基于多码本矢量量化的图像篡改恢复

doi:10.3969/j.issn.0255-8297.2015.06.005

应用科学学报 ›› 2015, Vol. 33 ›› Issue (6): 615-627.doi: 10.3969/j.issn.0255-8297.2015.06.005

基于多码本矢量量化的图像篡改恢复

季平, 秦川

上海理工大学光电信息与计算机工程学院, 上海 200093

收稿日期:2015-06-30 修回日期:2015-08-06 出版日期:2015-11-30 发布日期:2015-11-30
通信作者: 秦川,博士,副教授,研究方向:数字图像处理、多媒体信息安全,E-mail:qin@usst.edu.cn E-mail:qin@usst.edu.cn
基金资助:
国家自然科学基金(No.61303203);上海市自然科学基金(No.13ZR1428400);上海市教育委员会科研创新项目基金(No.14YZ087);上海智能家居大规模物联共性技术工程中心项目基金(No.GCZX14014);沪江基金研究基地专项基金(No.C14001);沪江基金(No.C14002)资助

Image Tampering Recovery Based on Multi-codebook Vector Quantization

JI Ping, QIN Chuan

School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Received:2015-06-30 Revised:2015-08-06 Online:2015-11-30 Published:2015-11-30

摘要/Abstract

摘要： 提出一种用于数字图像篡改检测与内容恢复的自嵌入脆弱图像水印算法.对原始图像每个不重叠分块进行基于边缘复杂度的内容分析,选择不同大小的矢量量化码本进行分块压缩,可获得相应的标识符和表示图像分块主要内容的索引值以构成压缩码.将其复制多份后作为参考比特,通过密钥嵌入至其他多个分块中.用于篡改定位的认证比特则被嵌入每个分块本身.由于在多码本矢量量化协同下生成的参考比特具有较高的内容表示效率,该算法在篡改率相同的条件下可取得更理想的内容恢复性能,这一结论得到了实验结果的验证.

关键词: 脆弱水印, 矢量量化, 多码本, 篡改检测, 内容恢复

Abstract: We propose a self-embedding fragile watermarking scheme to detect image tampering and recover original contents. By analyzing edge complexity of all non-overlapping blocks in the original image, the codebooks of vector quantization with different sizes are chosen to compress these blocks. The corresponding indicator and the index value representing the main content of the image block are collected to form the compression codes. They are duplicated to be used as reference-bits. These reference bits are then embedded into other multiple blocks according to secret keys, and authentication-bits are embedded into each block itself. Since the reference-bits based on multiple-codebook vector quantization have high efficiency in representing the image contents, the proposed scheme can achieve good performance of content recovery as compared to the reported methods. This is verified by experimental results.

Key words: fragile watermarking, vector quantization, multi-codebook, tampering detection, content recovery

中图分类号:

TP391

季平, 秦川. 基于多码本矢量量化的图像篡改恢复[J]. 应用科学学报, 2015, 33(6): 615-627.

JI Ping, QIN Chuan. Image Tampering Recovery Based on Multi-codebook Vector Quantization[J]. Journal of Applied Sciences, 2015, 33(6): 615-627.

参考文献

[1] Fridrich J, Goljan M. Images with self-correcting capabilities[C]//Proceedings of IEEE International Conference on Image Processing, 1999:792-796.

[2] Qian Z X, Feng G R. Inpainting assisted self-recovery with decreased embedding data[J]. IEEE Signal Processing Letters, 2010, 17(11):929-932.

[3] 马左红,华文深,李晓明,张悦.基于双随机相位加密技术的图像隐藏方法[J].光学仪器, 2012, 34(4):21-25. Ma Z H, Hua W S, Li X M, Zhang Y. Image hiding method based on double random phase encryption technology[J]. Optical Instruments, 2012, 34(4):21-25. (in Chinese)

[4] 付天舒,韩春杰,隋鑫.基于DCT变换的自适应图像水印实现[J].光学仪器, 2013, 35(3):51-57. Fu T S, Han C J, Sui X. Adaptive image watermark realization based on DCT transform[J]. Optical Instruments, 2013, 35(3):51-57. (in Chinese)

[5] 杨杉杉,秦川,徐伯庆.一种基于安全隐藏的图像分层篡改检测和内容恢复算法[J].计算机应用研究, 2015, 2:507-511. Yang S S, Qin C, Xu B Q. Fragile watermarking based on secure embedding for hierarchical tampering detection and content recovery[J]. Computer Application and Research, 2015, 2:507-511. (in Chinese)

[6] Suthaharan S. Fragile image watermarking using a gradient image for improved localization and security[J]. Pattern Recognition Letters, 2004, 25(16):1893-1903.

