【摘要】 以非下采样剪切波变换(NSST)及隐马尔可夫树(HMT)理论为基础,提出了一种基于BKF(Bessel K Form)矢量HMT的非下采样剪切波域图像水印算法.水印嵌入时,首先对原始载体图像进行NSST;然后构造自适应高阶水印嵌入强度函数;最后选择重要的NSST高频系数乘性嵌入水印.水印检测时,首先根据NSST系数的非高斯分布特性及NSST系数间的子带内、方向间、尺度间等多种相关特性,建立具有强描述能力的BKF矢量HMT模型;然后利用最大期望(EM)方法,估计出BKF矢量HMT模型参数;最后结合BKF矢量HMT模型和最大似然(ML)检验理论,构造出数字水印检测器并提取水印.仿真实验结果证明了本文算法的有效性.更多还原

【Abstract】 In this paper,we propose a blind NSST domain image watermark decoder,wherein a vector-based HMT statistical model using BKF distribution is used.In the proposed scheme,the NSST is firstly performed on the original host image,and then the adaptive high-order watermark embedding strength functions are constructed,and finally the watermark data is embedded into the significant high-frequency coefficients in NSST domain.At the watermark receiver,NSST highpass coefficients are firstly modeled by employing the BKF vector HMT,where the BKF marginal statistics and strong intra-subband,cross-scale,and cross-orientation dependencies of NSST coefficients are incorporated.Then the statistical model parameters of BKF vector HMT are estimated using the expectation maximization approach.And finally a blind image watermark decoder is developed using BKF vector HMT and the maximum likelihood decision rule.The experimental results validate the effectiveness of the proposed technique.更多还原