基于BKF矢量HMT的非下采样剪切波域数字水印检测算法

doi:10.12263/DZXB.20191028

电子学报 ›› 2021, Vol. 49 ›› Issue (1): 40-49.DOI: 10.12263/DZXB.20191028

基于BKF矢量HMT的非下采样剪切波域数字水印检测算法

王向阳, 牛盼盼, 田静, 杨红颖, 徐欢

辽宁师范大学计算机与信息技术学院, 辽宁大连 116029

收稿日期:2019-09-09 修回日期:2020-07-15 出版日期:2021-01-25
- 作者简介:
- 王向阳 男,1965年3月出生,辽宁铁岭人.1995年在吉林大学获工学硕士学位.现为辽宁师范大学计算机与信息技术学院教授,主要研究方向为网络信息安全、智能多媒体计算.E-mail:wxy37@126.com;牛盼盼 女,1983年4月出生,辽宁盘锦人.2013年在大连海事大学获工学博士学位.现为辽宁师范大学计算机与信息技术学院副教授,主要研究方向为网络信息安全、图像处理.E-mail:niupanpan3333@163.com
- 基金资助:
- 国家自然科学基金 (No.61472171，No.61701212）; 辽宁省教育厅科学研究经费项目 (重点项目） (No.LZ2019001）; 辽宁省自然科学基金 (No.2019-ZD-0468）

A Blind Watermark Decoder in NSST Domain Using BKF Vector HMT Model

WANG Xiang-yang, NIU Pan-pan, TIAN Jing, YANG Hong-ying, XU Huan

School of Computer and Information Technology, Liaoning Normal University, Dalian, Liaoning 116029, China

Received:2019-09-09 Revised:2020-07-15 Online:2021-01-25 Published:2021-01-25

摘要/Abstract

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.

关键词: 图像水印, 矢量HMT, BKF分布, 非下采样剪切波变换, 自适应嵌入强度, 最大似然决策

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.

Key words: image watermarking, vector-based HMT, BKF distribution, nonsubsampled Shearlet transform, adaptive watermark embedding strength, maximum likelihood decision

中图分类号:

TP309

王向阳, 牛盼盼, 田静, 杨红颖, 徐欢. 基于BKF矢量HMT的非下采样剪切波域数字水印检测算法[J]. 电子学报, 2021, 49(1): 40-49.

WANG Xiang-yang, NIU Pan-pan, TIAN Jing, YANG Hong-ying, XU Huan. A Blind Watermark Decoder in NSST Domain Using BKF Vector HMT Model[J]. Acta Electronica Sinica, 2021, 49(1): 40-49.

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基于BKF矢量HMT的非下采样剪切波域数字水印检测算法

A Blind Watermark Decoder in NSST Domain Using BKF Vector HMT Model

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