Document Type : Review Article


1 Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 Electrical Engineering Department, Sharif University of Technology, Tehran, Iran

3 Advanced Communications Research Institute, Sharif University of Technology, Tehran, Iran


This paper investigates digital data hiding schemes. The concept of information hiding will be explained at first, and its traits, requirements, and applications will be described subsequently. In order to design a digital data hiding system, one should first become familiar with the concepts and criteria of information hiding. Having knowledge about the host signal, which may be audio, image, or video and the final receiver, which is Human Auditory System (HAS) or Human Visual System (HVS), is also beneficial. For the speech/audio case, HAS will be briefly reviewed to find out how to make the most of its weaknesses for embedding as much data as possible. The same discussion also holds for the image watermarking. Although several audio and image data hiding schemes have been proposed so far, they can be divided into a few categories. Hence, conventional schemes along with their recently published extensions are introduced. Besides, a general comparison is made among these methods leading researchers/designers to choose the appropriate schemes based on their applications. Regarding the old scenario of the prisoner-warden and the evil intention of the warden to eavesdrop and/or destroy the data that Alice sends to Bob, there are both intentional and unintentional attacks to digital information hiding systems, which have the same effect based on our definition. These attacks can also be considered for testing the performance or benchmarking, of the watermarking algorithm. They are also known as steganalysis methods which will be discussed at the end of the paper.


 [1] C. S. Lu, Multimedia security: steganography and digital watermarking techniques for protection of intellectual property, Idea Group Publishing, 2004.
[2] J. Seitz, Digital watermarking for digital media, Information Science Publishing, 2005.
[3] G. C. Langelaar, I. Setyawan, and R.L. Lagendijk, Watermarking digital image and video data:  A state-of-the-art overview, IEEE Trans. Signal Process. Magazine, vol. 17, no. 5, pp. 20-46, 2000.
[4] S. Katzenbeisser, and F. A. Petitcolas, Information hiding techniques for steganography and digital watermarking, Artech House, Boston, 2000.
[5] I. J. Cox, M. L. Miller, and J. A. Bloom,.  Digital watermarking, first edition, San Francisco: Morgan Kaufmann, 2002.
[6] M. Barni and F. Bartolini, Watermarking systems engineering: Enabling Digital Assets Security and Other Applications, CRC, 2008.
[7] A. B. Watson, Handbook  of human  perception and  performance, in Temporal Sensitivity, K. Boff, L. Kaufmann, and  J. Thomas, Eds. New York: Wiley, 1986.
[8] A. B. Watson, M. Taylor, and R. Borthwick, Image quality and entropy masking, Proc. SPIE, Human  Vision, Visual Processing,  and Digital Display VIII, 1997, vol. 3016, pp. 2-12.
[9] A. B. Watson, J. Y. Yang, J. A. Solomon, and J. Villasenor, Visibility of wavelet quantization noise, IEEE Trans.  on Image Process., vol. 6, no. 8, pp. 1164-1175, Oct. 1997.
[10]  J. R. Deller, J. H. L. Hansen, and J. G. Proakis, Discrete- Time Processing of Speech Signals, 2nd edition,  IEEE  Press, 2000.
[11] SQAM - Sound Quality Assessment Material,,2006.
[12] K.  Brandenburg, T.  Sporer, NMR and masking flag: Evaluation of quality using perceptual criteria, Proceedings of the International Audio Engineering Society Conference on Audio Test and Measurement, pp.169-179, Sept, 1992.
[13] Z. Wang, and A. C. Bovik, Image quality assessment:  from error visibility to structural similarity, IEEE Trans. on Image Process., vol. 13, no. 4, pp. 600-612, 2004.
[14] Z. Wang,  and  A. C. Bovik,  A universal image quality index,  IEEE  Signal Processing Letters, vol. 9,no.3,pp.81-84,2002.
[15] P. Kabal,   An   Examination and   Interpretation   of ITU-R   BS.1387:   Perceptual evaluation of audio quality, Technical Report of Telecom. Signal Process. Lab., version 2, (, McGill University, 2003.
[16] Q. Cheng, and T. S. Huang, Robust optimum detection of transform domain multiplicative watermarks, IEEE Trans.  Signal Processing, vol. 51, no. 4, pp. 906-924, 2003.
