基于AC系数统计模型的多种JPEG图像真实性检测技术研究
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摘要
随着多媒体技术以及网络技术的迅猛发展,各种数码相机以及功能强大,简单易操作的图像处理软件的广泛应用,使得数字图像的修改越来越简单。在给人们日常生活带来方便的同时,也带来许多负面影响,如经过篡改的新闻图片或取证图像会给社会带来严重的不良影响以及妨碍司法公正。如何对数码图像的真伪进行有效地辨别,成为当今的研究热点。
JPEG压缩格式以其特有的优点,成为当前图像的主流压缩标准,由于其在压缩比较高的情况下仍能保持较好的图像质量,因而被广泛应用于各领域,所以对JPEG图像真实性的研究具有重要的意义。本文在AC系数统计模型的基础上有针对性的提出并改进了三种基于JPEG二次压缩的数字图像真实性检测算法。
在基于SVM的基础上设计并实现了AC系数拉普拉斯模型的JPEG图像真实性过滤算法,通过拟合图像一次JPEG压缩的概率曲线与图像实际的概率分布进行比较,提取特征向量进行SVM分类判别。
使用非传统统计模型—均衡α稳态模型对AC系数进行描述,通过引入图像复杂度定义减少算法中特征指数值α的计算量,设计提取新的特征向量用于SVM分类判别。
针对质量因子相近的二次JPEG压缩图像提出差分抖动检测模式,通过对AC系数直方图相邻系数做差分并进行抖动判定,来检测图像的真实性。
实验证明,以上算法皆能有效地对非原始JPEG图像进行判别。
With the rapid development of multi-medium technology and net technology, all kinds of digital cameras and powerful function、easy operation image process software are used widely. To tamper digital images is getting easier. While it brings convenience to our life, it also makes a lot of bad impacts. For example, tampered news pictures or modificated evidential images will result in serious bad affection and disturb the justness of judiciary. It's becoming very important that how to distinguish the reality of JPEG images effectively.
JPEG compress standard became the main image compress standard because of its special character. It can preserve better quality of images after a high rate of compress. So it is widely used in every fields. And it has an important signification to investigate the tampered JPEG images. This paper puts forward and improves three kinds of detection of double compressed JPEG images basis on the AC coefficients statistical model.
Designing a filter algorithm for reality of JPEG image based on laplacian distribution. Obtain the eigenvectors by comparing the inosculation degree the simulative probability function of the one time compressed image's AC coefficient and the probability function of AC coefficients of the image.
Depicting AC coefficients with new statistical model—balanced a steadily model. Import the definition of image complexity to cut down the calculation of the value ofα. Design a new character vector for SVM to distinguish.
Aiming at double compressed JPEG images which quality factors are very close, this paper designed difference twitter mode. To detect the reality of images by minus AC coefficients which are close to and determine whether they are twittered.
Experiments show that all the algorithms are effective for detecting double compressed JPEG images.
JPEG压缩格式以其特有的优点,成为当前图像的主流压缩标准,由于其在压缩比较高的情况下仍能保持较好的图像质量,因而被广泛应用于各领域,所以对JPEG图像真实性的研究具有重要的意义。本文在AC系数统计模型的基础上有针对性的提出并改进了三种基于JPEG二次压缩的数字图像真实性检测算法。
在基于SVM的基础上设计并实现了AC系数拉普拉斯模型的JPEG图像真实性过滤算法,通过拟合图像一次JPEG压缩的概率曲线与图像实际的概率分布进行比较,提取特征向量进行SVM分类判别。
使用非传统统计模型—均衡α稳态模型对AC系数进行描述,通过引入图像复杂度定义减少算法中特征指数值α的计算量,设计提取新的特征向量用于SVM分类判别。
针对质量因子相近的二次JPEG压缩图像提出差分抖动检测模式,通过对AC系数直方图相邻系数做差分并进行抖动判定,来检测图像的真实性。
实验证明,以上算法皆能有效地对非原始JPEG图像进行判别。
With the rapid development of multi-medium technology and net technology, all kinds of digital cameras and powerful function、easy operation image process software are used widely. To tamper digital images is getting easier. While it brings convenience to our life, it also makes a lot of bad impacts. For example, tampered news pictures or modificated evidential images will result in serious bad affection and disturb the justness of judiciary. It's becoming very important that how to distinguish the reality of JPEG images effectively.
JPEG compress standard became the main image compress standard because of its special character. It can preserve better quality of images after a high rate of compress. So it is widely used in every fields. And it has an important signification to investigate the tampered JPEG images. This paper puts forward and improves three kinds of detection of double compressed JPEG images basis on the AC coefficients statistical model.
