[1]李亚翔,张显全,俞春强,等.采用相邻像素预测的可逆信息隐藏算法[J].华侨大学学报(自然科学版),2020,41(2):223-229.[doi:10.11830/ISSN.1000-5013.201911018]
 LI Yaxiang,ZHANG Xianquan,YU Chunqiang,et al.Reversible Data Hiding Algorithm Using Adjacent Pixels Prediction[J].Journal of Huaqiao University(Natural Science),2020,41(2):223-229.[doi:10.11830/ISSN.1000-5013.201911018]
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采用相邻像素预测的可逆信息隐藏算法()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第41卷
期数:
2020年第2期
页码:
223-229
栏目:
出版日期:
2020-03-20

文章信息/Info

Title:
Reversible Data Hiding Algorithm Using Adjacent Pixels Prediction
文章编号:
1000-5013(2020)02-0223-07
作者:
李亚翔1 张显全123 俞春强1 唐振军12
1. 广西师范大学 计算机科学与信息工程学院, 广西 桂林 541004;2. 广西师范大学 广西多源信息挖掘与安全重点实验室, 广西 桂林 541004;3. 桂林电子科技大学 广西高校云计算与复杂系统重点实验室, 广西 桂林 541004
Author(s):
LI Yaxiang1 ZHANG Xianquan123 YU Chunqiang1 TANG Zhenjun12
1. College of Computer Science and Information Engineering, Guangxi Normal University, Guilin 541004, China; 2. Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin 541004, China; 3. Guangxi Colleges and Unive
关键词:
可逆信息隐藏 相邻像素 预测误差 局部线性预测
Keywords:
reversible data hiding adjacent pixels prediction error local linear prediction
分类号:
TP391
DOI:
10.11830/ISSN.1000-5013.201911018
文献标志码:
A
摘要:
为了提高图像信息隐藏算法的信息嵌入容量和载密图像的保真度,提出一种采用相邻像素预测的可逆信息隐藏算法.构建局部线性预测模型,以待预测像素的3个相邻像素为目标像素,通过目标像素的相邻像素建立线性方程组,求解预测模型参数.应用预测模型进行预测,计算预测误差,绘制预测误差直方图,通过直方图平移实现可逆信息隐藏.实验结果表明:文中算法可通过较少的预测像素进行预测,比其他算法具有更高的预测精度和更大的信息嵌入容量.
Abstract:
In order to improve the data embedding capacity of the image data hiding algorithm and the fidelity of the masked image, this paper propose a reversible data hiding algorithm based on adjacent pixels prediction. Building local linear prediction model and taking the three adjacent predicted pixels as the target pixel, the linear equations are established with the adjacent pixels of the target pixel, and the parameters of the prediction model are solved. Using the prediction model to predict, calculate prediction error and plot prediction error histograms, then implement reversible date hiding algorithm by histogram shift. The experimental results show that the proposed algorithm in this paper can predict with fewer prediction pixels, and has higher prediction accuracy and larger data embedding capacity than that of other algorithms.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2019-11-16
通信作者: 张显全(1964-),男,副教授,主要从事计算机图形图像处理的研究.E-mail:zxq6622@163.com.
基金项目: 国家自然科学基金资助项目(61562007, 61762017); 广西自然科学基金资助项目(2017GXNSFAA198 222); 广西师范大学计算机科学与信息工程学院创新项目(JXYJSKT-2019-001)
更新日期/Last Update: 2020-03-20