基于邻接差值与块分类的密文域可逆信息隐藏
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安徽理工大学计算机科学与工程学院

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国家自然科学基金(62102003);国家重大专项(2020YFB1314103);安徽省自然科学基金(2108085QF258);安徽省博士后基金(2022B623)


Reversible Data Hiding in Encrypted Images Based on Adjacency Difference and Block Classification
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安徽理工大学计算机科学与工程学院

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National Natural Science Foundation of China (62102003); National Major Special Project(2020YFB1314103); Natural Science Foundation of Anhui Province of China (2108085QF258); Anhui Postdoctoral Science Foundation (2022B623)

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    摘要:

    针对密文域可逆信息隐藏算法存在像素利用率低和嵌入容量小等问题,本文提出了一种基于邻接差值和块分类的密文域可逆信息隐藏算法。首先,充分利用原始图像的空间相关性,通过计算得到邻接差值图像,根据图像块的最大值实现初次块分类操作;其次,对初次分类中不可嵌入图像块,采用中值边缘预测器来预测像素,完成第二次块分类;然后,执行图像加密;最后,通过位替换,将辅助信息和秘密信息嵌入加密图像。实验结果表明,本文算法相较于现有算法,在BOSSbase、BOWS-2和UCID三个数据集上的平均嵌入率分别提高0.06bpp、0.01bpp和0.15bpp以上,能够获得较高的嵌入容量。

    Abstract:

    The existing reversible data hiding in encrypted image algorithms have the problems of poor utilization of pixels, and small embedding capacity. Addressing such issues, a Reversible Data Hiding in Encrypted Images based on Adjacency Difference and Block Classification scheme is proposed. Firstly, the spatial correlation of the original image is fully utilised to obtain the adjacency difference image by calculation, and the initial block classification operation is realised according to the maximum value of the image block; secondly, the median edge predictor is used to predict the pixels for the non-embeddable image blocks in the initial classification to complete the second block classification; then, the image encryption is executed; finally, the auxiliary data and secret data are embedded in the encrypted image by bit substitution. The experimental results show that the average embedding rate of this paper's algorithm is over 0.06bpp, 0.01bpp and 0.15bpp higher on the BOSSbase, BOWS-2 and UCID datasets respectively compared to the existing algorithms.

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  • 收稿日期:2023-02-20
  • 最后修改日期:2023-05-16
  • 录用日期:2023-06-06
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