Designing a filter algorithm for reality of JPEG image based on laplacian distribution. Obtain the eigenvectors by comparing the inosculation degree the simulative probability function of the one time compressed image's AC coefficient and the probability function of AC coefficients of the image.
Depicting AC coefficients with new statistical model—balanced a steadily model. Import the definition of image complexity to cut down the calculation of the value ofα. Design a new character vector for SVM to distinguish.
Aiming at double compressed JPEG images which quality factors are very close, this paper designed difference twitter mode. To detect the reality of images by minus AC coefficients which are close to and determine whether they are twittered.
Experiments show that all the algorithms are effective for detecting double compressed JPEG images.
引文
[1]Willam B Pennebaker, Joan L Mitchell著.黎洪松,成实译JPEG静止图像数据压缩标准[S北京：学苑出版社1996.
[2]H. Farid and S. Lyu. Higher-order wavelet statistics and their application to digital forensics[C]:in IEEE Workshop on Statistical Analysis in Computer Vision. Madison. Widconsin.2003.
[3]H. Farid. Creating and Detecting Doctored and Virtual Images:Implications to the Child Pornography Prevention[R].Act.Technical Report. Department of Computer Science. Dartmouth College. New Hampshire. USA.2004.
[4]S. Lyu and H. Farid. How realistic is photoreafistic?[C] IEEE Transactions on Signal Processing. vol.53, no.2.pp.845-850. February.2005.
[5]H. Farid. A picture tells a thousand lies[J]. New Scientist.2003.179(2411).
[6]A.C. Popescu. Statistical tools for digital image forensics [D]. Ph.D. dissertation Dartmouth College. Hanover. NH. December 2004. Dartmouth Computer Science Tech. Rep. TR2005-531.
[7]A. Popescu and H. Farid. Exposing digital forgeries by detecting traces of re-sampling[C]. in IEEE Transactions on Signal Processing.2004. vol. 53:758-767.
[8]A. Popescu and H. Farid. Exposing digital forgeries by detecting duplicated image regions. Tech. Rep. TR2004-515. Computer Science. [Online]. Available: http://www.cs.Dartmouth.edu/-farid/publications/tr04.pd#
[9]Mitchell D Swanson. Mei Kobayashi. Ahmed H Tewfik. Multimedia data-embedding and watermarking technologies[C]. Proceedings of the IEEE. 1998.86(6):1064-1087.
[10]Johnson M.K. and Farid H. Exposing Digital Forgeries by Detecting Inconsisten -cies in Lighting[J].Proc ACM Multimedia and Security Workshop. New York.2005. pp.1-9.
[11]Fridrich J.. Soukal D..and Lukas J. Detection of Copy-Move Forgery in Digital Images[J]. Proc.Digital Forensic Research Workshop. Cleveland. OH.2003.8.
[12]H. Farid. Detecting digital forgeries using bispectral analysis[C]. Technical Report AIM—1657.Massachusetts Institue of Technology. August 1999.
[13]T.-T. Ng and S.-F. Chang. Blind detection of digital photomontage University. June using higher orderstatistics[R].Technical Report ADVENT 201-2004-1, Columbia 2004.
[14]J. Fridrich. D. Soukal. and J. Lukas. Detection of copy-move forgery in digital images[C]. In Proceedings of Digital Forensic Research Workshop. August 2003.
[15]Ashwin Swaminathan. Min Wu. and K. J. Ray Liu. Non-Intrusive Component Forensics of Visual Sensors Using Output Images}C}. IEEE Transactions on Information Forensics and Security. to appear March 2007
[16]Ashwin Swaminathan. Min Wu. and K. J. Ray Liu. Image Tampering Identification using Blind Deconvolution[C]. Proceedings of the IEEE International Conference on Image Processing (ICIP). pp.2311-2314. Atlanta. GA. October 2006.
[17]Xiang-wei Kong. Wen-Feng Liu. and Xin-Gang You. Secret Message Location analysis Based on Local Coherences of Hue[J]. LNCS 37fi＄. pp.301-311,2005.
[18]V. Licks and R. Jordan. Geometric attacks on image watermarking system[J]. IEEE Multimedia.vol.12. no.3. pp.68-78. Jul.-Sep.2005.
[19]J. Liu. D. Huang. and J. Huang. Survey on watermarking against geometric attack. J. Electron. Inf.Technol[J]二 vol.26. no.9. pp.1495-1503.2004.
[20]Tian-Tsong Ng and Shih-Fu Chang. A model for image splicing[C]. in Proc. of ICIP. Singapore.Oct 24-27 2004. vol.2. pp.1169-1172.
[21]Alin C. Popescu and Hany Farid. Exposing digital forgeries by detecting traces of re-sampling[C].IEEE Transactions on Signal Processing. vol.53. no.2. pp. 758-767. February 2005.
