Optimal spread spectrum watermark embedding via a multistep feasibility formulation

IEEE Transactions on Image Processing

Volumn 18, Issue 2, 2009, Pages 371-387

  Altun, H Oktay ^a   Orsdemir, Adem ^a   Sharma, Gaurav ^b   Bocko, Mark F ^a  

^a University of Rochester   (United States)

^b UNIVERSITY OF ROCHESTER MEDICAL CENTER   (United States)

Author keywords

Optimum watermark design; Projections onto convex sets (POCS); Set theoretic watermarking; Spread spectrum watermarking

Indexed keywords

BIOLOGICAL MATERIALS; CONVEX OPTIMIZATION; OPTIMIZATION; PARAMETER ESTIMATION; SET THEORY; SPECTRUM ANALYSIS; WATERMARKING;

ALGORITHMIC FRAMEWORKS; CONVEX FEASIBILITIES; DETECTABILITY; EMBEDDINGS; GLOBAL OPTIMUM; MULTI STEPS; NATURAL EXTENSIONS; OBJECTIVE FUNCTIONS; OPTIMAL EMBEDDING; OPTIMAL FORMULATIONS; OPTIMIZATION FORMULATIONS; OPTIMUM VALUES; OPTIMUM WATERMARK DESIGN; PERCEPTUAL DISTORTIONS; PROJECTIONS ONTO CONVEX SETS (POCS); QUASI-CONVEX FORMULATIONS; SET THEORETIC WATERMARKING; SPREAD SPECTRUM WATERMARKING; SPREAD SPECTRUMS; WATERMARK EMBEDDING; WATERMARKED IMAGES;

PAPERMAKING;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER SECURITY; FEASIBILITY STUDY; IMAGE ENHANCEMENT; INFORMATION PROCESSING; METHODOLOGY; PACKAGING; PATENT; SIGNAL PROCESSING;

ALGORITHMS; COMPUTER GRAPHICS; COMPUTER SECURITY; DATA COMPRESSION; FEASIBILITY STUDIES; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATENTS AS TOPIC; PRODUCT LABELING; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 59649128970     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2008.2008222     Document Type: Article

References (39)

