Comparative Study of Wavelet Based Lattice QIM Techniques and Robustness against AWGN and JPEG Attacks

  • Dieter Bardyn
  • Ann Dooms
  • Tim Dams
  • Peter Schelkens
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5703)


We study watermarking techniques based on Quantization Index Modulation for which sets of lattice quantizers Q m are used (LQIM). A recipe for constructing such quantizers Q m is proposed, where the size of these sets is variable, so that the payload is easily adaptable. We make a comparative study of 8 dimensional lattices with good quantizer properties, where the embedding is done in the wavelet domain. Along the way, the gap between the theoretical ideas behind QIM and practical systems using lattices is closed by extending techniques, such as dithered quantizers and distortion compensation, from the scalar case to LQIM.


Digital Watermarking Quantization Index Modulation Lattice 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Balado, F., Perez-Gonzalez, F.: Hexagonal quantizers are not optimal for 2-D data hiding. In: Proc. of SPIE Security and Watermarking of Multimedia Contents V, vol. 5020, pp. 623–631. Santa Clara (2003)Google Scholar
  2. 2.
    Chen, B., Wornell, G.W.: Digital watermarking and information embedding using dither modulation. In: Proc. of 1998 IEEE Second Workshop on Multimedia Signal Processing, pp. 273–278. IEEE Press, Redondo Beach (1998)Google Scholar
  3. 3.
    Chen, B., Wornell, G.W.: Quantization Index Modulation: A class of provably good methods for digital watermarking and information embedding. IEEE Trans. Inf. Theory 47(4), 1423–1443 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Conway, J.H., Sloane, N.J.A.: Fast Quantizing and Decoding Algorithms for Lattice Quantizers and Codes. IEEE Trans. Inf. Theory 28(2), 227–232 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Conway, J.H., Sloane, N.J.A.: Sphere Packings, Lattices and Groups. Springer, New York (1999)CrossRefzbMATHGoogle Scholar
  6. 6.
    Conway, J.H., Rains, S.N.J.A.: On the existence of similar sublattices. Canad. J. Math. 51(6), 1300–1306 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Cornelis, B., Barbarien, J., Dooms, A., Munteanu, A., Cornelis, J., Schelkens, P.: Design and evaluation of sparse quantization index modulation watermarking schemes. In: Proc. of SPIE Applications of Digital Image Processing XXXI, San Diego, vol. 7073 (2008)Google Scholar
  8. 8.
    Eggers, J.J., Bäuml, R., Tzschoppe, R., Girod, B.: Scalar Costa scheme for information embedding. IEEE Trans. Signal Process. 51(4), 1003–1019 (2003)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Erez, U., Zamir, R.: Achieving (1/2)log(1+SNR) on the AWGN channel with lattice encoding and decoding. IEEE Trans. Inf. Theory 50(10), 2293–2314 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Kirac, A., Vaidyanathan, P.P.: Dithering in lattice quantization. In: Conf. Rec. of the 29th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, vol. 2, pp. 1066–1070 (1995)Google Scholar
  11. 11.
    Martinet, J.: Perfect Lattices in Euclidean Spaces. Springer, Berlin (2003)CrossRefzbMATHGoogle Scholar
  12. 12.
    Moulin, P., Koetter, P.: Data Hiding Codes (tutorial paper). Proceedings IEEE 93(12), 2083–2127 (2005)CrossRefGoogle Scholar
  13. 13.
    Perez-Gonzalez, F.: The Importance of Aliasing in Structured Quantization Index Modulation Data Hiding. In: Kalker, T., Cox, I., Ro, Y.M. (eds.) IWDW 2003. LNCS, vol. 2939, pp. 1–17. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  14. 14.
    Petitcolas, F.A.P.: Watermarking schemes evaluation. IEEE Trans. Signal Process. 17(5), 58–64 (2000)CrossRefGoogle Scholar
  15. 15.
    Petitcolas, F.A.P., Steinebach, M., Raynal, F., Dittmann, J., Fontaine, C., Fatès, N.: A public automated web-based evaluation service for watermarking schemes: StirMark Benchmark. In: Proc. of electronic imaging, security and watermarking of multimedia contents III, San Jose, vol. 4314, pp. 20–26 (2001)Google Scholar
  16. 16.
    Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Trans. on Image Process. 13(4), 600–612 (2004)CrossRefGoogle Scholar
  17. 17.
    Zamir, R., Shamai, S., Erez, U.: Nested linear/lattice codes for structured multiterminal binning. IEEE Trans. Inf. Theory 48(6), 1250–1276 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Zhang, Q., Boston, N.: Quantization Index Modulation using the E 8 lattice. In: Proc. of the 41th Annual Allerton Conference on Communication, Control and Computing (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Dieter Bardyn
    • 1
  • Ann Dooms
    • 1
  • Tim Dams
    • 1
    • 2
  • Peter Schelkens
    • 1
  1. 1.Dept. of Electronics and Informatics (ETRO)Vrije Universiteit Brussel (VUB), Interdisciplinary Institute for Broadband Technology (IBBT)BrusselsBelgium
  2. 2.Dept. of Applied Engineering (electronica-ict)Artesis University College of AntwerpAntwerpBelgium

Personalised recommendations