Multimedia Tools and Applications

, Volume 78, Issue 22, pp 31847–31865 | Cite as

Reversible robust data hiding based on wavelet filters modification

  • Sasan Golabi
  • Mohammad Sadegh HelfroushEmail author
  • Habibollah Danyali


In this paper, a new robust reversible data hiding method is proposed. The method is designed based on wavelet modifications which result in a scalable data hiding scheme. The well-known biorthogonal wavelets are modified according to the watermarking bits. This is done in a way that the embedded bit can easily be interpreted based on the wavelet coefficients of the watermarked image and regardless of its resolution. Following such an algorithm would result in both reversibility and robustness. The proposed method is especially robust against wavelet resolution changing attacks and DWT based compressions. This can be of high value when dealing with low bandwidth communication situations. The practical results show high robustness against signal processing attacks and high PSNR and capacity in lossless scenarios.


Watermarking Steganography Digital wavelet transform Jpeg2000 Scalable data hiding 



  1. 1.
    Borah A, Borah B (2015) A Spatial Domain Reversible Visible Watermarking Technique for Textured Images. Int J Comput Appl 129(14):28–35Google Scholar
  2. 2.
    Campisi P, Egiazarian K (Eds.) (2016) Blind image deconvolution: theory and applications. CRC Press, Taylor and Francis GroupGoogle Scholar
  3. 3.
    Celik M, Sharma G, Tekalp AM, Saber E (2002) Reversible data hiding. International Conference on Image Processing 2002, RochesterCrossRefGoogle Scholar
  4. 4.
    Cherian J, Mereena AT (2016) A Survey on DWT and LWT based Digital Image Watermarking. International Journal of Research in Computer Applications & Information Technology 4(3):27–32Google Scholar
  5. 5.
    Cohen A, Daubechies I, Feauveau J-C (1992) Biorthogonal bases of compactly supported wavelets. Commun Pure Appl Math 45(5):485–560MathSciNetCrossRefGoogle Scholar
  6. 6.
    Daubechies, Ingrid. Ten lectures on wavelets. Society for industrial and applied mathematics, 1992.CrossRefGoogle Scholar
  7. 7.
    De Vleeschouwer C, Delaigle JF, Macq B (March 2003) Circular interpretation of bijective transformations in lossless watermarking for media asset management. IEEE Tran Multimedia 5:97–105CrossRefGoogle Scholar
  8. 8.
    Dong P et al (2005) Digital watermarking robust to geometric distortions. IEEE Trans Image Process 14(12):2140–2150CrossRefGoogle Scholar
  9. 9.
    Feng H-C, Marcellin MW, Bilgin A (2015) A methodology for visually lossless JPEG2000 compression of monochrome stereo images. IEEE Trans Image Process 24(2):560–572MathSciNetCrossRefGoogle Scholar
  10. 10.
    Fridrich J, Goljan M, Du R (2002) Lossless data embedding-new paradigm in digital watermarking. Eur Assoc Signal Process J Appl Signal Process 2002(2):185–196zbMATHGoogle Scholar
  11. 11.
    Goljan M, Fridrich JJ, Rui D (2001) Distortion-free data embedding for images. In: International Workshop on Information Hiding. Springer, Berlin, HeidelbergGoogle Scholar
  12. 12.
    Honsinger CW, Jones PW, Rabbani M, Stoffel JC (2001) Lossless recovery of an original image containing embedded data. US Patent 6(278):791Google Scholar
  13. 13.
    Katzenbeisser S, Petitcolas F (2016) Information Hiding-techniques for steganography and digital watermarking. Artech house, Norwoord Artech House, Inc. Norwood, MA, USAGoogle Scholar
  14. 14.
    Kozhemiakina N et al (2016) JPEG compression with recursive group coding. Electronic Imaging 2016(15):1–6CrossRefGoogle Scholar
  15. 15.
    Li X et al (2013) General framework to histogram-shifting-based reversible data hiding. IEEE Trans Image Process 22(6):2181–2191MathSciNetCrossRefGoogle Scholar