[17] S. Wu, J. Huang, D.  Huang, Y.  Q.  Shi, Efficiently self-synchronized audio watermarking for assured audio data, IEEE Transmissions on Broadcast., vol.51, no. 1, pp. 69-76, Mar. 2005.
[18] E. T. Lin and E. J. Delp, A review of fragile image watermarks, Proc. Multimedia and Security Workshop on Multimedia Contents, Orlando, pp. 25-29, Oct. 1999.
[19]  L. M. Marvel, G. W. Hartwig,  and C. Boncelet, Compression compatible  fragile and semi fragile tamper  detection, Proc. SPIE, vol. 39, no 71, 131-139 ,2002.
[20] O.  Ekici, B.  Sankur, B.  Coskun, U. Naci, M. Akcay, Comparative assessment of semi fragile watermarking methods, Journal of Electronic Imaging, vol. 13, no. 1, pp. 209-216, Jan.  2004.
[21] C. Lu and H. M. Liao, Multipurpose watermarking for image authentication and protection, IEEE Trans.  Image Process., vol. 10, no. 10, pp.1579-1592, Oct., 2001.
[22] J.  Fridrich, Security of fragile authentication watermarks with localization, Proc. SPIE, vol. 46, no. 75, 691-700, 2002.
[23]  G. W. Yu, C. S. Lu, and  H. Y. M. Liao, Mean quantization-based fragile watermarking for image authentication, Opt. Eng. vol. 40, no. 7, 1396-1408, 2004.
[24] H. Yuan, and X. P.  Zhang, Multiscale fragile watermarking based on the Gaussian mixture model, IEEE Trans. on Image Process., vol. 15, no. 10, pp. 3189-3200, Oct. 2006.
[25]  E. T. Lin, C. I. Podilchuk, and  E. J. Delp, Detection of image  alterations using  semi-fragile watermarks, Proc. SPIE, vol. 39, no. 71, pp. 152-163, 2000.
[26] Z. M. Lu, C. H. Liu, D. G. Xu, and S. H. Sun, Semi-fragile image watermarking method based on index constrained vector quantization, Electronic Letter, vol. 39, no. 7, pp. 35-36. Jan. 2003.
[27]  D. Zou, Y. Q. Shi, Z. Ni, and  W. Su, A semi-fragile lossless digital watermarking scheme, IEEE  Trans. on Circuit and Systems for Video Tech., vol. 16, no. 10, pp. 1294-1300, Oct. 2006.
[28] J. Chou, K. Ramchandran, and A. Ortega, High capacity audio data hiding for noisy channels, Proc. of the International Conference  on Information Technology: Coding and Computing,  pp.108-111, 2001.
[29] K. Hofbauer and G. Kubin, High-rate data embedding in unvoiced speech, Proc. International Conference on Spoken Language Processing, pp.176-180, 2006.
[30] D. C. Wu and W.  H. Tsai, A steganographic method for images by pixel-value differencing, Pattern Recognition Letters, vol. 24, no. 910, pp.1613 - 1626, 2003.
[31]  X. Zhang  and  S. Wang,  Vulnerability of pixel- value differencing  steganography to histogram analysis and modification for enhanced security, Pattern  Recognition Letters, vol. 25, no. 3, pp.331 - 339, 2004.
[32] C. H. Yang, C. Y. Weng, S. J.  Wang, and H.M. Sun, Adaptive data hiding in edge areas of images with spatial lsb domain systems, IEEE Trans. on Info. Forensics and Security, vol. 3, no. 3, pp. 488 -497, Sept. 2008.
[33]  H. C.Wu, N. I.Wu, C. S. Tsai, and M. S. Hwang, Image  steganographic scheme  based  on pixel-value differencing and lsb replacement methods, Vision, Image and Signal Processing, IEE Proc., vol. 152, no. 5, pp. 611- 615, Oct. 2005.
[34] H. Hering and M. Hagmuller, Safety and security increase for air traffic management through unnoticeable watermark aircraft identification tag transmitted with the VHF voice communication, Proc. of International Conference on Digital Avionic Systems, pp. 202 - 206, 2003.
[35]  J. Mielikainen,  LSB Matching Revisited,  IEEE Signal Processing  Letters, vol. 13, no. 5., May, 2006.