[22]M. K. Johnson and H. Farid. Exposing digital forgeries by detecting inconsistencies in lighting[C].in ACM Multimedia and Security Workshop. New York. NY 2005.
[23]Tirkel A Z. et al. Electronic watermark[A]. Digital image computing Technology and Applications[C].1993.Macquaric University.1:666-673.
[24]Van Schyndel R.. Tirkel. A.. and Osborne. C. A digital watermark[A]. In Proceedings of ICIP (Austin.Tex.. Nov) IEEE Press[C].1994. pp.86-90.
[25]Ingemar J. Cox. Joe Killian F. Thomson. and Talal Shamoon. Secure Spread Spectrum Watermarking for Multimedia[J]. IEEE Trans. On Image Processing. 6(12).1997. pp.1673-1687.
[26]Pitas I. A method for signature casting on digital images[A]. IEEE International Conference on Image Processing[C].1996.3:215-218.
[27]P. W Wong. A watermark for image integrity and ownership verification[C]. In Proceedings of IS&T PIC Conference. Portland. Oregon.1998.5. pp.374-379.
[28]J. Fridrich. Security of fragile authentication watermarks with localization[C]. In Proceedings of SPIE. Electronic Imaging 2002. Security and Watermarking of Multimedia Contents. volume 4675.2002.1.pp.691-700.
[29]M. U. Celik. G Sharma. E. Saber. and A. M. Tekalp. Hierarchical watermarking for secure image authentication with localization[J].IEEE Transactions on Image Processing.11 (6).2002.6.pp.585-595.
[30]M. Yeung and F. Mintzer. An invisible watermarking technique for image verification[C]. In Proceedings of the International Conference on Image Processing. volume 1.1997. pp.680-683.
[31]Johnson M.K. and Farid H. Exposing Digital Forgeries by Detecting Inconsistencies in Lighting[J].Proc. ACM Multimedia and Security Workshop. New York.2005. pp.1-9.
[32]Fridrich J.. Soukal D 二 and Lukas J. Detection of Copy-Move Forgery in Digital Images[J]. Proc. Digital Forensic Research Workshop. Cleveland. OH.2003.8.
[33]The Joint Photographic Experts Group. T0081E[M].1992. pp.1-118.
[34]Chih-Chung Chang and Chih-Jen Lin. LIBSVM:a library for support vector machines[M].2001.
[35]C.W Hsu and C.J. Lin. A comparison of methods for multi-class support vector machines[J].IEEE Transactions on Neural Networks.13(2002). pp.415-425.
[36]D.-D. Fu. Y-Q. Shi. andW Su. A generalized benford's law for jpeg coefficients and its applications in image forensics[C]. in Proc. SPIE Security. Steganography. and Watermarking of Multimedia Contents.2007. vol.6505. p.58.
[37]J. He. Z. Lin. L.Wang. and X. Tang. Detecting doctored jpeg images via dct coefficient analysis[C]. in ECCV'06.2006. vol. Ⅲ:423-435.
[38]W-Q. Luo. Z.-H. Qu. J.-Wu. Huang. and G-P. Qiu. A novel method for detecting cropped and recompressed image block[C] in Proc. IEEE ICASSP'07. Hawaii. 2007.
[39]A. Hyv"arinen and E. Oja. Independent component analysis:algorithms and applications [J]. IEEE Trans. Neural Networks. vol.13. no.4-5. pp.411-430. Jun.2000.
[40]Xiangyang Wang. Jun Wu. and Panpan Niu. A New Digital Image Watermarking Algorithm Resilient to Desynchronization Attacks[c]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY VOL.2. NO.4. DECEMBER 2007
[41]M. Barni. I. J. Cox. and T. Kalker. Digital watermarking. in Proc.4th Int. Workshop on Digital Watermarking[J]. Siena. Italy. Sep.15-17.2005. vol.3710. Lecture Notes Comput. Sci.. pp.171-185.
[42]C.-L. Li and Z.Lu. Desynchronization attack on digital watermarks and their countermeasures[J].Image Graph., vol.10. no.4. pp.403-409.2005.
[43]刘文锋,基于图像连续性的数字图像取证技术研究[D].大连：大连理工大学,2005.
[44]孙璐璐,针对数码照片的被动数字图像取证技术[D]：硕士学位论文,大连：大连理工大学,2006.
[45]Zhou Linna.Wang Dongming.Guo Yunbiao and Zhang Jingfei. Blue Detection of Digital Forgery Using Mathematical Morphology[C]. KES AMSTA2007.Lecture notes in computer science.2007,5.
[46]王波,孙璐璐,孔样维,尤新刚.图像伪造中模糊操作的异常色调率取证技术[[J].电子学报200612A.2006年12月增刊.
