广西师范大学学报（自然科学版） ›› 2018, Vol. 36 ›› Issue (2): 24-32.doi: 10.16088/j.issn.1001-6600.2018.02.004

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一种基于多预测值分类的可逆信息隐藏算法

俞春强1,2,邓方舟3,张显全1,2,4*,唐振军4,陈艳1,2,何南3   

  1. 1.广西师范大学网络信息中心,广西桂林 541004;
    2.桂林电子科技大学广西信息科学实验中心,广西桂林 541004;
    3.桂林师范高等专科学校网络与教育技术中心,广西桂林 541001;
    4. 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
  • 收稿日期:2017-08-08 出版日期:2018-05-10 发布日期:2018-07-18
  • 通讯作者: 张显全(1964—),男,重庆人,广西师范大学教授。E-mail: zxq6622@163.com
  • 基金资助:
    国家自然科学基金(61762017,61363034,61562007,81701780);教育部“春晖计划”合作科研项目(Z2015149);广西自然科学基金(2015GXNSFDA139040,2017GXNSFAA198222,2017GXNSFBA198221);广西信息科学实验中心项目(20130204);广西教育厅高校科研项目(LX2014056,LX2014115,KY2015LX006);广西高校云计算与复杂系统重点实验室项目(15202);广西区域多源信息集成与智能处理协同创新中心项目;广西师范大学校级项目青年课题

A Reversible Information Hiding Method Based on Multiple Prediction Values

YU Chunqiang1,2,DENG Fangzhou3,ZHANG Xianquan1,2,4*,TANG Zhenjun4,CHEN Yan1,2,HE Nan3   

  1. 1. Network Information Center,Guangxi Normal University,Guilin Guangxi 541004,China;
    2. College of Computer Science and Information Technology,Guangxi Normal University,Guilin Guangxi 541004,China;
    3. Guangxi Experiment Center of Information Science,Guilin University of Electronic Technology,Guilin Guangxi 541004,China;
    4. Network and Educational Technology Center,Guilin Normal College,Guilin Guangxi 541001,China
  • Received:2017-08-08 Online:2018-05-10 Published:2018-07-18

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摘要： 本文提出一种基于多预测值分类的可逆信息隐藏算法。该算法通过多种预测算子对像素值进行预测,确定最大预测值和最小预测值的下标,根据最大预测值和最小预测值与当前像素值的关系进行分类。若最大预测值与最小预测值相等,则最优预测值为最小预测值;若当前像素值大于或等于最大预测值,则最优预测值为最大预测值;若当前像素值小于或等于最小预测值,则最优预测值为最小预测值。计算当前像素值与最优预测值的差值,然后选择相应差值隐藏秘密信息。该算法能够准确提取秘密信息,并无损恢复原始载体图像,且载密图像具有较好的视觉效果。

关键词: 多预测值, 分类, 差值, 可逆信息隐藏

Abstract: A reversible information hiding method based on multiple prediction values is proposed in this paper. Multiple Predictors are firstly applied to predict a pixel value. The indexes of maximum prediction value and minimum prediction value are thus determined. Then,the relationship among maximum prediction value,minimum prediction value and current pixel value is used for classification. If the maximum prediction value is equal to the minimum prediction value,the optimal prediction value is the minimum prediction value. If the current pixel value is equal to or greater than maximum prediction value,the optimal prediction value is the maximum prediction value. If the current pixel value is equal to or less than minimum prediction value,the optimal prediction value is the minimum prediction value. Finally,the difference value between the current pixel value and the optimal prediction value is calculated and the corresponding different value is selected for data hiding. The method can extract secret information accurately and recover the original image without loss of information. The stego-image has good visual quality.

Key words: multiple prediction values, classification, difference value, reversible information hiding

中图分类号: 