[36] S.  Sarreshtedari, M.  Ghotbi, and S. Ghaemmaghami, One-third probability embedding: Less detectable LSB steganography, Proc. of International Conference on Multimedia and Expo (ICME), pp. 1002-1005, 2009.
[37] X. Li, B. Yang, D. Cheng, and T. Zeng, A generalization of lsb matching, Signal Processing Letters, IEEE, vol. 16, no. 2, Feb. 2009.
[38]  N. Khademi-kalantari, M. A. Akhaee, and S. M. Ahadi,  and  S. M. R. Amindavar, Robust multiplicative patchwork method for audio  watermarking, IEEE  Trans. on Audio,  Speech,  and Language  Processing, vol. 17, no. 6, pp. 1133-1141, 2009.
[39] A. Westfeld, F5-A Steganographic algorithm, in Lecture Notes in Computer Science.  Springer, 2001, vol. 2137, pp. 289-302.
[40] J. Fridrich, T. Pevny, and J. Kodovsky, Statistically undetectable JPEG steganography: dead ends challenges, and opportunities, Proc. of 9th workshop on Multimedia & security, New York, NY, USA: ACM, 2007, pp. 3-14.
[41] J.  Fridrich and M. Goljan, Images with self-correcting capabilities, Proc. of International Conference on Image Processing, vol. 3, pp. 792-796, 1999.
[42] H. J. He, J. S. Zhang, and F. Chen, Adjacent-block based statistical detection method for self-embedding watermarking techniques, Signal Processing, vol. 89, no. 8, pp. 1557 - 1566, 2009.
[43] S. H. Liu, H. X. Yao, W.  Gao, and Y.-L. Liu, An image fragile watermark scheme based on chaotic image pattern and pixel-pairs, Applied Mathematics and Computation, vol. 185, no. 2, pp. 869-882, 2007.
[44] V. Mall, K. Bhatt, S. Mitra, and A. Roy, Exposing structural tampering in digital images, Proc.  International Conference Signal Processing, Computing and Control (ISPCC), pp. 1-6.2012.
[45]  R. Chamlawi,  A. Khan,  and I. Usman,  Authentication and  recovery  of images using multiple watermarks, Computers  and Electrical Engineering, vol. 36, no. 3, pp. 578 - 584, 2010.
[46] C. W. Yang and J. J. Shen, Recover the tampered image based on vq indexing, Signal Processing, vol. 90, no. 1, pp. 331 - 343, 2010.
[47]  A. Cheddad, J. Condell,  K. Curran, and  P. M. Kevitt, A secure and improved  self-embedding algorithm to combat digital  document forgery, Signal Processing, vol. 89, no. 12, pp. 2324 - 2332,2009.
[48]  X. Zhang and S. Wang, Statistical fragile watermarking capable of locating individual tampered pixels, Signal Processing Letters,  IEEE,  vol. 14, no. 10, pp. 727-730, 2007.
[49] X.  Zhang and S. Wang,   Fragile   watermarking with error-free restoration capability, IEEE Transactions on Multimedia, vol. 10, no. 8, pp.1490-1499, 2008.
[50]  X. Zhang  and  S. Wang,  Fragile  watermarking scheme using a hierarchical mechanism, Signal Processing,  vol. 89, no. 4, pp. 675 - 679, 2009.
[51] X. Zhang, S. Wang, and G. Feng, Fragile watermarking scheme with extensive content restoration  capability, in  Digital  Watermarking,  ser. Lecture  Notes  in Computer Science.  Springer Berlin Heidelberg, vol. 5703, pp. 268-278. 2009.
[52]  X. Zhang, S. Wang,  Z. Qian, and G. Feng, Self- embedding  watermark with flexible restoration quality,  Multimedia  Tools and Applications,  vol. 54, no. 2, pp. 385-395, 2011.
[53]  Z. Qian,  G. Feng,  X. Zhang,  and S. Wang,  Image self-embedding with high-quality restoration capability,  Digital Signal Processing, vol. 21, no.2, pp. 278 - 286, 2011.
[54] P.  Korus and A. Dziech, A novel approach to adaptive image authentication, Proc. International Conference on Image Processing (ICIP), pp. 2765-2768. 2011.