[47]Alin C. Popescu and Hany Farid. Statistical tools for digital forensics[C] in Proceedings of the 6th Information Hiding Workshop. May 2004.SPIE.The International Society for Optical. Engineering.1999.2(3668):528542.
[48]J. Lukas and J. Fridrich. Estimation of primary quantization matrix in double compressed jpeg images[C] in Proceedings of Digital Forensic Research Workshop. August 2003.
[49]J.F. He. Z.C. Lin. L.F. Wang. and X. Tang. Detecting doctored jpeg images via dct coefficient analysis[C].in ECCV06.2006. pp. Ⅲ:423435.
[50]The International Telegraph and Telephone Consultative Committee (CCITT). Information technology digital compression and coding of continuous-tone still images-requirements and guidelines[C] 1992.
[51]R.L. Zhigang Fan; de Queiroz. Identification of bitmap compression history: Jpeg detection and quantizer estimation[C] Image Processing. IEEE Transactions on. vol.12. no.2. pp.230-235. Feb 2003.
[52]Prasad S. and K.R.Ramakrishnan. ON RESAMPLING DETECTION AND ITS APPLICATION TO DETECT IMAGE TAMPERING[C]. IEEE Trans. ICME 2006.
[53]Weiqi Luo.Zhenhua Qu.Jiwu Huang. Guoping Qiu. A NOVEL METHOD FOR DETECTING CROPPED AND RECOMPRESSED IMAGE BLOCK[C] IEEE Trans. ICASSP 2007.
[54]H.Paek.R.-C.Kim and S.-U. Lee. On the POCS-based post processing technique to reduce the blocking artifacts intransform coded images[J] IEEE Trans Circuits and Systems for Video Tech. vol.8.no.3.pp.358-367.June 1998.
[55]Z.Wang.and D.Zhang. A novel approach for the reduction of blocking effects in low-bit-rate image compression[J] IEEE Trans. Communications. vol.46.no.6.pp.732-734. June 1998.
[56]Y.Yang and N.P.Galatsanos.. Removal of compression artifacts using projections onto convex sets and line process modeling[J]. IEEE Trans.Image Processing. vol.6.no.10.
[57]Zhou Wang. Alan C. Bovik and Brian L. Evans. BLIND MEASUREMENT OF BLOCKING ARTIFACTS IN IMAGES[J]. IEEE Trans.Image Processing.pp.1-4.
[58]S.A.Karunasekera and N.GKingsbury. A distortion measure for blocking artifacts in images based on human visual sensitivity[J] IEEE Trans. Image Processing. vol.4.no.6.pp.713-724.June 1995.
[59]M.Miyahara.Quafity assessments for visual service[J].IEEE Communications Magazine. pp.51-60.Oct.1988.
[60]Weiqi Luo.Zhenhua Qu.Jiwu Huang. Guoping Qiu. A NOVEL METHOD FOR DETECTING CROPPED AND RECOMPRESSED IMAGE BLOCK [C]. IEEE Trans.ICASSP 2007.
[61]H.R.Wu and M.Yuen. A generalized block-edgeimpairment metric for video coding[J] IEEE Signal Proc.Letters. vol.4.no.l1.pp.317-320.Nov.1997.
[62]D.Wei and A. C.Bovik. A new metric for blocking artifacts in block transform-coded images and video [J] Technical Report.The University of Texas.Oct.1998.
[63]秦川,王朔中,张新鹏.针对Poisson方程图像编辑的篡改检测[[J].计算机研究与发展.Vol46.no.46.pp.234-238.Mar.2009.
[64]张静,吉建华,苏育挺一种基于小波系数正则性的JPEG2000图像篡改检测算法[[J].计算机研究与发展.vol46.no.47.pp.239-243.Mar.2009.
[65]Xiang-wei Kong. Wen-Feng Local Coherences of Hue[J].Liu. and Xin-Gang You. Secret Message Location analysis Based on LNCS 37fi＄. pp.301-311,2005.
[66]V. Licks and R. Jordan. Geometric attacks on image watermarking system[J]. IEEE Multimedia. vol.12. no.3. pp.68-78. Jul.-Sep.2005.
[67]J. Liu. D. Huang. and J. Huang. Survey on watermarking against geometric attack. J. Electron. Inf. Technol[J]vol.26. no.9. pp.1495-1503.2004.
[68]Tian-Tsong Ng and Shih-Fu Chang. A model for image splicing[C]. in Proc. of ICIP. Singapore. Oct 24-27 2004. vol.2. pp.1169-1172.
[69]Alin C. Popescu and Hany Farid. Exposing digital forgeries by detecting traces of re-sampling[C].IEEE Transactions on Signal Processing. vol.53. no.2. bb. 758-767. February 2005.
