基于位平面压缩的密文医学图像可逆信息隐藏算法

doi:10.11772/j.issn.1001-9081.2016.11.3088

计算机应用 ›› 2016, Vol. 36 ›› Issue (11): 3088-3092.DOI: 10.11772/j.issn.1001-9081.2016.11.3088

基于位平面压缩的密文医学图像可逆信息隐藏算法

郑洪英, 任雯, 程惠惠

重庆大学计算机学院, 重庆 400044

收稿日期:2016-05-25 修回日期:2016-06-20 出版日期:2016-11-10 发布日期:2016-11-12
通讯作者: 任雯
作者简介:郑洪英(1975-),女,重庆人,副教授,博士,主要研究方向:图像加密、信息隐藏、压缩感知、多媒体安全;任雯(1992-),女,四川邻水人,硕士研究生,主要研究方向:可逆信息隐藏、数字水印;程惠惠(1989-),女,河南信阳人,硕士,主要研究方向:图像加密、信息隐藏。

Reversible data hiding in encrypted medical images based on bit plane compression

ZHENG Hongying, REN Wen, CHENG Huihui

College of Computer Science, Chongqing University, Chongqing 400044, China

Received:2016-05-25 Revised:2016-06-20 Online:2016-11-10 Published:2016-11-12

摘要/Abstract

摘要： 针对目前医学图像可逆信息隐藏算法嵌入容量小、需要对图像进行感兴趣区域（ROI）划分、接收方操作不灵活等缺点，结合医学图像特点，提出了一种基于位平面压缩的可分离式密文域信息隐藏算法。首先，将256级灰度医学图像分解成8个位平面，压缩高4个位平面，用峰值点像素值填充压缩后的空间，重构图像；然后，对重构的图像头部、中部、尾部分别加密；最后，在尾部根据嵌入密钥选取位置，通过直方图平移算法嵌入信息，接收方可根据密钥持有情况实现信息提取与图像恢复的可分离操作。实验结果表明，通过压缩图像预留空间来存放信息避免了辅助信息的传输，能有效提高嵌入容量，同时具有较高的安全性。

关键词: 医学图像, 游程编码, 直方图平移, 信息隐藏, 完全可逆

Abstract: The present reversible data hiding algorithms in encrypted medical image have low embedding capacity and need to partition Regions Of Interest (ROI), the receiver operation is not flexible. Combining with the characteristics of medical images, a novel separable reversible data hiding method in encrypted medical images was proposed. Firstly, the medical image with 256 gray levels was decomposed into 8 bit planes, and the highest four bit planes were compressed, which left some space to fill with the peak pixel values. Then the image was reconstructed. The head, middle, tail of the reconstructed image were encrypted respectively. After that, information was embedded in the encrypted image by histogram shifting, and the position was chosen by the data hiding key in the tail. For the receiver, information extraction and image restoration can be separated operations according to keys. The experimental results demonstrate that information can be stored in the compressed image to avoid auxiliary information transmission, which effectively improves the embedding capacity with higher security.

Key words: medical image, Run-Length-Encoding (RLE), histogram shifting, data hiding, fully reversible

中图分类号:

TP309.7

郑洪英, 任雯, 程惠惠. 基于位平面压缩的密文医学图像可逆信息隐藏算法[J]. 计算机应用, 2016, 36(11): 3088-3092.

ZHENG Hongying, REN Wen, CHENG Huihui. Reversible data hiding in encrypted medical images based on bit plane compression[J]. Journal of Computer Applications, 2016, 36(11): 3088-3092.

