吉林大学学报(理学版) ›› 2023, Vol. 61 ›› Issue (3): 592-600.

• • 上一篇    下一篇

基于张量分解和联合熵的双彩色鲁棒水印算法

张天骐, 闻斌, 吴超, 熊天   

  1. 重庆邮电大学 通信与信息工程学院, 重庆 400065
  • 收稿日期:2022-03-13 出版日期:2023-05-26 发布日期:2023-05-26
  • 通讯作者: 闻斌 E-mail:15236627651@163.com

Dual-color Robust Watermarking Algorithm Based on Tensor Decomposition and Joint Entropy

ZHANG Tianqi, WEN Bin, WU Chao, XIONG Tian   

  1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2022-03-13 Online:2023-05-26 Published:2023-05-26

摘要: 针对彩色图像水印算法在滤波攻击下鲁棒性较差的问题, 提出一种基于张量分解和联合熵的双彩色鲁棒水印算法. 首先, 将彩色载体图像整体进行张量分解得到其张量特征图并分块; 然后, 利用联合熵提取遮蔽性较好的特征图子块; 最后, 将水印信息嵌入到选定块经过奇异值分解(singular value decomposition, SVD)后的U矩阵中. 实验结果表明, Lena图像峰值信噪比达39 dB以上, 该算法不仅能有效抵抗图像的滤波攻击, NC值最高达1.000 0, 而且对其他常规图像攻击以及几何攻击也有较强的鲁棒性.

关键词: 图像水印, 张量分解, 联合熵, 奇异值分解

Abstract: Aiming at the problem of poor robustness of color image watermarking algorithms under filtering attacks, we proposed a dual-color robust watermarking algorithm based on tensor decomposition and joint entropy. Firstly, the color carrier image was tensor-decomposed as a whole to obtain its tensor feature map and divided into blocks. Secondly, joint entropy was used to extract the feature map sub-blocks with better shadowing. Finally, the watermark information was embedded into the U matrix of the selected block after singular value decomposition (SVD). The experimental results show that the peak signal-to-noise ratio of Lena images is more than 39 dB. The algorithm  can not only effectively resist image filtering attacks, with a maximum NC value of 1.000 0, but also has strong robustness against other conventional image attacks and geometric attacks.

Key words: image watermark, tensor decomposition, joint entropy, singular value decomposition (SVD)

中图分类号: 

  • TP309.7