计算机应用 ›› 2017, Vol. 37 ›› Issue (9): 2581-2584.DOI: 10.11772/j.issn.1001-9081.2017.09.2581

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基于压缩感知和GHM多小波变换的信息隐藏算法

张弢1, 康缘1, 任帅2, 柳雨农1   

  1. 1. 长安大学 电子与控制工程学院, 西安 710064;
    2. 长安大学 信息工程学院, 西安 710064
  • 收稿日期:2017-03-27 修回日期:2017-05-08 出版日期:2017-09-10 发布日期:2017-09-13
  • 通讯作者: 张弢,zt904@foxmail.com
  • 作者简介:张弢(1984-),女,山西吕梁人,副教授,博士,主要研究方向:信息隐藏、数字水印;康缘(1991-),女,陕西西安人,硕士研究生,主要研究方向:信息隐藏、数字水印;任帅(1982-),男,山西太原人,副教授,博士,CCF会员,主要研究方向:信息隐藏、数字水印、信息安全风险评估;柳雨农(1993-),男,甘肃兰州人,硕士研究生,主要研究方向:信息隐藏、数字水印。
  • 基金资助:
    国家自然科学基金资助项目(61402052);陕西省自然科学基础研究计划项目(2014JM2-6105);中国博士后科学基金资助项目(2015M572510);陕西省博士后科学基金资助项目;西藏自治区自然科学基金项目(2015ZR-14-20);中央高校基本科研业务费专项资金资助项目(310832151092);国家级大学生创新创业训练计划项目(201510710044);2017年中央高校教育教学改革专项(研究生卓越人才培养计划项目)(310624176303)。

Information hiding algorithm based on compression sensing and GHM multiwavelet transform

ZHANG Tao1, KANG Yuan1, REN Shuai2, LIU Yunong1   

  1. 1. School of Electronic and Control Engineering, Chang'an University, Xi'an Shaanxi 710064, China;
    2. School of Information Engineering, Chang'an University, Xi'an Shaanxi 710064, China
  • Received:2017-03-27 Revised:2017-05-08 Online:2017-09-10 Published:2017-09-13
  • Supported by:
    This work is partially supported by National Natural Science Foundation of China (61402052), the Natural Science Basic Research Plan of Shaanxi Province of China (2014JM2-6105), the China Postdoctoral Science Foundation (2015M572510), the Postdoctoral Science Foundation of Shaanxi Province, the Natural Science Foundation of Tibet (2015ZR-14-20), the Fundamental Research Funds for the Central Universities (310832151092), the National Students' Innovation and Enterpreneurship Training Program (201510710044), Education and teaching Reform Special Project for Central Affiliated University of 2017 (Outstanding Talents Education Project for Postgraduate) (310624176303).

摘要: 针对基于秘密信息置乱方法等类型的信息隐藏算法不可见性低和抗攻击性弱这一问题,提出了一种基于压缩感知和GHM多小波变换的信息隐藏算法。首先,将载体图像进行一次GHM多小波变换,再对所得到的中间能量区域进行一次小波变换得到HH分量,将HH分量进行奇异值分解;其次,将秘密图像进行小波变换,将得到的小波系数进行压缩感知得到观测矩阵,再对观测矩阵元素进行奇异值分解;最后,利用秘密图像的奇异值替换掉载体图像的奇异值来完成秘密信息的嵌入。实验结果表明,相比两种加密算法,算法不可见性(PSNR值)分别提高5.99%和22.11%;对低通滤波、椒盐噪声、高斯噪声、JPEG压缩等常见攻击具有良好的鲁棒性,相关系数(NC)平均增强了4.11%和11.53%。

关键词: 压缩感知, GHM多小波变换, 信息隐藏, 奇异值分解

Abstract: To solve the problem of low invisibility and weak anti-attacking ability in the traditional information hiding algorithm, an information hiding algorithm based on compression sensing was proposed. Firstly, the carrier image was operated by first-order GHM (Geronimo Hardin Massopust) multiwavelet transform, and the obtained region in medium energy level was processed by first-order GHM transform again to get HH component, which was decomposed by the Singular Value Decomposition (SVD). Secondly, the secret image was disposed by the wavelet transform, and the obtained wavelet coefficient was processed by compressed sensing in order to get the measurement matrix. Then the elements of the matrix were decomposed by SVD. Finally, the singular value of the carrier image was replaced by the singular value of the secret image to finish the secret information embedding. The experiment shows that compared with existing two information hiding algorithms, the invisibility has been improved by 5.99% and 22.11% respectively; and the robustness against some common attacks such as low-pass filtering, salt and pepper noise, Gaussian noise and JPEG compression has been improved by 4.11% and 11.53% averagely.

Key words: compressive sensing, Geronimo Hardin Massopust (GHM) multiwavelet transform, information hiding, Singular Value Decomposition (SVD)

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