Least Distortion Halftone Image Data Hiding Watermarking by Optimizing an Iterative Linear Gain Control Model

  • Weina Jiang
  • A. T. S. Ho
  • H. Treharne
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5041)


In this paper, a least distortion data hiding approach is proposed for halftone image watermarking. The impacts of distortion and tonality problems in halftoning are analyzed. An iterative linear gain model is developed to optimize perceptual quality of watermarking halftone images. An optimum linear gain for data hiding error diffusion is derived and mapped into a standard linear gain model, with the tonality evaluated using the average power spectral density. Our experiments show that the proposed linear gain model can achieve an improvement of between 6.5% to 12% as compared to Fu and Au’s data hiding error diffusion method using the weighted signal-to-noise ratio(WSNR).


Image Watermark Quantization Error Perceptual Quality Host Image Data Hiding 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Floyd, R., Steinberg, L.: An adaptive algorithm for spatial grayscale. Proceedings of the. Society for Information Display 17(2), 75–77 (1976)Google Scholar
  2. 2.
    Fu, M.S., Au, O.C.: Data hiding watermarking for halftone images. IEEE Transactions on Image Processding 11(4) (April 2002)Google Scholar
  3. 3.
    Horowitz, P., Hill, W.: The art of Eletronics. Combridge Univ. Press, Cambridgem UK (1980)Google Scholar
  4. 4.
    Hsieh, C.-T., Lu, Y.-L., Luo, C.-P., Kuo, F.-J.: A study of enhancing the robustness of watermark. In: Proceedings of International Symposium on Multimedia Software Engineering, 2000., pp. 325–327 (2000)Google Scholar
  5. 5.
    Jarvis, W.N.J., Judice, C.: A survey of techniques for the display of continuous tone pictures on bilevel displays. Comp. Graph. and Image Proc 5, 13–40 (1976)CrossRefGoogle Scholar
  6. 6.
    Kite, T.D., Evans, B.L., Bovik, A.C.: Modeling and quality assessment of halftoning by error diffusion. IEEE Transactions on Image Processing 9(5) (May 2000)Google Scholar
  7. 7.
    Knox, K.: Error image in error diffusion. In: SPIE, Image Processing Algorithms and Techniques III, vol. 1657, pp. 268–279 (1992)Google Scholar
  8. 8.
    Lfeachor, E.C., Jervis, B.W.: Digital Signal Processing: A Practical Approach. In: Dagless, E.L. (ed.). Addison-Wesley, Reading (1993)Google Scholar
  9. 9.
    U. of Surrey, “Surrey logo” (2007),
  10. 10.
    Petitcolas, F., Anderson, R., Kuhn, M.: Information hiding-a survey. IEEE Proceedings 87(7), 1062–1078 (1999)CrossRefGoogle Scholar
  11. 11.
    Solanki, K., Madhow, U., Manjunath, B.S., Chandrasekaran, S., El-Khalil, I.: ’print and scan’ resilient data hiding in images. IEEE Transactions on Information Forensics and Security (August 2006),
  12. 12.
    Soo-Chang Pei, J.-M.G.: High-capacity data hiding in halftone images using minimal-error bit searching and least-mean square filter. IEEE Transactions on Image Processding 15(6) (June 2006)Google Scholar
  13. 13.
    Ulichney, R.: Digital Halftoning. MIT Press, Cambridge (1987)Google Scholar
  14. 14.
    Williams, R.: Electrical Engineering Probability. West, St.Paul,MN (1991)Google Scholar
  15. 15.
    Wu, C.W., Thompson, G., Stanich, M.: Digital watermarking and steganography via overlays of halftone images. IBM Research Division,Thomas J. Watson Research Center, P.O. Box 218,Yorktown Heights, NY 10598, IBM Research Report (July 2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Weina Jiang
    • 1
  • A. T. S. Ho
    • 1
  • H. Treharne
    • 1
  1. 1.The Department of ComputingUniversity of SurreyGuildfordUK

Personalised recommendations