[55]  X. Zhang,  Z. Qian,  Y. Ren,  and  G. Feng,  Watermarking with  flexible  self-recovery quality based on compressive sensing and composite re- construction, IEEE Transactions on Information Forensics  and  Security, vol. 6, no. 4, pp. 1223-1232, 2011.
[56]  P. Korus and A. Dziech, Efficient method for con- tent reconstruction with  self-embedding, IEEE Transactions on Image Processing, vol. 22, no. 3, pp. 1134-1147, 2013.
[57] D. J. C. MacKay, Fountain codes, Communications, IEE Proceedings, vol. 152, no. 6, pp. 1062-1068, 2005.
[58] S. Sarreshtedari, M. Akhaee, On source channel coding for image tampering protection and self- recovery, submitted to IEEE Transactions on Image Processing, 2013.
[59] A.  Said and W.  Pearlman, A new,  fast,  and efficient image codec based on set partitioning in hierarchical trees, IEEE Transactions on Circuits and Systems for Video Technology, vol. 6, no. 3, pp. 243-250, 1996.
[60] S. B. Wicker, Reed-Solomon Codes and Their Applications. Piscataway, NJ, USA: IEEE Press, 1994.
[61] J.  Fridrich, Steganography in Digital Media: Principles, Algorithms, and Applications, 1st Edition, Cambridge University Press, NY, 2010.
[62]  M. Parvaix, L. Girin,  Informed  Source Separation of Linear Instantaneous Under-Determined Audio  Mixtures by  Source  Index  Embedding, IEEE  Transactions on Audio, Speech, and Language  Processing, vol.19,  no.6,  pp.1721,1733, Aug. 2011.
[63]  P. H. W. Wong, O. C. Au, A capacity estimation technique for JPEG-to-JPEG image watermarking, IEEE Transactions on Circuits and Systems for Video Technology, vol.13, no.8, pp.746,752, Aug. 2003.
[64] E. Zwicker and H. Fastl, Psychoacoustics: Facts and models, 2nd edition, Springer-Verlag, 1999.
[65] V. Schyndel, R. G., A. Z. Tirkel, and C. F. Osborne, A digital watermark, International Conference on Image Processing (ICIP), Austin, pp. 86-90. 1994.
[66] R.  Crandall, Some Notes on Steganography, posted on Steganography Mailing List. 1998.
[67] A. Westfeld and A. Pfitzmann, Attacks on steganographic systems, in Proc. 3rd Int. Work- shop on Information Hiding, vol. 1768, pp. 61-76. 1999.
[68] J. Fridrich, M. Goljan, and R. Du, Detecting lsb steganography in color, and gray-scale images, IEEE, Multimedia, vol. 8, no. 4, pp. 22-28, Oct. 2001.
[69] A. Latham, JPEG Hide and Seek. 1999. Available:
[70] N. Provos, Outguess.   [Online].    Available:
[71]  J. Fridrich, M. Goljan, and D. Soukal, Perturbed quantization steganography, Multimedia Syst., vol. 11, no. 2, pp. 98-107, Dec. 2005.
[72]  K. S. Wong, X. Qi, and K. Tanaka,  A DCT-based Mod4 steganographic method, Signal Processing, vol. 87, pp. 1251-1263, 2007.
[73]  C. K. Chan and L. Cheng, Hiding data in images by simple lsb substitution, Pattern Recognition, vol. 37, no. 3, pp. 469 - 474, 2004.
[74]  C. H. Yang,  Inverted pattern approach to improve image quality of information  hiding by lsb substitution, Pattern Recognition, vol. 41, no. 8, pp. 2674 - 2683, 2008.
[75]  X. Zhang and S. Wang, Efficient steganographic embedding by exploiting modification direction, Communications  Lett., IEEE, vol. 10, no. 11, pp.
781 -783, Nov. 2006.
[76] R. M. Chao, H. C. Wu, C. C. Lee, and Y. P. Chu, A novel image data hiding scheme with diamond encoding, EURASIP J. Inf. Security, vol. 4, 2009.
[77] W. Hong and T. S. Chen, A novel data embedding method using adaptive pixel pair matching, IEEE Trans.  on Info. Forensics and Security, vol. 7, no. 1, pp. 176 -184, Feb. 2012.
