A block-based RDWT-SVD image watermarking method using human visual system characteristics

  • Ferda Ernawan
  • Muhammad Nomani Kabir
Original Article


With the rapid growth of internet technology, image watermarking method has become a popular copyright protection method for digital images. In this paper, we propose a watermarking method based on \(4\times 4\) image blocks using redundant wavelet transform with singular value decomposition considering human visual system (HVS) characteristics expressed by entropy values. The blocks which have the lower HVS entropies are selected for embedding the watermark. The watermark is embedded by examining \(U_{2,1}\) and \(U_{3,1}\) components of the orthogonal matrix obtained from singular value decomposition of the redundant wavelet transformed image block where an optimal threshold value based on the trade-off between robustness and imperceptibility is used. In order to provide additional security, a binary watermark is scrambled by Arnold transform before the watermark is embedded into the host image. The proposed scheme is tested under various image processing, compression and geometrical attacks. The test results are compared to other watermarking schemes that use SVD techniques. The experimental results demonstrate that our method can achieve higher imperceptibility and robustness under different types of attacks compared to existing schemes. Our method provides high robustness especially under image processing attacks, JPEG2000 and JPEG XR attacks. It has been observed that the proposed method achieves better performance over the recent existing watermarking schemes.


Image watermarking Arnold transform Human visual characteristics Redundant wavelet transform Singular value decomposition 



We sincerely thank Universiti Malaysia Pahang, Malaysia, for providing financial support for this work through UMP Research Grant Scheme (RDU180358).