[70]Giannlula A., Boulgouris N. V., Hatzinakos D. and Plataniotis K. N., Watermark Detectionfor Noisy Interpolated Images[J], IEEE Trans. on Circuits and systems-II:Express Briefs,2006,53(5):359-403
[71]吴首阳,JPEG图像盲取证技术研究。[D]北京：中国科技大学,2009
[72]Reininger R. C. and Gibson J.D.,Distributions of the two-dimensional DCT coefficients for images[J],IEEE Transcation on Communcation,1983,COMM-31: 835-839
[73]Hernandez J. R., Amado M., and Perez-Gonzalez F., DCT-domain water-marking techniques for still images:Detector performance analysis and a new structure [J], IEEE Transcation on Image Process.,2000,9:55-68
[74]Wen-Nung Lie and Guo-Shiang Lin,A Feature-based classification technique for blind image steganalysis[J],IEEE Transactions on multimedia,2005,7(6):1007-1020
[75]Alexia Briassouli,Panagiotis Tsakalides and Athanasios Stouraitis, Hidden Messages in Heavy-Tails:DCT-Domain Watermark Detection Using Alpha-Stable Models, IEEE Transactions on Multimedia,2005,7(4):700-715
[76]Tsihrintzis G. A. and Nikias C. L., Performance of optimum and suboptimum receivers in the presence of impulsive noise modeled as an alphastable process[J], IEEE Transcation on Communcation,1995,43(3):904-914
[77]Sayrol E., Vidal J.,Cabanillas S., and Santamaria S., Optimum water mark detection in color images[A], in Proc.1999 Int. Conf. Image Processing(ICIP 99)[C],Kobe,Japan:IEEE,1999,2:231-235
[78]Birney K.A. and Fischer T.R., On the modeling of DCT and subband image data for compression[J], IEEE Trans. Image Process.,1995,4(2):186-193
[79]Adler R., Feldman R., and Taqqu M.S., A Guide to Heavy Tails:Statistical Techniques and Applications[M]. Boston, MA:Birkhauser,1998
[80]Barni M.,Bartolini F., Rosa A.De, and Piva A., Capacity of full frame DCT image watermarks [J], IEEE Trans.Image Process.,2000,9(8):1450-1455
[81]Fabrizio G.A.,Turley M.D., An advanced STAP implementation for surveillance radar systems[J], IEEE Statistical Signal Processing.2001,8 (2):137-137
[82]Willinger W., Taqqu M.S., Leland W.E., and Wilson D.V., Self-similarity in high-speed packet traffic:Analysis and modeling of ethernet traffic measurements[J], Statistical Science.,1995,10(1):67-85
[83]Achim A., Bezerianos A., and Tsakalides P., Novel Bayesian multiscale method for speckle removal in medical ultrasound images[J], IEEE Trans.Med. Imag.,2001,20(8):772-783
[2]H. Farid and S. Lyu. Higher-order wavelet statistics and their application to digital forensics[C]:in IEEE Workshop on Statistical Analysis in Computer Vision. Madison. Widconsin.2003.
[3]H. Farid. Creating and Detecting Doctored and Virtual Images:Implications to the Child Pornography Prevention[R].Act.Technical Report. Department of Computer Science. Dartmouth College. New Hampshire. USA.2004.
[4]S. Lyu and H. Farid. How realistic is photoreafistic?[C] IEEE Transactions on Signal Processing. vol.53, no.2.pp.845-850. February.2005.
[5]H. Farid. A picture tells a thousand lies[J]. New Scientist.2003.179(2411).
[6]A.C. Popescu. Statistical tools for digital image forensics [D]. Ph.D. dissertation Dartmouth College. Hanover. NH. December 2004. Dartmouth Computer Science Tech. Rep. TR2005-531.
[7]A. Popescu and H. Farid. Exposing digital forgeries by detecting traces of re-sampling[C]. in IEEE Transactions on Signal Processing.2004. vol. 53:758-767.
[8]A. Popescu and H. Farid. Exposing digital forgeries by detecting duplicated image regions. Tech. Rep. TR2004-515. Computer Science. [Online]. Available: http://www.cs.Dartmouth.edu/-farid/publications/tr04.pd#
[9]Mitchell D Swanson. Mei Kobayashi. Ahmed H Tewfik. Multimedia data-embedding and watermarking technologies[C]. Proceedings of the IEEE. 1998.86(6):1064-1087.
[10]Johnson M.K. and Farid H. Exposing Digital Forgeries by Detecting Inconsisten -cies in Lighting[J].Proc ACM Multimedia and Security Workshop. New York.2005. pp.1-9.
[11]Fridrich J.. Soukal D..and Lukas J. Detection of Copy-Move Forgery in Digital Images[J]. Proc.Digital Forensic Research Workshop. Cleveland. OH.2003.8.