  • TP311
[1] 王朔中,张新鹏,张卫明.以数字图像为载体的隐写分析研究进展[J].计算机学报,2009,32(7):1247-1263.DOI:10.3724/SP.J.1016.2009.01247.
[2] ZHANG Xianquan,SUN Zerui,TANG Zhenjun,et al. High capacity data hiding based on interpolated image[J].Multimedia Tools and Applications,2017,76(7):9195-9218.DOI:10.1007/s11042-016-3521-0.
[3] WANG Chunpeng,WANG Xingyuan,ZHANG Chuan,et al. Geometric correction based color image watermarking using fuzzy least squares support vector machine and Bessel K form distribution[J]. Signal Processing,2017,134:197-208.DOI:10.1016/j.sigpro.2016.12.010.
[4] WANG Chunpeng,WANG Xingyuan,XIA Zhiqiu,et al.Geometrically resilient color image zero-watermarking algorithm based on quaternion Exponent moments[J]. Journal of Visual Communication and Image Representation,2016,41: 247-259.DOI:10.1016/j.jvcir.2016.10.004.
[5] WANG Chunpeng,WANG Xingyuan,XIA Zhiqiu. Geometrically invariant image watermarking based on fast Radial Harmonic Fourier Moments[J].Signal Processing: Image Communication,2016,45: 10-23.DOI:10.1016/j.image.2016.03.007.
[6] FRIDRICH J,GOLJAN M,DU R. Lossless data embedding:new paradigm in digital watermarking[J]. EURASIP J Appl Signal Process, 2002(2):185-196.DOI:10.1155/S1110865702000537.
[7] CELIK M U,SHARMA G,TEKALP A M,et al. Lossless generalized:LSB data embedding[J]. IEEE Transactions on Image Processing,2005,14(2):253-266.DOI:10.1109/TIP.2004.840686.
[8] TIAN Jun. Reversible data embedding using a difference expansion[J]. IEEE Transactions on Circuits and Systems for Video Technology,2003,13(8):890-896.DOI:10.1109/TCSVT.2003.815962.
[9] LEE Chihchiang,WU Hsienchu,TSAI Chweishyong,et al. Adaptive lossless steganographic scheme with centralized difference expansion[J]. Pattern Recognition,2008,41(6):2097-2106.DOI:10.1016/j.patcog.2007.11.018.
[10] NI Zhicheng,SHI Yunqing,ANSARI N,et al,Reversible data hiding[J]. IEEE Transactions on Circuits and Systems for Video Technology,2006,16(3):354-362.DOI:10.1109/TCSVT.2006.869964.
[11] MA Xiaoxiao,PAN Zhibin,HU Sen,et al. High-fidelity reversible data hiding scheme based on multi-predictor sorting and selecting mechanism[J].Journal of Visual Communication and Image Representation,2015,28:71-82.DOI:10.1016/j.jvcir.2015.01.012.
[12] ZHANG Xianquan,YU Chunqiang,WANG Xiaoyun,et al. A reversible data hiding scheme for JPEG images[J]. ICIC Express Letters,2013,7(9):2575-2580.
[13] LI Xiaolong,LI Jian,LI Bin,et al. High-fidelity reversible data hiding scheme based on pixel-value-ordering and prediction-error expansion[J]. Signal Processing. 2013,93(1):198-205.DOI:10.1016/j.sigpro.2012.07.025.
[14] PENG Fei,LI Xiaolong,YANG Bin.Improved PVO-based reversible data hiding[J].Digital Signal Processing,2014,25:255-265.DOI:10.1016/j.dsp.2013.11.002.
[15] WANG Xiang,DING Jing,PEI Qingqi.A novel reversible image data hiding scheme based on pixel value ordering and dynamic pixel block partition[J]. Information Sciences,2015,310:16-35.DOI:10.1016/j.ins.2015.03.022.
[16] 闫兵,柏森,阳溢,等.改进的PVO-k可逆信息隐藏算法[J]. 应用科学学报,2016,34(5):605-615.DOI:10.3969/j.issn.0255-8297.2016.05.013.
[17] WEINBERGER M J,SEROUSSI G,SAPIRO G.The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS[J].IEEE Transactions on Image Processing,2000,9(8):1309-1324.DOI:10.1109/83.855427.
[18] WU Xiaolin,MEMON N. Context-based,adaptive,lossless image coding[J]. IEEE Transactions on Communications,1997,45(4):437-444.DOI:10.1109/26.585919.
[19] JIANG J,GUO B,YANG S Y.Revisiting the JPEG-LS prediction scheme[J]IEE Proceedings:Vision,Image and Signal Processing, 2000,147(6):575-580.DOI:10.1049/ip-vis:20000767.
[20] TANG Haijiang,KAMATA S.A gradient based predictive coding for lossless image compression[J].IEICE Transactions on Information and Systems,2006,E89-D(7): 2250-2256.DOI: 10.1093/ietisy/e89-d.7.2250.
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