An Angle QIM Watermarking in STDM Framework Robust against Amplitude Scaling Distortions

  • Vijay Harishchandra Mankar
  • Tirtha Sankar Das
  • Subir Kumar Sarkar
Part of the Communications in Computer and Information Science book series (CCIS, volume 40)


Quantization index modulation (QIM) watermarking proposed by Chen and Wornell provides computational efficient blind watermarking based on Costa’s dirty paper codes. The limitation of this is its vulnerability against amplitude scaling distortion. The present work is proposed to solve this problem based on angle QIM within spread transform dither modulation (STDM) framework. AQIM embeds the information by quantizing the angle formed by the host-signal vector with respect to the origin of a hyperspherical coordinate system as opposed to quantizing the amplitude of pixel values. It has been shown experimentally that the proposed work not only provides the resistance against this valumetric scaling distortion but also against non-linear, gamma correction and constant luminance change.


Quantization index modulation (QIM) STDM watermarking angle QIM valumetric scaling gamma correction 


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  1. 1.
    Moulin, P., O’Sullivan, J.A.: Information-theoretic analysis of information hiding. IEEE Trans. Inf. Theory 49(3), 563–593 (2003)CrossRefGoogle Scholar
  2. 2.
    Chen, B., Wornell, G.: Quantization index modulation: A class of provably good methods for digital watermarking and information embedding. IEEE Trans. Inf. Theory 47, 1423–1443 (2001)CrossRefGoogle Scholar
  3. 3.
    Gel’fand, S.I., Pinsker, M.S.: Coding for channel with random parameters. Prob. Contr. Inf. Theory 9, 19–31 (1980)Google Scholar
  4. 4.
    Costa, M.H.: Writing on dirty paper. IEEE Trans. Inf. Theory IT-29(3), 439–441 (1983)CrossRefGoogle Scholar
  5. 5.
    Conway, J.H., Sloane, N.J.A.: Sphere Packings, Lattices and Groups, 3rd edn. Springer, Berlin (1999)CrossRefGoogle Scholar
  6. 6.
    Miller, M.L., Doerr, G.J., Cox, J.: Dirty-paper trellis codes for watermarking. In: IEEE Int. Conf. Image Process, Rochester, NY, September 2002, vol. 2, pp. 129–132 (2002)Google Scholar
  7. 7.
    Bradley, B.: Improvement to CDF grounded lattice codes. In: Proc. SPIE Security, Steganography, Watermarking Multimedia Contents VI, vol. 5306 (January 2004)Google Scholar
  8. 8.
    Perez-Gonzalez, F., Mosquera, C., Barni, M., Abrardo, A.: Rational dither modulation: A high rate data-hiding method invariant to gain attacks. IEEE Trans. Signal Process. 53(10), 3960–3975 (2005)CrossRefGoogle Scholar
  9. 9.
    Eggers, J.J., Bauml, R., Girod, B.: Estimation of amplitude modifications before SCS watermark detection. In: Proc. SPIE Security Watermarking Multimedia Contents IV, San Jose, CA, January 2002, vol. 4675, pp. 387–398 (2002)Google Scholar
  10. 10.
    Shterev, I.D., Lagendijk, R.L.: Maximum likelihood amplitude scale estimation for quantization-based watermarking in the presence of dither. In: Proc. SPIE Security, Steganography, Watermarking Multimedia Contents VII (January 2005)Google Scholar
  11. 11.
    Shterev, I.D., Lagendijk, R.L., Heusdens, R.: Statistical amplitude scale estimation for quantization-based watermarking. In: SPIE Security, Steganography, Watermarking Multimedia Contents VI, vol. 5306 (January 2004)Google Scholar
  12. 12.
    Lee, K., Kim, D.S., Kim, T., Moon, K.A.: EM estimation of scale factor for quantization-based audio watermarking. In: Int. Workshop Digital Watermarking, Seoul, Korea (October 2003)Google Scholar
  13. 13.
    Balado, F., Whelan, K.M., Silvestre, G.C.M., Hurley, N.J.: Joint iterative decoding and estimation for side-informed data hiding. IEEE Trans. Signal Process. 53(10), 4006–4019 (2005)CrossRefGoogle Scholar
  14. 14.
    Schuchman, L.: Dither signals and their effect on quantization noise. IEEE Trans. Commun. Technol. COM-12(4), 162–165 (1964)CrossRefGoogle Scholar
  15. 15.
    Oostveen, J., Kalker, T., Staring, M.: Adaptive quantization watermarking. In: Proceedings of SPIE –IS&T Electronic Imaging, vol. 5306, pp. 296–303 (2004)Google Scholar
  16. 16.
    Ourique, F., Licks, V., Jordan, R., Perez-Gonzalez, F.: Angle QIM: A novel watermark embedding scheme robust against amplitude scaling distortions. In: International Conference on Acoustics, Speech, and Signal Processing, pp. 797–800 (2005)Google Scholar
  17. 17.
    Chen, B.: Design and Analysis of Digital Watermarking, Information Embedding, and Data Hiding Systems, PhD Thesis, Massachusetts Institute of Technology, Massachusetts, USA (June 2000)Google Scholar
  18. 18.
    Li, Q., Cox, I.J.: Using perceptual models to improve fidelity and provide invariance to valumetric scaling for quantization index modulation watermarking. Presented at the IEEE Int. Conf. Acoustics, Speech and Signal Processing, Philadelphia, PA (March 2005)Google Scholar
  19. 19.
    Cox, I.J., Miller, M.L., McKellips, A.: Watermarking as communications with side information. Proc. IEEE 87(7), 1127–1141 (1999)CrossRefGoogle Scholar
  20. 20.
    Moulin, P., Koetter, R.: Data-Hiding Codes. Proceedings of the IEEE 93(12) (December 2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Vijay Harishchandra Mankar
    • 1
  • Tirtha Sankar Das
    • 1
  • Subir Kumar Sarkar
    • 1
  1. 1.Dept. of Electronics and TelecommunicationJadavpur UniversityKolkataIndia

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