[78]  C. F. Lee, C. C. Chang,  and  K. H. Wang,  An improvement of EMD  embedding method for large payloads by pixel segmentation strategy, Image and Vision Computing,  vol. 26, no. 12, pp. 1670 - 1676, 2008.
[79]  W. Hong, T. S. Chen, and C. W. Shiu, A minimal Euclidean  distance  searching  technique  for sudoku steganography, in International Symposium Info. Science and Engineering, vol. 1, pp. 515 -518. 2008.
[80] J. Wang, Y. Sun, H. Xu, K. Chen, H. J. Kim, and S. H. Joo, An improved section-wise exploiting modification direction method, Signal Processing, vol. 90, no. 11, pp. 2954 - 2964, 2010.
[81] B. Chen and G. Wornell, Quantization index modulation: A class of provably good methods for digital watermarking and information embed- ding, IEEE Trans.  Inf. Theory, vol. 47, no. 4, pp. 1423-1443, May 2001.
[82] T. H. Lan, A. H. Tewfik, A novel high-capacity data-embedding system, IEEE Trans.  On Image Process., vol. 15, no. 8, , pp.  2431-2440, Aug. 2006.
[83] J.  J.  Eggers, R.  Buml, R.  Tzschoppe, and B. Girod, Scalar costa scheme for information embedding, IEEE Trans.  Signal Process., vol. 4, no. 51, pp. 1003-1019, Apr. 2003.
[84] R. Zamir, S. Shamai, and U. Erez, Nested linear/lattice codes for structured multi-terminal binning, IEEE Trans. Inf. Theory, vol. 48, no. 6, pp. 1250-1276, Jul. 2002.
[85] J.  J. Eggers, J. K. Su, B. Girod, A blind watermarking scheme based on structured code-books, In Secure Images and Image Authentication, Proc.  IEE Colloquium, pp. 4/1-4/6, Lon- don, UK, Apr. 2000.
[86] Q. Zhang, and N. Boston, Quantization index modulation using E8 lattice, Proc. of 41th Annual Allerton Conf. on Communication, Control and Computing, Allerton,  IL, USA, 2003.
[87]  R. Fischer, R. Tzschoppe, and R. Buhamel, Lattice costa schemes using subspace projection for digital watermarking, European Trans. Telecommunications, vol. 15, no. 4, pp. 51-362, Aug. 2004.
[88] A. Abrardo and M. Barni, Informed watermarking by means of orthogonal and quasi-orthogonal dirty paper coding, IEEE Trans.  Signal Processing, vol. 53, no. 2, pp. 824-833, 2005.
[89] M. A. Akhaee, M. J. Saberian, S. Feizi, and F. Marvasti, Robust audio data hiding using correlated quantization with histogram based detector, IEEE Trans. on Multimedia, vol. 11, no. 5, pp. 834-842, Aug. 2009.
[90] J. J. Eggers, R. Buml, and B. Girod, Estimation of amplitude modifications before SCS watermark detection, Proc. SPIE Security Watermarking Multimedia Contents, vol. 46 no. 75, pp. 387-398, Jan.  2002.
[91]  M. L. Miller, G. J. Doerr, and I. J. Cox, Applying informed  coding and  embedding to design a robust  high capacity  watermark, IEEE  Trans. Image Process.,  vol. 13, no. 6, pp. 792-807, Jun. 2004.
[92] F. Perz-Gonzalez, C. Mosquera, M. Barni, and A. Abrado, Rational dither modulation: A high rate data-hiding method invariant to gain attacks, IEEE Trans.  Signal Process., vol. 53, no. 10, pp. 3960-3975, Oct. 2005.
[93] A. Abrardo, M. Barni, F. Perez-Gonzallez and C. Mosquera, Improving the performance of RDM watermarking by means of trellis coded quantization, IEE Proc.  Inf. Security, vol. 153, no. 3, pp. 107-114, Sept. 2006.
[94] P. Guccione, M. Scagliola, Hyperbolic RDM for nonlinear volumetric distortions, IEEE Trans. Inf. Forensics and Security,  vol. 4, no. 2, pp. 25-35, March 2009.
[95]  F. Perz-Gonzalez, C. Mosquera, Quantization-based data hiding robust to linear-time-invariant filtering, IEEE Trans. Inf. Forensics Security, vol. 3, no. 2, pp. 137-152, June 2008.
