Skip to main content

Better Use of Human Visual Model in Watermarking Based on Linear Prediction Synthesis Filter

  • Conference paper
Digital Watermarking (IWDW 2004)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 3304))

Included in the following conference series:

Abstract

This paper presents a new approach on utilizing human visual model (HVM) for watermarking. The approach introduces the linear prediction synthesis filter, whose parameters are derived from a set of just noticeable differences estimated by HVM. After being filtered by such a filter, the watermark can be adapted to characteristics of human visual system. As a result, the watermark visibility is noticeably decreased, while at the same time enhancing its energy. The theoretic analysis of the detector is done to illustrate the affect of the filter on detection value. And the experimental results prove the effectiveness of the new approach.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cox, I., Miller, M.L.: A review of watermarking and the importance of perceptual modeling. In: Proc. Electronic Imaging (February 1997)

    Google Scholar 

  2. Tewfik, A.H., Swanson, M.: Data hiding for multimedia personalization, interaction, and protection. IEEE Signal Processing Mag. 14, 41–44 (1997)

    Article  Google Scholar 

  3. Wolfgang, R.B., Podilchuk, C.I., Delp, E.J.: Perceptual watermarks for digital images and video. Proc. IEEE 87, 1108–1126 (1999)

    Article  Google Scholar 

  4. Voloshynovskiy, S., Herrigel, A., Baumgaetner, N., Pun, T.: A stochastic approach to content-adaptive digital image watermarking. In: Third International Workshop on Information Hiding (1999)

    Google Scholar 

  5. Jayant, N., Johnston, J., Safranek, R.: Signal compression based on models of human perception. Proc. IEEE 81 (October 1993)

    Google Scholar 

  6. Watson, B.: DCT quantization matrices optimized for individual images. In: Human Vision, Visual Processing, and Digital Display IV, SPIE, vol. 1913, pp. 202–216 (1993)

    Google Scholar 

  7. Watson, A.B., Yang, G.Y., Solomon, J.A., Villasenor, J.: Visual thresholds for wavelet quantization error. In: Human Vision and Electronic Imaging, SPIE, vol. 2657, pp. 381–392 (1996)

    Google Scholar 

  8. Lewis, A.S., Knowles, G.: Image compression using the 2-D wavelet transform. IEEE Trans. Image Processing 1, 244–250 (1992)

    Article  Google Scholar 

  9. Podilchuk, C.I., Zeng, W.: Image-adaptive watermarking using visual models. IEEE J. Selected Areas Comm. 16(4), 525–539 (1998)

    Article  Google Scholar 

  10. Barni, M., Bartolini, F., Cappellini, V., Piva, A.: A DCT-domain System for Robust Image Watermarking. IEEE Transactions on Signal Processing 66(3), 357–372 (1998)

    MATH  Google Scholar 

  11. Delaigle, J.F., De Vleeschouwer, C., Macq, B.: Watermarking Algorithm Based on Human Visual Model. IEEE Transactions on Signal Processing 66(3), 319–335 (1998)

    MATH  Google Scholar 

  12. Kim, Y.S., Kwon, O.H., Park, R.H.: Wavelet based watermarking method for digital images using the human visual system. In: ISCAS 1999. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems vol. 4(30) (June 1999)

    Google Scholar 

  13. Vleeschouwer, C.D., Delaigle, J.F., Macq, B.: Invisibility and application functionalities in perceptual watermarking an overview. Proceedings of the IEEE 90(1), 64–77 (2002)

    Article  Google Scholar 

  14. Cox, I.J., Miller, M.L., Bloom, J.A.: Digital Watermarking. Academic Press, San Francisco (2002)

    Google Scholar 

  15. Rangsanseri, Y., Thitimajshima, W.: Copyright protection of images using human visual masking on DCT-based watermarking. In: APCCAS 2002. Asia-Pacific Conference on Circuits and Systems, October 2001, vol. 1, pp. 28–31 (2002)

    Google Scholar 

  16. Barni, M., Bartolini, F., Piva, A.: Improved Wavelet-Based Watermarking Through Pixel-Wise Masking. IEEE Transactions on Image Processing 10(5), 783–791 (2001)

    Article  MATH  Google Scholar 

  17. Saravanan, V., Bora, P.K., Ghosh, D.: Oblivious Image-Adaptive Watermarking Using Quantization Index Modulation. In: The Eighth National Conf. on Communications, India, January 2002, pp. 26–37 (2002)

    Google Scholar 

  18. Haykin, S.: Adaptive Filter Theory, 3rd edn. Prentice Hall, Englewood Cliffs (1998)

    MATH  Google Scholar 

  19. Lawrence Marple Jr., S.: Two-dimensional Lattice Linear Prediction Parameter Estimation Method and Fast Algorithm. IEEE Signal Processing Letters 7, 164–168 (2000)

    Article  Google Scholar 

  20. Kuo, S.-S., Johnston, J.D.: Spatial Noise Shaping Based on Human Visual Sensitivity and Its Application to Image Coding. IEEE Transactions on Image Processing 11(5), 509–517 (2002)

    Article  Google Scholar 

  21. Miller, M.L., Bloom, J.A.: Computing the probability of false watermark detection. In: Proceeding of the Third International Workshop on Information Hiding, pp. 146–158 (1999)

    Google Scholar 

  22. Helstrom, C.W.: Statistical Theory of Signal Detection. Pergamon Press, New York (1960)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhu, X., Wang, Y. (2005). Better Use of Human Visual Model in Watermarking Based on Linear Prediction Synthesis Filter. In: Cox, I.J., Kalker, T., Lee, HK. (eds) Digital Watermarking. IWDW 2004. Lecture Notes in Computer Science, vol 3304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31805-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-31805-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24839-2

  • Online ISBN: 978-3-540-31805-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics