基于图像块分类阈值优化的改进可逆图像伪装

doi:10.3969/j.issn.0255-8297.2018.02.003

应用科学学报 ›› 2018, Vol. 36 ›› Issue (2): 237-246.doi: 10.3969/j.issn.0255-8297.2018.02.003

基于图像块分类阈值优化的改进可逆图像伪装

刘小凯¹, 姚恒^1,2, 秦川¹

1. 上海理工大学光电信息与计算机工程学院, 上海 200093;
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

收稿日期:2018-02-01 出版日期:2018-03-31 发布日期:2018-03-31
通信作者: 姚恒,博士,讲师,研究方向:多媒体信息安全,E-mail:hyao@usst.edu.cn E-mail:hyao@usst.edu.cn
基金资助:
国家自然科学基金（No.61702332，No.61672354）；广西多源信息挖掘与安全重点实验室开放基金（No.MIMS16-03）资助

Improved Reversible Image Camouflage Method Based on Image Block Classifcation Threshold Optimization

LIU Xiao-kai¹, YAO Heng^1,2, QIN Chuan¹

1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin 541004, Guangxi Province, China

Received:2018-02-01 Online:2018-03-31 Published:2018-03-31

摘要/Abstract

摘要：

为了提高数字图像伪装中生成的伪装图像的视觉质量，提出一种基于图像块分类阈值优化的可逆图像伪装方案.根据统计特征对原始图像子块和目标图像子块进行分类，通过优化分类阈值使得生成伪装图像和目标图像的均方差最小，然后进行相应类内图像块匹配、块线性变换、块旋转和翻转校正，最终使原始图像伪装成目标图像.采用可逆信息隐藏的算法将恢复原图所需的变换参数信息嵌入伪装图像，接收方提取辅助信息，从而实现原始图像的无损恢复.实验结果表明，该算法生成的伪装图像的视觉效果比未经阈值优化的伪装图像的效果更好.

关键词: 图像伪装, 阈值优化, 块分类, 可逆信息隐藏

Abstract:

In order to improve the visual quality of stego images in digital image camouflage, a method of reversible image camouflage based on the threshold optimization of image sub-block classifcation is proposed. First, the sub-blocks of the original image and the cover image are classifed, respectively, according to their statistical characteristics. The threshold for classifcation is optimized through minimizing the mean square error of the camouflage image and cover image. Then, after the processes of the image sub-block matching, image sub-block linear transformation, sub-block rotation and horizontal flipping, a stego image which is visually similar to the cover image is generated. The transformation parameter information used for restoring the original image is eventually embedded into the stego image in a reversible manner to generate the fnal camouflage image. Therefore, the receiver side can extract the auxiliary information to realize the lossless recovery of the original image. The experimental results show that the visual quality of the camouflage image generated by the proposed method is better than that of the image without classifcation threshold optimization.

Key words: threshold optimization, image camouflage, block classifcation, reversible data hiding

中图分类号:

TP317.4

刘小凯, 姚恒, 秦川. 基于图像块分类阈值优化的改进可逆图像伪装[J]. 应用科学学报, 2018, 36(2): 237-246.

LIU Xiao-kai, YAO Heng, QIN Chuan. Improved Reversible Image Camouflage Method Based on Image Block Classifcation Threshold Optimization[J]. Journal of Applied Sciences, 2018, 36(2): 237-246.