  1. 1.
    Lin, C.-H., Chao, M.-W., Liang, C.-Y., Lee, T.-Y.: A novel semi-blind-and-semi-reversible robust watermarking scheme for 3D polygonal models. Vis. Comput. 26(6–8), 1101–1111 (2010)CrossRefGoogle Scholar
  2. 2.
    Wang, J., Feng, J., Miao, Y.: A robust confirmable watermarking algorithm for 3D mesh based on manifold harmonics analysis. Vis. Comput. 28(11), 1049–1062 (2011)CrossRefGoogle Scholar
  3. 3.
    Lee, H., Dikici, Ç., Lavoué, G.: Joint reversible watermarking and progressive compression of 3D meshes. Vis. Comput. 27(6–8), 781–792 (2011)CrossRefGoogle Scholar
  4. 4.
    Cao, L., Men, C., Ji, R.: Nonlinear scrambling-based reversible watermarking for 2D-vector maps. Vis. Comput. 29(3), 231–237 (2013)CrossRefGoogle Scholar
  5. 5.
    Su, Q.T., Wang, G., Jia, S.L., Zhang, X.F., Liu, Q.M., Liu, X.X.: Embedding color image watermark in color image based on two-level DCT. SIViP 9(5), 991–1007 (2015)CrossRefGoogle Scholar
  6. 6.
    Keshavarzian, R., Aghagolzadeh, A.: ROI based robust and secure image watermarking using DWT and Arnold map. AEU Int. J. Electron. Commun. 70(3), 278–288 (2016)CrossRefGoogle Scholar
  7. 7.
    Fazli, S., Moeini, M.: A robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric attacks. Opt. Int. J. Light Electron Opt. 127(2), 964–972 (2016)CrossRefGoogle Scholar
  8. 8.
    Ansari, I.A., Pant, M., Ahn, C.W.: Robust and false positive free watermarking in IWT domain using SVD and ABC. Eng. Appl. Artif. Intell. 49, 114–125 (2016)CrossRefGoogle Scholar
  9. 9.
    Purohit, N., Chennakrishna, M., Manikantan, K.: Novel digital image watermarking in SWT+SVD domain. In: Proceedings of the International Conference on Signal, Networks, Computing, and Systems. Lecture Notes in Electrical Engineering, vol. 395, pp. 13–23 (2017)Google Scholar
  10. 10.
    Lagzian S., Soryani M., Fathy M.: Robust watermarking scheme based on RDWT-SVD: Embedding data in all subbands. In: International Symposium on Artificial Intelligence and Signal Processing (AISP), pp. 48–52 (2011)Google Scholar
  11. 11.
    Ling, H.-C., Phan, R.C.-W., Heng, S.-H.: Comment on "Robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition". Int. J. Electron. Commun. 67(10), 894–897 (2013)CrossRefGoogle Scholar
  12. 12.
    Yavuza, E., Telatarb, Z.: Comments on "A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm". Digit. Signal Proc. 23(4), 1335–1336 (2013)CrossRefGoogle Scholar
  13. 13.
    Zhang, X.-P., Li, K.: Comments on "An SVD-based watermarking scheme for protecting rightful ownership". IEEE Trans. Multimed. 7(3), 593–594 (2015)CrossRefGoogle Scholar
  14. 14.
    Chang, C.C., Tsai, P., Lin, C.C.: SVD-based digital image watermarking scheme. Pattern Recognit. Lett. 26(10), 1577–1586 (2005)CrossRefGoogle Scholar
  15. 15.
    Chung, K.L., Yang, W.N., Huang, Y.H., et al.: On SVD-based watermarking algorithm. Appl. Math. Comput. 188(1), 54–57 (2007)MathSciNetzbMATHGoogle Scholar
  16. 16.
    Fan, M.Q., Wang, H.X., Li, S.K.: Restudy on SVD-based watermarking scheme. Appl. Math. Comput. 203(2), 926–930 (2008)MathSciNetzbMATHGoogle Scholar
  17. 17.
    Lai, C.C.: An improved SVD-based watermarking scheme using human visual characteristics. Opt. Commun. 284(4), 938–944 (2011)CrossRefGoogle Scholar
  18. 18.
    Makbol, N.M., Khoo, B.E., Rassem, T.H.: Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics. IET Image Proc. 10(1), 34–52 (2016)CrossRefGoogle Scholar
  19. 19.
    Makbol, N.M., Khoo, B.E.: Robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition. Int. J. Eletron. Commun. (AEÜ) 67(2), 102–112 (2013)CrossRefGoogle Scholar
  20. 20.
    Zhang, X.P., Li, K.: Comments on "An SVD-based watermarking scheme for protecting rightful ownership". IEEE Trans. Multimed. 7(3), 593–594 (2005)CrossRefGoogle Scholar
  21. 21.
    Rykaczewski, R.: Comments on "An SVD-based watermarking scheme for protecting rightful ownership". IEEE Trans. Multimed. 9(2), 421–423 (2007)CrossRefGoogle Scholar
  22. 22.
    Liu, R., Tan, T.: An SVD-based watermarking scheme for protecting rightful ownership. IEEE Trans. Multimed. 4(1), 121–128 (2002)CrossRefGoogle Scholar
  23. 23.
    Lai, C.C., Tsai, C.C.: Digital image watermarking using discrete wavelet transform and singular value decomposition. IEEE Trans. Instrum. Meas. 59(11), 3060–3063 (2010)CrossRefGoogle Scholar
  24. 24.
    Hien, T.D., Nakao, Z., Chen, Y.-W.: RDWT domain watermarking based on independent component analysis extraction. Adv. Soft Comput. 34, 401–414 (2006)CrossRefGoogle Scholar
  25. 25.
