基于两级奇异值分解的鲁棒水印算法

为了平衡水印系统的不可见性和鲁棒性,提出一种新的基于旋转稳定区域和两级奇异值分解(singular value decomposition, SVD)分解的水印算法.在嵌入水印过程中,先选取像素近似无损的稳定区域,并对该区域进行冗余离散小波变换提取低频部分,进而进行分块处理;接着对各分块进行SVD分解,提取第1行第1列的奇异值构建特征矩阵,对特征矩阵进行第2次SVD分解;最后,选取合适的嵌入强度,将水印奇异值嵌入载体奇异值.在水印提取时,先对含水印信息的载体图像进行Radon旋转校正,再提取出水印信息.实验结果表明,该水印算法的峰值信噪比(peak signal-to-noise ratio, PSNR)可达到45 dB,在抵抗旋转攻击时,提取的水印归一化相关系数(normalized correlation, NC)值能达到0.90以上.该文所提的水印算法保证了水印的嵌入容量,且具有良好的不可见性和较高的鲁棒性,在数字版权保护中具有较高的实际应用价值.

Robust Watermarking Algorithm Based on Two-Level Singular Value Decomposition

The paper aims to propose a watermarking algorithm based on rotation stable region and two-level SVD decomposition to improve the imperceptibility and the robustness of watermarking systems. First, the stable region where pixels are approximately lossless is selected. Then, the region is transformed by using redundant discrete wavelet transform, and the low-frequency sub-block is divided into non-overlapping blocks. Next, each subblock is decomposed by using SVD, and the first row and the first column of singular values are extracted to construct a characteristic matrix, and the characteristic matrix is decomposed by using SVD for the second time. Finally, an appropriate scaling factor is selected to embed the watermarking into the singular values of the characteristic matrix. When extracting watermarking, Radon transform is used to correct the host image containing the watermarking information, and the watermarking information is extracted. Experiments with the proposed algorithm show high PSNR values of above 45 dB and high normalized correlation (NC) values of greater than 0.90. It is verified that the watermarking algorithm performs good imperceptibility and ability of anti-geometric attack and highly guaranteed embedding capacity of the watermark. The algorithm has high practical application value in digital copyright protection.