[96] M. A. Akhaee, A. Amini, G. Ghorbani, and F. Marvasti, A solution to gain attack on water marking systems: Logarithmic homogeneous rational dither modulation, Proc. of International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1312-1316, 2010.
[97] P. Comesaa and F. Perez-Gonalez, Dither modulation in the logarithmic domain, Proc. of International Workshop  in Digital Watermarking (IWDW’07),  Guangzhou, China,  Dec. 2007.
[98] P. Comesata and F. Perez-Gonzalez, On a watermarking scheme in the logarithmic domain and its perceptual advantages, Proc. of International Conference on Image Processing (ICIP’07), pp. 2036-2039, 2007.
[99] U. Erez and R. Zamir, Achieving (1=2log(1+SNR) on the AWGN channel  with lattice encoding and decoding, IEEE  Trans. on Inf. Theory, vol. 50, no. 10, pp. 2293-2314, Oct. 2004.
[100] P. Moulin and  R. Koetter, Data-hiding codes, IEEE Trans. on Signal Process., vol. 93, no. 12, pp. 2081-2127, Dec. 2005.
[101] R. Tzschoppe,  R. Bahml,  R. Fischer,  A. Kaup, and J. Huber, Additive non-Gaussian attacks  on the scalar costa scheme, in Proc. SPIE, San Jose, CA, Jan.  2005.
[102] P. Moulin, and A. K. Goteti, Block QIM watermarking games, IEEE  Trans. on Inf. Forensics and Security, vol. 1, no. 3, pp. 293-310, Sept. 2006.
[103] N. K. Kalantari, S. M. Ahadi,  A logarithmic quantization index modulation for perceptually better data hiding, Image Processing, IEEE Transactions on, vol. 19, no. 6, pp. 1504,1517, June  2010.
[104] W. Bender, D. Gruhl, N. Morimoto, and A. Lu, Techniques for data  hiding, IBM Systems, vol. 35, no. 3, pp. 313-336, 1996.
[105] M. Arnold, Audio watermarking: Features, applications and algorithms, IEEE International Conference Multimedia and Expo, vol. 2, pp. 1013-1016, 2008.
[106] I. K. Yeo and H. J. Kim, Modified patchwork algorithm: A novel audio watermarking scheme, IEEE Trans. on Speech, Audio, and Language Process., vol. 11, no. 4, pp. 381-386, Jul. 2003.
[107] I. K. Yeo, H. J. Kim Generalized patchwork algorithm for image watermarking, Multimedia Systems, vol. 9, no. 3, pp. 261-265, 2003.
[108] H. Malik, R. Ansari, and A. Khokhar, Robust data hiding in audio using allpass filters, IEEE Trans. on Audio, Speech, and Language Process., vol. 15, no. 4, pp. 1296-1304, May 2007.
[109] A. Takahashi, R. Nishimura, Y. Suzuki, Multiple watermarks for stereo audio signals using phase-modulation techniques, IEEE Trans. on Signal Process.,  vol. 53, no. 2 , pp. 806-815, Feb. 2005.
[110] D. Gruhl and W. Bender, Echo hiding, Proc. of Information Hiding Workshop, pp. 295-315, 1996.
[111] H. O. Oh, J. W. Seok, J. W. Hong, and D. H. Youn, New echo embedding technique for robust and imperceptible  audio watermarking, Proc. of International Conference  on Acoustics,  Speech and Signal Processing (ICASSP),  pp. 2011-2014, 2001.
[112] C. Xu, J. Wu, Q. Sun, and K. Xin, Applications of digital watermarking technology in audio signals, J. Audio Eng. Soc., vol. 47, no. 10, Oct. 1999.
[113] B. S. Ko, R. Nishimura, and Y. Suzuki,  Time-spread echo method for digital audio watermarking, IEEE Trans. on Multimedia, vol. 7 , no. 2 , pp. 212-221, Apr. 2005.
[114] O. T. C. Chen, W. C. Wu, Highly Robust, Secure, and  Perceptual-Quality Echo Hiding  Scheme, IEEE Trans. on Audio, Speech, and Language Process.,  vol. 16, no. 3, pp. 629-638, Mar. 2008.
[115] I. J. Cox, M. L. Miller, and A. L. McKellips, Watermarking as communications with side information, Proceeding of the IEEE, 87, pp. 1127-1141, July 1999.