[12]H. Farid. Detecting digital forgeries using bispectral analysis[C]. Technical Report AIM—1657.Massachusetts Institue of Technology. August 1999.
[13]T.-T. Ng and S.-F. Chang. Blind detection of digital photomontage University. June using higher orderstatistics[R].Technical Report ADVENT 201-2004-1, Columbia 2004.
[14]J. Fridrich. D. Soukal. and J. Lukas. Detection of copy-move forgery in digital images[C]. In Proceedings of Digital Forensic Research Workshop. August 2003.
[15]Ashwin Swaminathan. Min Wu. and K. J. Ray Liu. Non-Intrusive Component Forensics of Visual Sensors Using Output Images}C}. IEEE Transactions on Information Forensics and Security. to appear March 2007
[16]Ashwin Swaminathan. Min Wu. and K. J. Ray Liu. Image Tampering Identification using Blind Deconvolution[C]. Proceedings of the IEEE International Conference on Image Processing (ICIP). pp.2311-2314. Atlanta. GA. October 2006.
[17]Xiang-wei Kong. Wen-Feng Liu. and Xin-Gang You. Secret Message Location analysis Based on Local Coherences of Hue[J]. LNCS 37fi＄. pp.301-311,2005.
[18]V. Licks and R. Jordan. Geometric attacks on image watermarking system[J]. IEEE Multimedia.vol.12. no.3. pp.68-78. Jul.-Sep.2005.
[19]J. Liu. D. Huang. and J. Huang. Survey on watermarking against geometric attack. J. Electron. Inf.Technol[J]二 vol.26. no.9. pp.1495-1503.2004.
[20]Tian-Tsong Ng and Shih-Fu Chang. A model for image splicing[C]. in Proc. of ICIP. Singapore.Oct 24-27 2004. vol.2. pp.1169-1172.
[21]Alin C. Popescu and Hany Farid. Exposing digital forgeries by detecting traces of re-sampling[C].IEEE Transactions on Signal Processing. vol.53. no.2. pp. 758-767. February 2005.
[22]M. K. Johnson and H. Farid. Exposing digital forgeries by detecting inconsistencies in lighting[C].in ACM Multimedia and Security Workshop. New York. NY 2005.
[23]Tirkel A Z. et al. Electronic watermark[A]. Digital image computing Technology and Applications[C].1993.Macquaric University.1:666-673.
[24]Van Schyndel R.. Tirkel. A.. and Osborne. C. A digital watermark[A]. In Proceedings of ICIP (Austin.Tex.. Nov) IEEE Press[C].1994. pp.86-90.
[25]Ingemar J. Cox. Joe Killian F. Thomson. and Talal Shamoon. Secure Spread Spectrum Watermarking for Multimedia[J]. IEEE Trans. On Image Processing. 6(12).1997. pp.1673-1687.
[26]Pitas I. A method for signature casting on digital images[A]. IEEE International Conference on Image Processing[C].1996.3:215-218.
[27]P. W Wong. A watermark for image integrity and ownership verification[C]. In Proceedings of IS&T PIC Conference. Portland. Oregon.1998.5. pp.374-379.
[28]J. Fridrich. Security of fragile authentication watermarks with localization[C]. In Proceedings of SPIE. Electronic Imaging 2002. Security and Watermarking of Multimedia Contents. volume 4675.2002.1.pp.691-700.
[29]M. U. Celik. G Sharma. E. Saber. and A. M. Tekalp. Hierarchical watermarking for secure image authentication with localization[J].IEEE Transactions on Image Processing.11 (6).2002.6.pp.585-595.
[30]M. Yeung and F. Mintzer. An invisible watermarking technique for image verification[C]. In Proceedings of the International Conference on Image Processing. volume 1.1997. pp.680-683.
[31]Johnson M.K. and Farid H. Exposing Digital Forgeries by Detecting Inconsistencies in Lighting[J].Proc. ACM Multimedia and Security Workshop. New York.2005. pp.1-9.
[32]Fridrich J.. Soukal D 二 and Lukas J. Detection of Copy-Move Forgery in Digital Images[J]. Proc. Digital Forensic Research Workshop. Cleveland. OH.2003.8.
[33]The Joint Photographic Experts Group. T0081E[M].1992. pp.1-118.
[34]Chih-Chung Chang and Chih-Jen Lin. LIBSVM:a library for support vector machines[M].2001.
[35]C.W Hsu and C.J. Lin. A comparison of methods for multi-class support vector machines[J].IEEE Transactions on Neural Networks.13(2002). pp.415-425.
[36]D.-D. Fu. Y-Q. Shi. andW Su. A generalized benford's law for jpeg coefficients and its applications in image forensics[C]. in Proc. SPIE Security. Steganography. and Watermarking of Multimedia Contents.2007. vol.6505. p.58.