参考文献

[1] ZHANG X P. Reversible data hiding in encrypted image[J]. IEEE Signal Processing Letters, 2011, 18(4):255-258.
[2] HONG W, CHEN T S, WU H Y. An improved reversible data hiding in encrypted images using side match[J]. IEEE Signal Processing Letters, 2012, 19(4):199-202.
[3] ZHANG X P. Separable reversible data hiding in encrypted image[J]. IEEE Transactions on Information Forensics and Security, 2012, 7(2):826-832.
[4] WU H T, HUANG J W, SHI Y Q. A reversible data hiding method with contrast enhancement for medical images[J].Journal of Visual Communication and Image Representation, 2015,31(C):146-153.
[5] 邓小鸿, 陈志刚, 梁涤青, 等. 分区域的医学图像高容量无损信息隐藏方法[J].通信学报, 2015, 36(1):21-31.(DENG X H,CHEN Z G,LIANG D Q, el al. Region-based lossless data hiding with high capacity for medical images[J].Journal on Communications,2015,36(1):21-31.)
[6] 李文娜, 高立群, 孔祥勇, 等.ROI和轮廓波结合的医学图像盲水印算法[J].哈尔滨工程大学学报, 2013,34(7):918-923.(LI W N,GAO L Q,KONG X Y, et al. A blind watermark algorithm for medical images using ROI and contourlet[J]. Journal of Harbin Engineering University, 2013, 34(7):918-923.)
[7] MOUSAVI S M, NAGHSH A, ABU-BAKAR S A R.A heuristic automatic and robust ROI detection method for medical image warermarking[J].Journal of Digital Imaging, 2015,28(4):417-427.
[8] 侯宏化.数字图像处理与分析[M].北京:北京理工大学出版社,2011:144-145.(HOU H H. Digital Image Processing and Analysis[M]. Beijing:Beijing Institute of Technology Press, 2011:144-145.)
[9] 谢涛.Logistic映射在密码学中的应用研究[D].湘潭:湘潭大学,2014:20-33.(XIE T. On cryptographic application of Logistic map[D].Xiangtan:Xiangtan University,2014:20-33.)
[10] FU C, MENG W H, ZHAN Y F, et al. An efficient and secure medical image protection scheme based on chaotic maps[J]. Computers in Biology and Medicine, 2013, 43(8):1000-1010.
[11] NI Z C, SHI Y Q, ANSARI N W, et al. Reversible data hiding[J]. IEEE Transactions on Circuits and System for Video Technology, 2006, 16(3):354-362.

[1]	张林发, 张榆锋, 王琨, 李支尧. 基于直觉模糊集和亮度增强的医学图像融合[J]. 计算机应用, 2021, 41(7): 2082-2091.
[2]	黄梨, 卢龙. 基于长距离依赖编码与深度残差U-Net的缺血性卒中病灶分割[J]. 计算机应用, 2021, 41(6): 1820-1827.
[3]	董阳, 潘海为, 崔倩娜, 边晓菲, 滕腾, 王邦菊. 面向多模态磁共振脑瘤图像的小样本分割方法[J]. 计算机应用, 2021, 41(4): 1049-1054.
[4]	魏淳武, 赵涓涓, 唐笑先, 强彦. 基于多时期蒸馏网络的随访数据知识提取方法[J]. 计算机应用, 2021, 41(10): 2871-2878.
[5]	高海军, 曾祥银, 潘大志, 郑伯川. 基于U-Net改进模型的直肠肿瘤分割方法[J]. 计算机应用, 2020, 40(8): 2392-2397.
[6]	魏小娜, 邢嘉祺, 王振宇, 王颖珊, 石洁, 赵地, 汪红志. 基于改进U-Net的关节滑膜磁共振图像的分割[J]. 计算机应用, 2020, 40(11): 3340-3345.
[7]	潘沛克, 王艳, 罗勇, 周激流. 基于U-net模型的全自动鼻咽肿瘤MR图像分割[J]. 计算机应用, 2019, 39(4): 1183-1188.
[8]	任帅, 徐振超, 王震, 贺媛, 张弢, 苏东旭, 慕德俊. 基于多融合态的低密度三维模型信息隐藏算法[J]. 计算机应用, 2019, 39(4): 1100-1105.
[9]	李琦, 颜斌, 陈娜, 杨红梅. 基于单向预测误差扩展的三维医学图像可逆水印算法[J]. 计算机应用, 2019, 39(2): 483-487.
[10]	秦品乐, 李启, 曾建潮, 张娜, 宋宇龙. 基于多尺度密集网络的肺结节图像检索算法[J]. 计算机应用, 2019, 39(2): 392-397.
[11]	高媛, 吴帆, 秦品乐, 王丽芳. 生成对抗残差网络的医学图像融合算法[J]. 计算机应用, 2019, 39(12): 3528-3534.
[12]	梁志刚, 顾军华. 改进头脑风暴优化算法与Powell算法结合的医学图像配准[J]. 计算机应用, 2018, 38(9): 2683-2688.
[13]	张茹, 黄福鸿, 刘建毅, 祝锋. 基于信息隐藏技术的木马植入方法[J]. 计算机应用, 2018, 38(8): 2267-2273.
[14]	郑鸿昌, 王春桃, 王俊祥. 基于LASSO的可逆图像水印算法[J]. 计算机应用, 2018, 38(8): 2287-2292.
[15]	才雪, 杨杨, 肖星星. 基于纹理度划分的医学图像可逆信息隐藏方法[J]. 计算机应用, 2018, 38(8): 2293-2300.

基于位平面压缩的密文医学图像可逆信息隐藏算法

Reversible data hiding in encrypted medical images based on bit plane compression

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics