Step-projection-based spread transform dither modulation

X. Li; J. Liu; J. Sun; X. Yang; W. Liu

Step-projection-based spread transform dither modulation

Access Full Text

Step-projection-based spread transform dither modulation

Author(s): X. Li ; J. Liu ; J. Sun ; X. Yang ; W. Liu
DOI: 10.1049/iet-ifs.2010.0218

For access to this article, please select a purchase option:

Buy article PDF

Buy Knowledge Pack

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership

Recommend Title Publication to library

IET Information Security — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Author(s): X. Li ¹ ; J. Liu ^{1, 2} ; J. Sun ¹ ; X. Yang ¹ ; W. Liu ²
- Affiliations: 1: School of Information Science and Engineering, Shandong University, Jinan, People's Republic of China
  2: School of Information Science and Engineering, Hisense State Key Laboratory of Digital Multi-Media Technology Co. Ltd, Qingdao, People's Republic of China
Source: Volume 5, Issue 3, September 2011, p. 170 – 180
DOI: 10.1049/iet-ifs.2010.0218 , Print ISSN 1751-8709, Online ISSN 1751-8717

Published

Quantisation index modulation (QIM) is an important class of watermarking methods, which has been widely used in blind watermarking applications. It is well known that spread transform dither modulation (STDM), as an extension of QIM, has good performance in robustness against random noise and re-quantisation. However, the quantisation step-sizes used in STDM are random numbers not taking features of the image into account. The authors present a step projection-based approach to incorporate the perceptual model with STDM framework. Four implementations of the proposed algorithm are further presented according to different modified versions of the perceptual model. Experimental results indicate that the step projection-based approach can incorporate the perceptual model with STDM framework in a better way, thereby providing a significant improvement in image fidelity. Compared with the former proposed modified schemes of STDM, the author's best performed implementation provides powerful resistance against common attacks, especially in robustness against Gauss noise, salt and pepper noise and JPEG compression.

References

1. 1)
  - M. Costa . Writing on dirty paper. IEEE Trans. Inf. Theory , 3 , 439 - 441
2. 2)
  - R.L. Lagendijk , I.D. Shterev . Estimation of attacker's scale and noise variance for QIM-DC watermark embedding. IEEE Int. Image Process. , 55 - 58
3. 3)
  - Lee, K., Kim, D.S., Kim, T., Moon, K.A.: `EM estimation of scale factor for quantization-based audio watermarking', Int. Workshop on Digital Watermarking, October 2003, Seoul, Korea.
4. 4)
  - P. Guccione , M. Scagliola . Hyperbolic RDM for nonlinear valumetric distortions. IEEE Trans. Inf. Forensics Secur. , 25 - 35
5. 5)
  - Watson, A.B.: `DCT quantization matrices optimized for individual images', SPIE. Proc. Human Vision, Visual Processing, and Digital Display IV, 1993, SPIE-1993, p. 202–216.
6. 6)
  - Eggers, J., Bauml, R., Girod, B.: `Estimation of amplitude modifications before SCS watermark detection', SPIE. Proc. Security, Steganography, and Watermarking of Multimedia Contents VI, January 2002, p. 387–398.
7. 7)
  - Q. Li , I.J. Cox . Using perceptual models to improve fidelity and provide resistance to valumetric scaling for quantization index modulation watermarking. IEEE Trans. Inf. Forensics Secur. , 2 , 127 - 139
8. 8)
  - Li, Q., Doerr, G., Cox, I.J.: `Spread transform dither modulation using a perceptual model', IEEE Int. Workshop Multimedia Signal Processing, October 2006, p. 98–102.
9. 9)
  - Shterev, I.D., Lagendijk, I.L., Heusdens, R.: `Statistical amplitude scale estimation for quantization-based watermarking', SPIE. Proc. Security, Steganography, and Watermarking of Multimedia Contents VI, January 2004, 5306, p. 796–804.
10. 10)
  - F. Guerrini , R. Leonardi , M. Barni . Image watermarking robust against non-linear value-metric scaling based on higher order statistics. IEEE ICASSP , 397 - 400
11. 11)
  - Yu, D., Ma, L., Wang, G., Lu, H.: `Adaptive spread-transform dither modulation using an improved luminance-masked threshold', IEEE ICIP, October 2008, p. 449–452.
12. 12)
  - Bas, P.: `A quantization watermarking technique robust to linear and non-linear valumetric distortions using a fractal set of floating quantizers', Seventh Int. Workshop Information Hiding, June 2005, Barcelona, Spain.
13. 13)
  - I. Cox , J. Bloom , M. Miller . (2001) Digital watermarking.
14. 14)
  - Oostveen, J., Kalker, A., Staring, M.: `Adaptive quantization watermarking', SPIE. Proc. Security, Steganography, and Watermarking of Multimedia Contents VI, 2004, 5306, p. 37–39.
15. 15)
  - P. Moulin , R. Koetter . Data-hiding codes. Proc. IEEE , 2083 - 2127
16. 16)
  - B. Chen , G. Wornell . Quantization index modulation, a class of provably good methods for digital watermarking and information embedding. IEEE Trans. Inf. Theory , 4 , 1423 - 1443
17. 17)
  - F. Pèrez-Gonzàlez , F. Mosquera , M. Barni , A. Abrardo . Rational dither modulation: a high-rate data-hiding method invariant to gain attacks. IEEE Trans. Signal Process. , 10 , 3960 - 3975
18. 18)
  - Q. Li , I.J. Cox . Improved spread transform dither modulation using a perceptual model: robustness to amplitude scaling and JPEG compression. IEEE ICASSP , 185 - 188

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Step-projection-based spread transform dither modulation

Step-projection-based spread transform dither modulation

Buy article PDF

Buy Knowledge Pack

Thank you

References

Related content