[37]J. He. Z. Lin. L.Wang. and X. Tang. Detecting doctored jpeg images via dct coefficient analysis[C]. in ECCV'06.2006. vol. Ⅲ:423-435.
[38]W-Q. Luo. Z.-H. Qu. J.-Wu. Huang. and G-P. Qiu. A novel method for detecting cropped and recompressed image block[C] in Proc. IEEE ICASSP'07. Hawaii. 2007.
[39]A. Hyv"arinen and E. Oja. Independent component analysis:algorithms and applications [J]. IEEE Trans. Neural Networks. vol.13. no.4-5. pp.411-430. Jun.2000.
[40]Xiangyang Wang. Jun Wu. and Panpan Niu. A New Digital Image Watermarking Algorithm Resilient to Desynchronization Attacks[c]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY VOL.2. NO.4. DECEMBER 2007
[41]M. Barni. I. J. Cox. and T. Kalker. Digital watermarking. in Proc.4th Int. Workshop on Digital Watermarking[J]. Siena. Italy. Sep.15-17.2005. vol.3710. Lecture Notes Comput. Sci.. pp.171-185.
[42]C.-L. Li and Z.Lu. Desynchronization attack on digital watermarks and their countermeasures[J].Image Graph., vol.10. no.4. pp.403-409.2005.
[43]刘文锋,基于图像连续性的数字图像取证技术研究[D].大连：大连理工大学,2005.
[44]孙璐璐,针对数码照片的被动数字图像取证技术[D]：硕士学位论文,大连：大连理工大学,2006.
[45]Zhou Linna.Wang Dongming.Guo Yunbiao and Zhang Jingfei. Blue Detection of Digital Forgery Using Mathematical Morphology[C]. KES AMSTA2007.Lecture notes in computer science.2007,5.
[46]王波,孙璐璐,孔样维,尤新刚.图像伪造中模糊操作的异常色调率取证技术[[J].电子学报200612A.2006年12月增刊.
[47]Alin C. Popescu and Hany Farid. Statistical tools for digital forensics[C] in Proceedings of the 6th Information Hiding Workshop. May 2004.SPIE.The International Society for Optical. Engineering.1999.2(3668):528542.
[48]J. Lukas and J. Fridrich. Estimation of primary quantization matrix in double compressed jpeg images[C] in Proceedings of Digital Forensic Research Workshop. August 2003.
[49]J.F. He. Z.C. Lin. L.F. Wang. and X. Tang. Detecting doctored jpeg images via dct coefficient analysis[C].in ECCV06.2006. pp. Ⅲ:423435.
[50]The International Telegraph and Telephone Consultative Committee (CCITT). Information technology digital compression and coding of continuous-tone still images-requirements and guidelines[C] 1992.
[51]R.L. Zhigang Fan; de Queiroz. Identification of bitmap compression history: Jpeg detection and quantizer estimation[C] Image Processing. IEEE Transactions on. vol.12. no.2. pp.230-235. Feb 2003.
[52]Prasad S. and K.R.Ramakrishnan. ON RESAMPLING DETECTION AND ITS APPLICATION TO DETECT IMAGE TAMPERING[C]. IEEE Trans. ICME 2006.
[53]Weiqi Luo.Zhenhua Qu.Jiwu Huang. Guoping Qiu. A NOVEL METHOD FOR DETECTING CROPPED AND RECOMPRESSED IMAGE BLOCK[C] IEEE Trans. ICASSP 2007.
[54]H.Paek.R.-C.Kim and S.-U. Lee. On the POCS-based post processing technique to reduce the blocking artifacts intransform coded images[J] IEEE Trans Circuits and Systems for Video Tech. vol.8.no.3.pp.358-367.June 1998.
[55]Z.Wang.and D.Zhang. A novel approach for the reduction of blocking effects in low-bit-rate image compression[J] IEEE Trans. Communications. vol.46.no.6.pp.732-734. June 1998.
[56]Y.Yang and N.P.Galatsanos.. Removal of compression artifacts using projections onto convex sets and line process modeling[J]. IEEE Trans.Image Processing. vol.6.no.10.
[57]Zhou Wang. Alan C. Bovik and Brian L. Evans. BLIND MEASUREMENT OF BLOCKING ARTIFACTS IN IMAGES[J]. IEEE Trans.Image Processing.pp.1-4.
[58]S.A.Karunasekera and N.GKingsbury. A distortion measure for blocking artifacts in images based on human visual sensitivity[J] IEEE Trans. Image Processing. vol.4.no.6.pp.713-724.June 1995.
[59]M.Miyahara.Quafity assessments for visual service[J].IEEE Communications Magazine. pp.51-60.Oct.1988.
