一种压缩感知下的NSCT-Zernike的鲁棒数字水印方案

A Robust Digital Watermarking of NSCT-Zernike under Compressed Sensing

为了达到水印抗几何攻击鲁棒性高的要求,提出一种在压缩感知下的非下采样轮廓波变换结合伪Zernike矩的鲁棒数字水印方案.利用非下采样轮廓波变换对载体图像进行三层分解提取其低频分量,通过一维离散小波变换对低频分量进行稀疏化以获取稀疏基,构造稀疏基的测量矩阵,并对其进行压缩感知处理得到新的低频分量,计算其Zernike矩,通过量化调制正则化伪Zernike矩幅值的方式将水印信息嵌入.利用正则化正交匹配追踪算法进行图像压缩感知的重构.仿真与实验分析表明,当峰值信噪比达到40 dB以上时,本文算法提取水印的NC值和误码率较为理想.

To meet the high requirements of watermarking robustness against geometric attacks, a robust digital watermarking scheme was proposed based on the combination of non-subsampled Contourlet transform under compressed sensing and pseudo Zernike moments. First, the original image was decomposed to extract its lowfrequency components by non-subsampled Contourlet transform, and the low-frequency components were sparsed by discrete wavelet transform to obtain sparse bases. And then, the measurement matrix was constructed,compressed sensing processing was performed, the Zernike moments were calculated, and the watermark information was embedded by quantizing the amplitude of the regularized pseudo Zernike moment. Finally, a regularized orthogonal matching pursuit algorithm was used to reconstruct the image compressed sensing. Simulation and experimental results show that when the peak signal to noise ratio reaches more than 40 dB, the proposed algorithm can ideally extract the NC value and bit error rate of the watermark.