参考文献

[1] Rivest R. The RC4 encryption algorithm[J]. RSA Data Security Inc, 1992, 20(1):86-96.
[2] Paillier P. Public-key cryptosystems based on composite degree residuosity classes[C]//International Conference on Theory and Application of Cryptographic Techniques. Springer-Verlag, 1999:223-238.
[3] 丁玮,闫伟齐,齐东旭. 基于Arnold变换的数字图像置乱技术[J]. 计算机辅助设计与图形学学报,2001, 13(4):338-341. Ding W, Yan W Q, Qi D X. Digital image scrambling technology based on Arnold transformation[J]. Journal of Computer Aided Design & Computer Graphics, 2001, 13(4):338-341. (in Chinese)
[4] 向德生,熊岳山. 基于约瑟夫遍历的数字图像置乱算法[J]. 计算机工程与应用,2005, 41(10):44-46. Xiang D S, Xiong Y S. Digital image scrambling based on Josephus traversing[J]. Computer Engineering and Applications, 2005, 41(10):44-46. (in Chinese)
[5] 张贵仓,王让定,章毓晋. 基于迭代混合的数字图像隐藏技术[J]. 计算机学报,2003, 26(5):569-574. Zhang G C, Wang R D, Zhang Y J. Digital image information hiding technology based on iterative blending[J]. Chinese Journal of Computers, 2003, 26(5):569-574. (in Chinese)
[6] 丁玮. 数字图像信息安全的算法研究[D]. 北京:中国科学院计算技术研究所,2000.
[7] 吴军,吴秋新. 一种基于七巧板游戏的数字图像信息伪装方法[J]. 计算机应用,2004, 24(6):125-128. Wu J, Wu Q X. A steganography method of digital image information based on tangram[J]. Computer Applications, 2004, 24(6):125-128. (in Chinese)
[8] Lai I J, Tsai W H. Secret-fragment-visible mosaic image-a new computer art and its application to information hiding[J]. IEEE Transactions on Information Forensics & Security, 2011, 6(3):936-945.
[9] Lee Y L, Tsai W H. A new secure image transmission technique via secret-fragment-visible mosaic images by nearly reversible color transformations[J]. IEEE Transactions on Circuits & Systems for Video Technology, 2014, 24(4):695-703.
[10] Reinhard E, Ashikhmin M, Gooch B, Shirley P. Color transfer between images[J]. IEEE Computer Graphics & Applications, 2001, 21(5):34-41.
[11] Zhang W M, Wang H, Hou D D, Yu N H. Reversible data hiding in encrypted images by reversible image transformation[J]. IEEE Transactions on Multimedia, 2016, 18(8):1469-1479.
[12] Hou D D, Zhang W M, Yu N H. Image camouflage by reversible image transformation[J]. Journal of Visual Communication and Image Representation, 2016, 40:225-236.
[13] Sachnev V, Kim H J, Nam J, Suresh S, Shi Y Q. Reversible watermarking algorithm using sorting and prediction[J]. IEEE Transactions on Circuits & Systems for Video Technology, 2009, 19(7):989-999.
[14] BossBase image database,[DB]. http://agents.fel.cvut.cz/stegodata/RAWs/

基于图像块分类阈值优化的改进可逆图像伪装

Improved Reversible Image Camouflage Method Based on Image Block Classifcation Threshold Optimization

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 9

编辑推荐

Metrics

本文评价

[1]	孙容海, 施林甫, 俞春强, 劳欢, 唐振军. 面向密文图像信息隐藏的随机插值方法[J]. 应用科学学报, 2020, 38(3): 419-430.
[2]	屈凌峰, 陈帆, 和红杰, 袁源. 基于位平面-块置乱的图像加密算法安全性分析[J]. 应用科学学报, 2019, 37(5): 631-642.
[3]	王俊祥, 毛宁雄, 赵怡, 王春桃. 面向全容量的高性能彩色图像可逆信息隐藏算法[J]. 应用科学学报, 2019, 37(5): 744-760.
[4]	何志红, 秦川, 周青. 大容量的密文域图像可逆信息隐藏算法[J]. 应用科学学报, 2018, 36(4): 611-627.
[5]	黄丹, 程思锦, 黄方军. 基于频段选择的JPEG图像可逆信息隐藏[J]. 应用科学学报, 2018, 36(2): 209-219.
[6]	陈艳, 俞春强, 侯晓杰, 张显全, 唐振军, 何南. 基于曲面插值的加密图像可逆信息隐藏算法[J]. 应用科学学报, 2018, 36(2): 220-236.
[7]	王晓雨, 马宾, 李健, 施云庆. 基于多元线性回归的自适应图像可逆信息隐藏误差预测算法[J]. 应用科学学报, 2018, 36(2): 362-370.
[8]	魏巍, 和红杰, 陈帆. 基于块分类编码的电子发票图像自恢复水印算法[J]. 应用科学学报, 2016, 34(5): 490-502.
[9]	闫兵, 柏森, 阳溢, 季晓勇. 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.