计算机与现代化 ›› 2020, Vol. 0 ›› Issue (09): 37-42.doi: 10.3969/j.issn.1006-2475.2020.09.007

• 信息安全 • 上一篇    下一篇

一种基于熵理论的自适应水印嵌入算法

  

  1. (1.太原广播电视大学教学研究中心,山西太原030024;2.太原科技大学应用科学学院,山西太原030024)
  • 收稿日期:2020-02-21 出版日期:2020-09-24 发布日期:2020-09-24
  • 作者简介:张帅(1983—),男,山西榆社人,讲师,硕士,研究方向:数字图像处理,水印技术,E-mail: 39736632@qq.com; 通信作者:杨雪霞(1985—),女,河北邯郸人,副教授,硕士生导师,研究方向:电子封装,数字图像处理,E-mail: 13753486687@126.com。
  • 基金资助:
    国家自然科学基金资助项目(11602157); 山西电大校基金资助规划课题(SXDDKT201903)

An Adaptive Watermark Embedding Algorithm Based on Entropy Theory

  1. (1. Teaching Research Center, Taiyuan Radio & TV University, Taiyuan 030024, China;
    2. College of Applied Sciences, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Received:2020-02-21 Online:2020-09-24 Published:2020-09-24

摘要: 为了提高数字图像嵌入水印时的不可感知性与鲁棒性,提出一种利用图像信息熵与边缘熵理论并结合果蝇优化算法的水印嵌入方案。首先对载体图像进行分块,并计算每个分块的信息熵与边缘熵,将每个分块的2个熵值相加并排序。然后根据嵌入水印的容量选择熵值较高的分块,并将每一位水印信息嵌入到经过小波变换与奇异值分解的分块中。最后为了进一步平衡嵌入水印不可感知性与鲁棒性之间的矛盾,利用果蝇算法对嵌入水印的强度进行自适应优化。实验结果表明该方法具有更好的不可感知性,在面对多种类型、多种强度的模拟攻击时比同类算法表现出更强的鲁棒性。

关键词: 信息熵, 边缘熵, 果蝇优化, 数字水印, 嵌入强度

Abstract: In order to improve the imperceptibility and robustness of the digital image with watermark, a watermark embedding scheme based on image information entropy and edge entropy theory combined with fruit fly optimization algorithm is proposed. Firstly, the carrier image is divided into blocks, and the information entropy and edge entropy of each block are calculated. The two entropy values of each block are added and sorted. Then, the blocks with higher entropy value are selected according to the capacity of embedded watermark, and each bit of watermark is embedded into the blocks which are decomposed by wavelet transform and singular value. Finally, in order to further balance the contradiction between the transparency and robustness of the embedded watermark, the intensity of the embedded watermark is optimized by using the fruit fly algorithm. The experimental results show that the proposed method has better imperceptibility and is more robust than similar algorithms in the face of multiple types and intensity of simulated attacks.

Key words: information entropy, edge entropy, fruit fly optimization, digital watermark, embedding intensity

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