[116] A. B. Watson, J. Hu, and J. F. McGowan, III, DVQ: A digital video quality metric based on human vision, Journal Electronic Imaging, vol. 10, pp. 20-29, Jan.  2001.
[117] A. B. Watson, J. Y. Yang, J. A. Solomon, and J. Villasenor, Visibility  of wavelet quantization noise, IEEE Trans. on Image Process., vol. 6, no. 8, pp. 1164-1175, Oct. 1997.
[118] I. J. Cox, J. Kilian, F.T. Leighton, and T. Shamoon, Secure spread spectrum watermarking for multimedia, IEEE Trans.  Image Process., vol. 6, no. 12, pp. 1673-1687, 1997.
[119] Q. Cheng and T.S. Huang, An additive approach to transform-domain information hiding and optimum detection structure, IEEE Trans. Multimedia, vol. 3, no. 3, pp. 273-284, 2001.
[120] P. Moulin and A. Ivanovic The zero-rate spread spectrum watermarking game, IEEE Trans. on Signal  Process.,  vol. 51, no. 4, pp.  1098-1117, Apr. 2003.
[121] H. O. Altun, A. Orsdemir, G. Sharma, and M. F. Bocko, Optimal spread  spectrum watermark embedding via a multi-step feasibility formulation, IEEE Trans. Image Process., vol. 18, no. 2, pp. 371-386, Aug. 1999.
[122] L. M. Marvel, C. G. Boncelet, and C. T. Retter, Spread spectrum image steganography, IEEE Trans. on Signal Process., vol. 8, no. 8, pp. 1285-1293, Aug. 1999.
[123] S. P.  Maity, and S. Maity, Multistage spread spectrum watermark detection, IEEE Signal Processing Lett., vol. 16, no. 4, Apr. 2009.
[124] M. Barni, F. Bartolini, A. De Rosa, and A. Piva, A new decoder for the optimum recovery of non-additive watermarks, IEEE Trans. Image Process., vol. 10, no. 5, pp. 755-766, 2001.
[125] Q. Cheng, and T. S. Huang, Robust optimum detection of transform domain multiplicative watermarks, IEEE Trans. Signal Processing, vol. 51, no. 4, pp. 906-924, 2003.
[126] M. Barni, F. Bartolini, A. De Rosa, and A. Piva, Optimum decoding and detection of multiplicative watermarks, IEEE Trans. on Signal Process., vol. 51, no. 4, pp.1118-1123, 2003.
[127] T. M. Ng, H. Garg, Maximum likelihood  detection in image  watermarking using  generalized gamma model, Proc. of 39th Asilomar Conference on Signals,  Systemsand Computer, pp. 1680-1684, 2005.
[128] V. Solachidis,  and  I. Pitas, Optimal detector for multiplicative watermarks embedded  in the DFT domain  of non-white signals, EURASIP Journal on Applied Signal Processing, vol. 16, pp. 522-532, 2004.
[129] J. Wang, G. Liu, Y. Dai, and J. Sun, Locally optimum detection for Barni multiplicative watermarking in DWT domain, Signal Processing, vol. 88, pp. 117-130. 2008.
[130] M. N. Do, and M. Vetterli, The contourlet transform: An efficient directional multi-resolution image representation, IEEE Trans. on Image Process. vol. 14, no. 12, pp. 2091-2106, 2005.
[131] M. N. Do, and M. Vetterli, Framing pyramids, IEEE Trans. on Signal Process., pp. 23292342, Sep. 2003.
[132] M. A. Akhaee, N. Khademi-Kalantari, and F. Marvasti, Robust Multiplicative Audio and Speech Watermarking Using Statistical Modeling, Proc. of International Conference on Communications (ICC),  2009.
[133] M. A. Akhaee, N. K. Kalantari, F. Marvasti, Robust audio and speech watermarking using Gaussian and Laplacian modeling, Signal Processing, vol. 90, no. 8, pp. 2487-2497, August  2010.
[134] M. A. Akhaee, S. M. E. Sahraeian, F. Marvasti, and B. Sankur, Robust scaling-based image multiplicative watermarking technique using maximum likelihood decoder with optimum  strength factor, IEEE Trans. on Multimedia,  vol. 11, no 5, pp. 822-833, Aug. 2009.