[7] Walton S. Image authentication for a slippery new age[J]. Dr Dobb's Journal, 1995, 20(4):18-26.

[8] Chang C C, Hu Y S, Lu T C. A watermarking-based image ownership and tampering authentication scheme[J]. Pattern Recognition Letters, 2006, 27(5):439-446.

[9] He H J, Chen F, H. Tai M, Kalker T, Zhang J S. Performance analysis of a blockneighborhood-based self-recovery fragile watermarking scheme[J]. IEEE Transactions on Information Forensics and Security, 2012, 7(1):185-196.

[10] Qin C, Chang C C, Chen K N. Adaptive self-recovery for tampered images based on VQ indexing and inpainting[J]. Signal Processing, 2013, 93(4):933-946.

[11] Qin C, Chang C C, Chen P Y. Self-embedding fragile watermarking with restoration capability based on adaptive bit allocation mechanism[J]. Signal Processing, 2012, 92(4):1137-1150.

[12] Korus P, Dziech A. Adaptive self-embedding scheme with controlled reconstruction performance[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(2):169-181.

[13] Korus P, Dziech A. Efficient method for content reconstruction with self-embedding[J]. IEEE Transactions on Image Processing, 2013, 22(3):1134-1147.

[14] Lin P L, Hsieh C K, Huang P W. A hierarchical digital watermarking method for image tamper detection and recovery[J]. Pattern Recognition, 2005, 38(12):2519-2529.

[15] Lee T Y, Lin S D. Dual watermark for image tamper detection and recovery[J]. Pattern Recognition, 2008, 41(11):3497-3506.

[16] Zhang X P, Wang S Z, Qian Z X. Self-embedding watermark with flexible restoration quality[J]. Multimedia Tools and Applications, 2011, 54(2):385-395.

[17] Zhang X P, Wang S Z, QianZ X, Feng G R. Reference sharing mechanism for watermark self-embedding[J]. IEEE Transactions on Image Processing, 2011, 20(2):485-495.

[18] Yang C, Shen J. Recover the tampered image based on VQ indexing[J]. Signal Processing, 2010, 90(1):331-343.

[19] Gray R M. Vector quantization[J]. IEEE ASSP Magazine, 1984, 1(2):4-29.

[20] Linde Y, Buzo A, Gray R M. An algorithm for vector quantizer design[J]. IEEE Transactions on Communication, 1980, 28(1):84-95.

[21] Canny J. A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6):679-698.

基于多码本矢量量化的图像篡改恢复

Image Tampering Recovery Based on Multi-codebook Vector Quantization

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 12

编辑推荐

Metrics

本文评价

[1]	赵琰, 周晓炜, 沈麒. 基于对立色与显著区域的紧凑图像哈希算法[J]. 应用科学学报, 2019, 37(5): 691-703.
[2]	王金伟, 徐春晖. 基于QPCA的彩色图像复制粘贴检测[J]. 应用科学学报, 2019, 37(2): 291-300.
[3]	苏文煊, 方针. 基于CFA插值特性不一致的图像真伪鉴别[J]. 应用科学学报, 2019, 37(1): 33-40.
[4]	李纪成, 胡永健, Al-Alas Mohammed, 熊艺纯, 文东霞, 任圆圆, 廖广军. 视频篡改检测数据库的扩充及其有效性验证[J]. 应用科学学报, 2018, 36(2): 347-361.
[5]	史骏鹏, 吴一全. 基于QR分解的NSCT域指纹图像脆弱水印算法[J]. 应用科学学报, 2017, 35(6): 735-744.
[6]	张伟伟, 杨正洪, 韩洪立, 王珺斌, 牛少彰. 特征增强的平滑区域篡改检测算法[J]. 应用科学学报, 2017, 35(5): 537-544.
[7]	王慧丽, 秦川, 高丽萍, 陈庆奎. 基于恢复信息共享机制的最优自嵌入算法[J]. 应用科学学报, 2016, 34(6): 677-690.
[8]	陈竺益, 方针. 基于色像差特性的图像篡改检测[J]. 应用科学学报, 2015, 33(6): 604-614.
[9]	张晓琳，方针，张新鹏. 利用通道间相关性的CFA图像盲取证[J]. 应用科学学报, 2015, 33(1): 87-94.
[10]	赵琰1;2，王朔中1，姚恒1，吴蔚1. 结合保角变换和Zernike矩的稳健图像Hash[J]. 应用科学学报, 2012, 30(1): 75-81.
[11]	丁琦，平西建. 基于子带谱平滑度的音频篡改检测[J]. 应用科学学报, 2010, 28(2): 142-146.
[12]	刘翠卿+;平西建;张涛王云鹤. 基于RS码的图像半脆弱水印[J]. 应用科学学报, 2008, 26(1): 34-34 .