    Zhang, H., Wang, C., Zhou, X.: A robust image watermarking scheme based on SVD in the spatial domain. Future Internet 9(45), 1–16 (2017)Google Scholar
  26. 26.
    Gao, L., Gao, T., Zha, J.: Reversible watermarking in medical image using RDWT and sub-sample. Int. J. Digital Crime Forensics (IJDCF) 7(4), 1–18 (2015)CrossRefGoogle Scholar
  27. 27.
    Lagzian, S., Soryani, M., Fathy, M.: A new robust watermarking scheme based on RDWT-SVD. Int. J. Intell. Inf. Process. 2(1), 22–29 (2011)Google Scholar
  28. 28.
    Rassem, T.H., Makbol, N.M., Khoo, B.E.: Performance evaluation of RDWT-SVD and DWT-SVD watermarking schemes. AIP Conf. Proc. 1774(050021), 1–9 (2016)Google Scholar
  29. 29.
    Liu, Z.J., Xu, L., Liu, T., Chen, H., Li, P.F., Lin, C., Liu, S.T.: Color image encryption by using Arnold transform and color-blend operation in discrete cosine transform domains. Opt. Commun. 284(1), 123–128 (2011)CrossRefGoogle Scholar
  30. 30.
    Chen, W., Quan, C., Tay, C.J.: Optical color image encryption based on Arnold transform and interference method. Opt. Commun. 282(18), 3680–3685 (2009)CrossRefGoogle Scholar
  31. 31.
    Deng, X.P., Zhao, D.M.: Color component 3D Arnold transform for polychromatic pattern recognition. Opt. Commun. 284(24), 5623–5629 (2011)CrossRefGoogle Scholar
  32. 32.
    Liu, Z.J., Gong, M., Dou, Y.K., Liu, F., Lin, S., Ahmad, M.A., Dai, J.M., Liu, S.T.: Double image encryption by using Arnold transform and discrete fractional angular transform. Opt. Lasers Eng. 50(2), 248–255 (2012)CrossRefGoogle Scholar
  33. 33.
    Basso, A., Bergadano, F., Cavagnino, D., Pomponiu, V., Vernone, A.: A novel block-based watermarking scheme using the SVD transform. Algorithms 2(1), 46–75 (2009)CrossRefGoogle Scholar
  34. 34.
    Ernawan, F., Abu, N.A., Suryana, N.: Adaptive tchebichef moment transform image compression using psychovisual model. J. Comput. Sci. 9(6), 716–725 (2013)CrossRefGoogle Scholar
  35. 35.
    Ernawan, F., Abu, N.A., Suryana, N.: An adaptive JPEG image compression using psychovisual model. Adv. Sci. Lett. 20(1), 026–031 (2014)CrossRefGoogle Scholar
  36. 36.
    Abu, N.A., Ernawan, F.: Psychovisual threshold on large Tchebichef moment for image compression. Appl. Math. Sci. 8, 6951–6961 (2014)Google Scholar
  37. 37.
    Ernawan, F., Nugraini, S.H.: The optimal quantization matrices for JPEG image compression from psychovisual threshold. J. Theor. Appl. Inf. Technol. 70(3), 566–572 (2014)Google Scholar
  38. 38.
    Ernawan, F., Abu, N.A., Suryana, N.: An optimal tchebichef moment quantization using psychovisual threshold for image compression. Adv. Sci. Lett. 20(1), 070–074 (2014)CrossRefGoogle Scholar
  39. 39.
    Ernawan, F., Mustaffa, Z., Aji, L.B.: An efficient image compression using bit allocation based on psychovisual threshold. Information (Japan) 9(9B), 4177–4182 (2016)Google Scholar
  40. 40.
    Ernawan, F., Kabir, M.N., Zain, J.M.: Bit allocation strategy based on psychovisual threshold in image compression. Multimed. Tools. Appl. 77(11), 13923–13946 (2018)CrossRefGoogle Scholar
  41. 41.
    Ernawan, F., Kabir, N., Zamli, K.Z.: An efficient image compression technique using Tchebichef bit allocation. Opt. Int. J. Light Electron Opt. 148, 106–119 (2017)CrossRefGoogle Scholar
  42. 42.
    Abu, N.A., Ernawan, F., Suryana, N., Sahib, S.: Image watermarking using psychovisual threshold over the edge. Inf. Commun. Technol. 7804, 519–527 (2013)Google Scholar
  43. 43.
    Ernawan, F.: Robust image watermarking based on psychovisual threshold. J. ICT Res. Appl. 10(3), 228–242 (2016)CrossRefGoogle Scholar
  44. 44.
    Ernawan, F., Kabir, M.N., Fadli, M., Mustaffa, Z.: Block-based Tchebichef image watermarking scheme using psychovisual threshold. In: International Conference on Science and Technology-Computer (ICST), 27–28 October, pp. 6–10 (2016)Google Scholar
  45. 45.
    Ernawan, F., Ramalingam, M., Sadiq, A.S., Mustaffa, Z.: An improved imperceptibility and robustness of \(4\times 4\) DCT-SVD image watermarking using modified entropy. J. Telecommun. Electron. Comput. Eng. 9, 111–116 (2017)Google Scholar
  46. 46.
    Ernawan, F., Liew, S.C., Mustaffa, Z., Moorthy, K.: A blind multiple watermarks based on human visual characteristics. Int. J. Electr. Comput. Eng. (in press)Google Scholar
  47. 47.
    Ernawan, F., Kabir, M.N.: A robust image watermarking technique with an optimal DCT-psychovisual threshold. IEEE Access 6, 20464–20480 (2018)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Computer Systems and Software EngineeringUniversiti Malaysia PahangGambang, KuantanMalaysia

Personalised recommendations