1. O. Altun, G. Sharma, and M. Bocko, "Optimum watermark design by vector space projections," in Proc. Int. Conf. Image Processing, 2006, pp. 1413-1416.
2. I. Cox, M. Miller, J. Bloom, J. Fridrich, and T. Kalker, Digital Watermarking and Steganography, 2nd ed. San Francisco, CA: Morgan Kaufmann, 2007.
3. C. Podilchuk and E. Delp, "Digital watermarking: Algorithms and applications," IEEE Signal Process. Mag., vol. 18, no. 4, pp. 33-46, Jul. 2001.
4. G. Langelaar, I. Setyawan, and R. Lagendijk, "Watermarking digital image and video data," IEEE Signal Process. Mag., vol. 17, no. 5, pp. 20-46, Sep. 2000.
5. M. Barni and F. Bartolini, "Data hiding for fighting piracy," IEEE Signal Process. Mag., vol. 21, no. 2, pp. 28-29, Mar. 2004.
6. M. U. Celik, G. Sharma, and A. M. Tekalp, "Lossless watermarking for image authentication: A new framework and an implementation," IEEE Trans. Image Process., vol. 15, no. 4, pp. 1042-1049, Apr. 2006.
7. T. Ohsawa and M. Karita, "Automatic Telecasting or Radio Broadcasting Monitoring System," U.S. patent (3,760,275), 1973.
8. M. Wu, W. Trappe, Z. Wang, and K. Liu, "Collusion-resistant fingerprinting for multimedia," IEEE Signal Process. Mag., vol. 21, no. 2, pp. 15-27, Feb. 2004.
9. I. 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, Dec. 1997.
10. K. Solanki, N. Jacobsen, U. Madhow, B. S. Manjunath, and S. Chandrasekaran, "Robust image-adaptive data hiding based on erasure and error correction," IEEE Trans. Image Process., vol. 13, no. 12, pp. 1627-1639, Dec. 2004.
11. M. L. Miller, G. J. Doërr, and I. J. Cox, "Dirty-paper trellis codes for watermarking," in Proc. Int. Conf. Image Processing, 2002, pp. 129-132.
12. J. Fridrich, M. Goljan, and D. Soukal, "Wet paper codes with improved embedding efficiency," IEEE Trans. Inf. Forensics Security, vol. 1, no. 1, pp. 102-110, Jan. 2006.
13. B. Chen and G. W. Wornell, "Quantization index modulation: A class of provably good methods for digital watermarking and information embedding," IEEE Trans. Inf. Theory, vol. 47, no. 4, pp. 1423-1443, May 2001.
14. S. Pereira, S. Voloshynoskiy, and T. Pun, "Optimal transform domain watermark embedding via linear programming," Signal Process., vol. 81, no. 6, pp. 1251-1260, Jun. 2001.
15. M. K. Mihcak, R. Venkatesan, and M. Kesal, "Optimization algorithms for quantizing randomized statistics of image regions," presented at the 40th Annu. Allerton Conf. Communication, Control and Computing, Oct. 2002.
16. M. L. Miller, I. J. Cox, and J. A. Bloom, "Informed embedding: Exploiting image and detector information during watermark insertion," presented at the Int. Conf. Image Processing, 2000.
17. O. Altun, G. Sharma, M. Celik, and M. Bocko, "A set theoretic framework for watermarking and its application to semifragile tamper detection," IEEE Trans. Inf. Forensics Security, vol. 1, no. 4, pp. 479-492, Dec. 2006.
18. O. Altun, G. Sharma, M. Celik, and M. Bocko, "Semifragile hierarchical watermarking in a set theoretic framework," in Proc. Int. Conf. Image Processing, 2005, vol. 1, pp. 1001-1004.
19. S. Boyd, Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press.
20. H. Stark and Y. Yang, Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics. New York: Wiley, 1998.
21. H. J. Trussell and M. R. Civanlar, "The feasible solution in signal restoration," IEEE Trans. Acoust. Speech Signal Process., vol. ASSP-32, no. 4, pp. 201-212, Apr. 1984.
22. P. L. Combettes, "The foundations of set theoretic estimation," Proc. IEEE, vol. 81, no. 2, pp. 182-208, Feb. 1993.
23. Y. Yang, N. P. Galatsanos, and A. Katsaggelos, "Projection-based spatially adaptive reconstruction of block transform compressed images," IEEE Trans. Image Process., vol. 4, no. 7, pp. 896-908, Jul. 1995.
24. G. Sharma, "Set theoretic estimation for problems in subtractive color," Color Res. Appl., vol. 25, no. 4, pp. 333-348, Oct. 2000.
25. G. Sharma and H. J. Trussell, "Set theoretic signal restoration using an error in variables criterion," IEEE Trans. Image Process., vol. 6, no. 12, pp. 1692-1697, Dec. 1997.
26. I. J. Cox, M. L. Miller, and J. A. Bloom, Digital Watermarking. San Francisco, CA: Morgan Kaufmann, 2001.
27. J. L. Mannos and D. L. Sakrison, "The effects of a visual fidelity criterion on the encoding of images," IEEE Trans. Inf. Theory, vol. 20, no. 7, pp. 525-536, Jul. 1974.
28. V. K. Goyal, "Theoretical foundations of transform coding," IEEE Signal Process. Mag., vol. 18, no. 9, pp. 9-21, Sep. 2001.
29. S. Pereira, S. Voloshynoskiy, and T. Pun, "Optimal transform domain watermark embedding via linear programming," Signal Process., vol. 81, no. 6, pp. 1251-1260, 2001.
30. L. M. Bregman, "The method of successive projection for finding a common point of convex sets," Dokl. Akad. Nauk. SSSR, vol. 162, no. 3, pp. 688-692, 1965.
31. P. L. Combettes, "The foundations of set theoretic estimation," Proc. IEEE, vol. 81, no. 1, pp. 182-208, Feb. 1993.
32. [Online]. Available: http://sipi.usc.edu/database/
33. O. Altun, G. Sharma, and M. Bocko, C. A. Bouman and E. L. Miller, Eds., "Multiple watermarking: A vector space projections approach," in Proc. SPIE: Computational Imaging IV, Jan. 2006, vol. 6065, pp. 60650O1-60650O12.
34. P. Moulin and J. A. O'Sullivan, "Information-theoretic analysis of information hiding," IEEE Trans. Inf. Theory, vol. 49, no. 3, pp. 563-593, Mar. 2003.
35. A. B. Watson and J. A. Solomon, "Model of visual contrast gain control and pattern masking," J. Opt. Soc. Amer., vol. 14, no. 19, pp. 2379-2391, 1994.
36. J. Lubin, "A visual discrimination model for imaging system design and evaluation," in Vision Models for Target Detection and Recognition E. Peli, Ed. Singapore: World Scientific, 1995, pp. 245-283.
37. S. Daly, "A visual model for optimizing the design of image processing algorithms," in Proc. IEEE Int. Conf. Image Processing, Austin, TX, Nov. 1994, vol. 2, pp. 16-20.
38. S. Voloshynoskiy, A. Herrigel, N. Baumgaertner, and T. Pun, "A stochastic approach to content adaptive digital image watermarking," in Proc. 3rd Int. Workshop on Information Hiding, Dresden, Germany, 1999, pp. 211-236.
39. D. G. Luenberger, Linear and Nonlinear Programming. Reading, MA: Addison Wesley, 1989.