[135] M. A. Akhaee, S. M. E. Sahraeian, F. Marvasti, Contourlet-based image watermarking using optimum detector in a noisy environment, IEEE Trans. on Image Process., vol.19, no.4, pp. 967-980, Apr 2010.
[136] N. K. Kalantari, S. M. Ahadi, M. Vafadust, M., A robust image watermarking in the ridgelet domain using universally optimum decoder, IEEE Trans. on Circuits and Systems for Video Technology, vol. 20, no. 3, pp. 396 -406, March 2010.
[137] M. A. Akhaee, S. M. E. Sahraeian, F. Marvasti, Universal optimum blind scaling based Watermarking using maximum likelihood decoder, Proc. of International Conference on Image Processing (ICIP), pp. 765-768, 2009.
[138] S. M. E. Sahraeian, M. A. Akhaee, F. Marvasti, Information hiding with optimal detector for highly correlated signals, Proc. of International Conference on Communications (ICC), 2009.
[139] J. J. Harmsen  and W. A. Pearlman, Steganalysis of additive-noise modelable information hiding, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conf., vol. 5020, pp. 131-142, 2003.
[140] A. D. Ker, Steganalysis of lsb matching in grayscale images, IEEE Signal Process. Lett., vol. 12, no. 6, pp. 441 - 444, Jun.  2005.
[141] X. Li, T. Zeng, and B.  Yang, Detecting lsb matching by applying calibration technique for difference image, Proc. of the 10th ACM workshop on Multimedia and  security, pp. 133-138, 2008.
[142] T. Pevny, P. Bas, and J. Fridrich, Steganalysis by subtractive pixel adjacency matrix, IEEE Trans. on Information Forensics and Security, vol. 5, no. 2, pp. 215 -224, Jun.  2010.
[143] H. Farid, Detecting hidden messages using higher-order statistical models, International Conference on Image Processing, vol. 2, pp. 905-908, 2002.
[144] I. Avcibas, N. Memon, and B. Sankur, Steganalysis using image quality  metrics, IEEE Transactions on Image Process., vol. 12, no. 2, pp. 221-229, 2003.
[145] F. Huang, B. Li, and J. Huang, Attack lsb matching steganography by counting alteration rate of the number of neighborhood gray levels, Proc. of International Conference on Image Processing, pp. 401-404, 2007.
[146] Y. Wang and P. Moulin, Optimized feature extraction for learning-based image steganalysis, IEEE Trans. on Info. Forensics and Security, vol. 2, no. 1, pp. 31 -45, Mar. 2007.
[147] T. Pevny, P. Bas, and J. Fridrich, Steganalysis by subtractive pixel adjacency matrix, IEEE Transactions on Info. Forensics and Security, vol. 5, no. 2, pp. 215-224, 2010.
[148] Y. Q. Shi, C. Chen, and W. Chen, A markov process based approach to effective attacking jpeg steganography, in Information Hiding. Springer, pp. 249-264, 2007.
[149] C. Chen and Y. Shi, Jpeg image steganalysis utilizing both intrablock and interblock correlations, Proc. of International Symposium on Circuits and Systems, pp. 3029-3032, 2008.
[150] T. Pevny and J. Fridrich, Merging Markov and DCT features for multi-class JPEG  steganalysis, Proceedings SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents, vol. 3, pp. 1117-1126 2007.
[151] J. Kodovsky, J. Fridrich, Steganalysis in high dimensions: fusing classifiers built on random subspaces, Proc. of SPIE  Media Watermarking, Security, and Forensics III, pp. 23-26, 2011.
[152] Y. Shi, G. Xuan, D. Zou, J. Gao, C. Yang, Z. Zhang, P. Chai, W. Chen, and C. Chen, Image steganalysis based on moments of characteristic functions using wavelet decomposition, prediction-error image, and neural network, Proc. of International Conference on Multimedia and Expo(ICME), 2005.
[153] C. C. Chang and C. J. Lin, Libsvm: a library for support vector machines, 2001, software available at
[154] J. Kodovsky, J. Fridrich, and V. Holub, Ensemble classifiers for steganalysis of digital media, IEEE Trans. on Info. Forensics and Security, vol. 7, no. 2, pp. 432-444, 2012.