基于图变换和DWT-SVD的鲁棒图像水印算法北大核心CSCD

针对图像水印算法在攻击强度较大时鲁棒性差的问题,提出了一种基于图变换(graph-based transform,GBT)、离散小波变换(discrete wavelet transform,DWT)和奇异值分解(singular value decomposition,SVD)的鲁棒图像水印算法。首先对载体图像进行不重叠分块处理,挑选出像素方差值较高的子块进行DWT得到其低频系数矩阵,然后对低频系数矩阵依次进行GBT和SVD得到奇异值矩阵,最后将水印信息嵌入到奇异值矩阵的最大奇异值中。实验结果表明,Pirate图像结构相似度(structural similarity,SSIM)达到0.97以上时,本文算法能有效抵抗噪声、滤波、JPEG压缩、剪切和交换行列等攻击,归一化互相关系数(normalization coefficient,NC)值均在0.9以上。

Robust image watermarking algorithm based on graph-based transform and DWT -SVD

Aiming at the problem of poor robustness of image watermarking algorithms when t he attack is strong,a robust method based on graph-based transform (GBT),discret e wavelet transform (DWT) and singular value decomposition (SVD) is proposed.First,we perform non- overlapping block processing on the carrier image,select the sub-blocks with higher pixel varian ce values and perform DWT on each sub-block to obtain its low-frequency coefficient matrix,and then perform GBT and SVD on the low frequency coefficient matrix in turn to obtain the singular value matrix,and fi nally embed the watermark information to the largest singular value matrix.The experimental res ults show that when Pirate image structure similarity (SSIM) reaches 0.97 or more,the algorithm in this pa per can effectively resist attacks such as noise,filtering,JPEG compression,cropping,and exchang e of ranks,and the normalization coefficient (NC) value is all above 0.9.