计算机应用 ›› 2012, Vol. 32 ›› Issue (11): 3125-3128.DOI: 10.3724/SP.J.1087.2012.03125

• 信息安全 • 上一篇    下一篇

基于预测误差和直方图对的无损数据隐藏方法

张晓杰1,童学锋1,宣国荣1,杨志强1,施云庆2   

  1. 1. 同济大学 电子与信息工程学院,上海 201804
    2. 新泽西理工学院 电气工程与计算机系,美国 新泽西 07102
  • 收稿日期:2012-05-30 修回日期:2012-07-13 发布日期:2012-11-12 出版日期:2012-11-01
  • 通讯作者: 张晓杰
  • 作者简介:张晓杰(1988-),男,安徽歙县人,硕士研究生,主要研究方向:图像处理、模式识别; 童学锋(1963-),男,湖北蕲春人,教授,博士,主要研究方向:图像处理、模式识别; 宣国荣(1935-),男,上海人,教授,博士生导师,主要研究方向:图像处理、模式识别。
  • 基金资助:
    国家自然科学基金资助项目(61175014);上海市教委科研创新项目(12ZZ033)

Reversible data hiding based on predictionerror and histogram pairs

ZHANG XIao-jie1,TONG Xue-feng1,XUAN Guo-rong1,YANG Zhi-qiang1,SHI Yun-qing2   

  1. 1. College of Electronics and Information Engineering, Tongji University, Shanghai 201804,China
    2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, New Jersey 07102,USA
  • Received:2012-05-30 Revised:2012-07-13 Online:2012-11-12 Published:2012-11-01
  • Contact: ZHANG XIao-jie
  • Supported by:
    ;Innovation Project of Shanghai Education Commission

摘要: 针对目前存在的大部分图像数据隐藏方法的嵌入量不大和视觉效果一般的问题,提出一种基于预测误差和直方图对的无损数据隐藏方法。在多灰度图像中,用某一像素点周围的八个像素点来预测中心像素点的灰度值,同时得到预测误差。再利用直方图对的方法,把数据嵌入到预测误差中。在嵌入过程中,以嵌入阈值和起伏阈值作为指导进行嵌入,通过调整这两个阈值,得到最佳的嵌入效果。实验表明,该方法在视觉效果和嵌入容量方面都取得很好的效果。

关键词: 预测误差, 直方图对, 无损数据隐藏, 嵌入阈值, 起伏阈值

Abstract: Most of the existing image data hiding methods have little payload and the visual effect is usually not good enough. The paper proposed a reversible hiding technique based on predictionerror and histogram pair. The gray value of a pixel was predicted using eight pixels around it in a multigray image. Then the predictionerror could be calculated. The hiding data were embedded into the predictionerror with the technique of histogram pair. An embedded threshold and an undulating threshold were selected during embedding,and adjusting the pair of thresholds achieved the best performance. The experimental results have demonstrated the proposed method obtains good performance both in embedding payload and visual quality.

Key words: predictionerror, histogram pair, reversible data hiding, embedded threshold, undulating threshold

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