Significant Pixel Watermarking Using Human Visual System Model in Wavelet Domain

  • M. Jayalakshmi
  • S. N. Merchant
  • U. B. Desai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4338)


In this paper, we propose a novel algorithm for robust image watermarking by inserting a single copy of the watermark. Usually, robustness is achieved by embedding multiple copies of the watermark.The proposed method locates and watermarks ‘significant pixels’ of the image in the wavelet domain. Here, the amount of distortion at every pixel is kept within the threshold of perception by adopting ideas from Human Visual System (HVS) model. The robustness of the proposed method was verified under six different attacks. To verify the advantage of selecting the significant pixels over the highest absolute coefficients, simulations were performed under both cases with quantization of pixels as per HVS model. Simulation results show the advantage of selecting the ‘significant pixels’ for watermarking gray images as well as color images.


Discrete Wavelet Transform Watermark Image Watermark Scheme JPEG Compression Digital Watermark 


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  1. 1.
    Wolfgang, R.B., Delp, E.J.: A watermark for digital images. In: Proceedings of IEEE Int. Conf. Image proc., vol. 3, pp. 219–222 (1996)Google Scholar
  2. 2.
    Wolfgang, R., Delp, E.J.: Fragile watermarking using the vw2d watermark. In: Proceedings of SPIE, vol. 3228, pp. 297–308 (1997)Google Scholar
  3. 3.
    Ruanaidh, J.J.K.O., Dowling, W.J., Boland, F.M.: Phase watermarking of digital images. In: Proc. Int. Conf. Image Processing, vol. 3, pp. 239–242 (1996)Google Scholar
  4. 4.
    Hsu, C.T., Wu, J.L.: Hidden signatures in images. In: Proc. Int. Conf. Image Processing, vol. 3, pp. 223–226 (1996)Google Scholar
  5. 5.
    Kundur, D., Hatzinakos, D.: A robust digital image watermarking scheme using wavelet based fusion. In: Proceedings of IEEE Int. Conf. Image proc., pp. 544–547 (1997)Google Scholar
  6. 6.
    Inoue, H., Miyazaki, A., Yamamoto, A., Katsura, T.: A digital watermark based on wavelet transform and its robustness on image compression and transformation. IEICE Trans. Fund. Electron., Commun., Comput. Sci. E82-A, 2–10 (1999)Google Scholar
  7. 7.
    Xia, X., Boncelet, C.J., Arce, G.R.: A multiresolution watermark for digital images. In: Proceedings of IEEE Int. Conf. Image Proc., pp. 548–551 (1997)Google Scholar
  8. 8.
    Alghoniemy, M., Tewfik, A.H.: Geometric invariance in image watermarking. IEEE Trans. Image Proc. 13, 145–153 (2004)CrossRefGoogle Scholar
  9. 9.
    Barnii, M., Bartolini, F., Piva, A.: Improved wavelet based watermarking through pixel-wise masking. IEEE Trans. Image Proc. 10, 470–477 (2001)CrossRefGoogle Scholar
  10. 10.
    Lewis, A.S., Knowles, G.: Image compression using 2-d wavelet transform. IEEE Trans. Image Proc. 1, 244–250 (1992)CrossRefGoogle Scholar
  11. 11.
    Kundur, D., Hatzinakos, D.: Towards robust logo watermarking using multiresolution image fusion principles. IEEE Trans. Multimedia 6, 185–198 (2004)CrossRefGoogle Scholar
  12. 12.
    Tian, Q., Sebe, N., Lew, M.S., Loupias, E., Huang, T.S.: Content-based image retrieval using wavelet-based salient points. In: Proceedings of SPIE, vol. 4315, pp. 425–436 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • M. Jayalakshmi
    • 1
  • S. N. Merchant
    • 1
  • U. B. Desai
    • 1
  1. 1.SPANN Lab, Electrical Engineering DepartmentIndian Institute of TechnologyBombay, Powai

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