[60]Weiqi Luo.Zhenhua Qu.Jiwu Huang. Guoping Qiu. A NOVEL METHOD FOR DETECTING CROPPED AND RECOMPRESSED IMAGE BLOCK [C]. IEEE Trans.ICASSP 2007.
[61]H.R.Wu and M.Yuen. A generalized block-edgeimpairment metric for video coding[J] IEEE Signal Proc.Letters. vol.4.no.l1.pp.317-320.Nov.1997.
[62]D.Wei and A. C.Bovik. A new metric for blocking artifacts in block transform-coded images and video [J] Technical Report.The University of Texas.Oct.1998.
[63]秦川,王朔中,张新鹏.针对Poisson方程图像编辑的篡改检测[[J].计算机研究与发展.Vol46.no.46.pp.234-238.Mar.2009.
[64]张静,吉建华,苏育挺一种基于小波系数正则性的JPEG2000图像篡改检测算法[[J].计算机研究与发展.vol46.no.47.pp.239-243.Mar.2009.
[65]Xiang-wei Kong. Wen-Feng Local Coherences of Hue[J].Liu. and Xin-Gang You. Secret Message Location analysis Based on LNCS 37fi＄. pp.301-311,2005.
[66]V. Licks and R. Jordan. Geometric attacks on image watermarking system[J]. IEEE Multimedia. vol.12. no.3. pp.68-78. Jul.-Sep.2005.
[67]J. Liu. D. Huang. and J. Huang. Survey on watermarking against geometric attack. J. Electron. Inf. Technol[J]vol.26. no.9. pp.1495-1503.2004.
[68]Tian-Tsong Ng and Shih-Fu Chang. A model for image splicing[C]. in Proc. of ICIP. Singapore. Oct 24-27 2004. vol.2. pp.1169-1172.
[69]Alin C. Popescu and Hany Farid. Exposing digital forgeries by detecting traces of re-sampling[C].IEEE Transactions on Signal Processing. vol.53. no.2. bb. 758-767. February 2005.
[70]Giannlula A., Boulgouris N. V., Hatzinakos D. and Plataniotis K. N., Watermark Detectionfor Noisy Interpolated Images[J], IEEE Trans. on Circuits and systems-II:Express Briefs,2006,53(5):359-403
[71]吴首阳,JPEG图像盲取证技术研究。[D]北京：中国科技大学,2009
[72]Reininger R. C. and Gibson J.D.,Distributions of the two-dimensional DCT coefficients for images[J],IEEE Transcation on Communcation,1983,COMM-31: 835-839
[73]Hernandez J. R., Amado M., and Perez-Gonzalez F., DCT-domain water-marking techniques for still images:Detector performance analysis and a new structure [J], IEEE Transcation on Image Process.,2000,9:55-68
[74]Wen-Nung Lie and Guo-Shiang Lin,A Feature-based classification technique for blind image steganalysis[J],IEEE Transactions on multimedia,2005,7(6):1007-1020
[75]Alexia Briassouli,Panagiotis Tsakalides and Athanasios Stouraitis, Hidden Messages in Heavy-Tails:DCT-Domain Watermark Detection Using Alpha-Stable Models, IEEE Transactions on Multimedia,2005,7(4):700-715
[76]Tsihrintzis G. A. and Nikias C. L., Performance of optimum and suboptimum receivers in the presence of impulsive noise modeled as an alphastable process[J], IEEE Transcation on Communcation,1995,43(3):904-914
[77]Sayrol E., Vidal J.,Cabanillas S., and Santamaria S., Optimum water mark detection in color images[A], in Proc.1999 Int. Conf. Image Processing(ICIP 99)[C],Kobe,Japan:IEEE,1999,2:231-235
[78]Birney K.A. and Fischer T.R., On the modeling of DCT and subband image data for compression[J], IEEE Trans. Image Process.,1995,4(2):186-193
[79]Adler R., Feldman R., and Taqqu M.S., A Guide to Heavy Tails:Statistical Techniques and Applications[M]. Boston, MA:Birkhauser,1998
[80]Barni M.,Bartolini F., Rosa A.De, and Piva A., Capacity of full frame DCT image watermarks [J], IEEE Trans.Image Process.,2000,9(8):1450-1455
[81]Fabrizio G.A.,Turley M.D., An advanced STAP implementation for surveillance radar systems[J], IEEE Statistical Signal Processing.2001,8 (2):137-137
[82]Willinger W., Taqqu M.S., Leland W.E., and Wilson D.V., Self-similarity in high-speed packet traffic:Analysis and modeling of ethernet traffic measurements[J], Statistical Science.,1995,10(1):67-85
[83]Achim A., Bezerianos A., and Tsakalides P., Novel Bayesian multiscale method for speckle removal in medical ultrasound images[J], IEEE Trans.Med. Imag.,2001,20(8):772-783