Skip to main content
Log in

Robust and secure fractional wavelet image watermarking

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

This paper presents an efficient fractional wavelet transform (FWT) image watermarking technique based on combining the discrete wavelet transform (DWT) and the fractional Fourier transform (FRFT). In the proposed technique, the host image is wavelet transformed with two resolution levels, and then, the middle frequency sub-bands are FRFT transformed. The watermark is hidden by altering the selected FRFT coefficients of the middle frequency sub-bands of the 2-level DWT-transformed host image. Two pseudo-random noise (PN) sequences are used to modulate the selected FRFT coefficients with the watermark pixels, and inverse transforms are finally applied to get the watermarked image. In watermark extraction, we just need the same two PN sequences used in the embedding process and the watermark size. The correlation factor is used to determine whether the extracted pixel is one or zero. The proposed fractional wavelet transform (FWT) image watermarking method is tested with different image processing attacks and under composite attacks to verify its robustness. Experimental results demonstrated improved robustness and security.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Miyazaki, A.: A study on the best wavelet filter bank problem in the wavelet-based image watermarking. In: 18th European Conference on Circuit Theory and Design, ECCTD, pp. 184–187 (2007)

  2. Brannock, E., Weeks, M., Harrison, R.: Watermarking with wavelets: simplicity leads to robustness. In: Proceedings of the IEEE Southeast Conference 2008, Huntsville, Alabama, April 3–6, pp. 587–592 (2008)

  3. Djurovic, I., Stankovic, S., Pitas, I.: Digital watermarking in the fractional Fourier transformation domain. J. Netw. Comput. Appl. 24(2), 167–173 (2001)

  4. Yu, F.Q., Zhang, Z. K., Xu, M.H.: A digital watermarking algorithm for image based on fractional Fourier transform. In: 2006 1ST IEEE Conference on Industrial Electronics and Applications, IEEE (2006)

  5. Hussain, F., Khan, E., Farooq, O.: Embedding and non-blind extraction of watermark data in images in FRFT domain. In: International Conference on Multimedia, Signal Processing, and Communication Technologies 14–16 March, pp. 280–283 (2009)

  6. Elshazly, Ehab H., Ashour, Mahmoud A., El-Rabaie, El-sayed M., Abbas, Alaa M., Kazemian, H.: An efficient fractional fourier transform approach for digital image watermarking. In: Proceeding of National Radio Science Conference NRSC (2012)

  7. Pujara, Chirag, Bhardwaj, Ashok, Gadre, Vikram M.: Secured watermarking in fractional wavelet domains. IETE J. Res. 53(6), 573–580 (2007)

    Article  Google Scholar 

  8. Dietze, M., Jassim, S.: Filters ranking for DWT domain robust digital watermarking. EURASIP J. Appl. Signal Process. 2004, 2093–2101 (2004)

  9. Tao, P., Eskicioglu, A.M.: A robust multiple watermarking scheme in the DWT Domain. In: Optics East 2004 Symposium, Internet Multimedia Management Systems V Conference, Philadelphia, PA, pp. 133–144, October 25–28 (2004)

  10. Tcheslavski, G.V.: Wavelets Fundamentals. http://ee.lamar.edu/gleb/dip/index.htm, April (2008)

  11. Ozaktas, M.H., Arikan, O.: Digital computation of the fractional fourier transform. IEEE Transactions on Signal Processing 9, 2141–2149 (1996)

    Article  Google Scholar 

  12. Elhoseny, H.M., Ahmed, H.E.H., Abbas, A.M., Kazemian, H.B., Faragallah, O.S., El-Rabaie, S.M., Abd El-Samie, F.E.: Chaotic encryption of images in the fractional Fourier transform domain using different modes of operation. Signal Image Video Process. J. (2013). doi:10.1007/s11760-013-0490-x. Springer

  13. Pei, S.C., Yeh, M.H.: Two dimensional discrete fractional fourier transform. Signal Process. 67, 99–108 (1998)

    Article  MATH  Google Scholar 

  14. Bhatnagar, G., Raman, B.: A new SVD based watermarking framework in fractional Fourier domain. Contemp. Comput. IC3(1), 107–118 (2010)

  15. Ejima, M., Myazaki, A.: On the evaluation of performance of digital watermarking in the frequency domain. In: Proceedings of the IEEE International Conference on Image Processing, pp. 546–549 (2001)

  16. Aboshosha, A., Hassan, M., Ashour, M., El Mashade, M.: Image denoising based on spatial filters, an analytical study. In: ICCES09, Cairo, Egypt (2009)

  17. Voloshynovskiy, S., Pereira, S., Pun, T.: Attacks on digital watermarks: classification, estimation-based attacks, and benchmarks. Comm. Mag. 39(8), 118–126 (2001)

    Article  Google Scholar 

  18. Sheng Xie, R., Zhou, M., Huang, C., Li, Y.: Anti-geometrical attacks image watermarking scheme based on template watermark. In: Proceedings of Computer Network and Multimedia Technology, CNMT, pp. 1–4 (2009)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Osama S. Faragallah.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elshazly, E.H., Faragallah, O.S., Abbas, A.M. et al. Robust and secure fractional wavelet image watermarking. SIViP 9 (Suppl 1), 89–98 (2015). https://doi.org/10.1007/s11760-014-0684-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-014-0684-x

Keywords

Navigation