然 (ML) 决策规则，提出了一种借助信道侧信息的最优检测器。下一步，使用拼凑思想提出了所提出算法的盲扩展。实验结果表明，与最近提出的技术相比，该方法在抵抗常见攻击（如加性高斯白噪声 (AWGN)、JPEG 压缩和旋转攻击）方面具有优越性。
