目的为了解决图像的鲁棒性和透明性之间的矛盾,依据压缩感知理论的计算保密性提出一种基于压缩感知的强鲁棒彩色图像双水印算法。方法首先将水印图像RGB分解后,对G,B分量分块压缩感知获得测量值,再对载体图像G,B分量NSCT分解,对低频分量非重叠分块后LU分解、奇异值分解,将每个分块的水印测量值按不同嵌入强度对应嵌入载体奇异值矩阵中,经过一系列逆变换得到含水印图像。最后用含水印图像R分量分块压缩感知测量值生成零水印,发往IPR中心注册保存。结果该算法在水印的嵌入和提取仿真实验结果中峰值信噪比大于40 d B,重建的水印图像与原图像相似度极高,且能抵抗剪切、高斯噪声、椒盐噪声、高斯低通滤波和JPEG压缩等类攻击。结论算法具有很强的鲁棒性和较好的透明性,实现较简单具有切实的可行性。
The work aims to propose a strongly robust dual watermark algorithm for color image based on Compressed Sensing(CS) according to the computational secrecy of CS theory, in order to solve the dispute between the robustness and transparency of the image. First, the block CS of G and B components was done to obtain the measurements after the RGB decomposition of the watermark image. Then, the NSCT decomposition of G and B components of the carrier image was carried out. LU and singular value decompositions were done after the non-overlapped blocking of the low-frequency components. The watermark measurements of each block were correspondingly embedded into the singular value matrix of the carrier according to the different embedding strengths. After a series of inverse transformations, the watermarked image was obtained. Finally, a zero watermark was generated with the block CS measurements of R component of the watermarked image, and sent to the IPR center for registration and safekeeping. Based on the water embedding and extraction simulation experiment results, the peak signal to noise ratio of the proposed algorithm was greater than 40 d B. The similarity between the reconstructed watermark image and the original image was very high. The reconstructed watermark image could resist such attacks as shearing, Gaussian noise, salt and pepper noise, Gaussian low-pass filter and JPEG compression, etc. It is concluded that, with both strong robustness and good transparency, the algorithm is simple and feasible.