  16. 16.
    Liu F et al (2017) Visibility Thresholds in Reversible JPEG2000 Compression. Data Compression Conference (DCC), 2017. IEEEGoogle Scholar
  17. 17.
    Nasir I et al (2012) Robust image watermarking via geometrically invariant feature points and image normalisation. IET Image Process 6(4):354–363MathSciNetCrossRefGoogle Scholar
  18. 18.
    Newtson KA, Creusere CC (2017) Compressed imagery detection rate through map seeking circuit, and histogram of oriented gradient pattern recognition. Pattern Recognition and Tracking XXVIII. Vol. 10203. International Society for Optics and PhotonicsGoogle Scholar
  19. 19.
    Ni Z, Shi YQ, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circuits Syst Video Technol 16(3):354–362CrossRefGoogle Scholar
  20. 20.
    Ni Z et al (2006) Reversible data hiding. IEEE Transactions on Circuits and Systems for Video Technology 16(3):354–362CrossRefGoogle Scholar
  21. 21.
    Ni Z et al (2008) Robust lossless image data hiding designed for semi-fragile image authentication. IEEE Transactions on Circuits and Systems for Video Technology 18(4):497–509CrossRefGoogle Scholar
  22. 22.
    Oraintara S, Chen Y-J, Nguyen TQ (2002) Integer first Fourier transform. IEEE Transaction on Signal Processing 50(3):607–618CrossRefGoogle Scholar
  23. 23.
    Pathak S, Tiwari S, Agrawal S (2016) Digital Image Watermarking in wavelet domain using chaotic sequence. Futuristic Trends in Engineering, Science, Humanities, and Technology FTESHT 16:108Google Scholar
  24. 24.
    Peyré G (2009) A wavelet tour of signal processing: the sparse way. 3rd Academic Press, Inc. Orlando, FL, USAGoogle Scholar
  25. 25.
    Pla OG, Lin ET, Delp III EJ (2004) A wavelet watermarking algorithm based on a tree structure. Security, Steganography, and Watermarking of Multimedia Contents VI. Vol. 5306. International Society for Optics and PhotonicsGoogle Scholar
  26. 26.
    Rabbani M (2002) JPEG2000: Image compression fundamentals, standards and practice. Journal of Electronic Imaging 11(2):286CrossRefGoogle Scholar
  27. 27.
    Rao RSP, Rajesh Kumar P (2017) PSO Based Lossless and Robust Image Watermarking using Integer Wavelet Transform. Global Journal of Computer Science and TechnologyGoogle Scholar
  28. 28.
    Reddy MR et al (2017) Optimized watermarking technique using PCA-DWT and log filter. 2017 International Conference on Networks & Advances in Computational Technologies (NetACT), IEEEGoogle Scholar
  29. 29.
    Smith M, Collar B (2017) Region-of-interest encoding enhancements for variable-bitrate mezzanine compression. U.S. Patent No. 9,749,659. 29Google Scholar
  30. 30.
    Su Q, Chen B (2018) Robust color image watermarking technique in the spatial domain. Soft Comput 22(1):91–106MathSciNetCrossRefGoogle Scholar
  31. 31.
    Tang C-W, Hang H-M (2003) A feature-based robust digital image watermarking scheme. IEEE Trans Signal Process 51(4):950–959MathSciNetCrossRefGoogle Scholar
  32. 32.
    Thabit R, Khoo BE (2015) A new robust lossless data hiding scheme and its application to color medical images. Digital Signal Processing 38:77–94CrossRefGoogle Scholar
  33. 33.
    Tian H et al (2013) LDFT-based watermarking resilient to local desynchronization attacks. IEEE Transactions on Cybernetics 43(6):2190–2201CrossRefGoogle Scholar
  34. 34.
    Tsai J-S, Huang W-B, Kuo Y-H (2011) On the selection of optimal feature region set for robust digital image watermarking. IEEE Trans Image Process 20(3):735–743MathSciNetCrossRefGoogle Scholar
  35. 35.
    Vaishnav M, Kamargaonkar C, Sharma M (2017) Medical Image Compression Using Dual Tree Complex Wavelet Transform and Arithmetic Coding TechniqueGoogle Scholar
  36. 36.
    Wiseman Y (2015) The still image lossy compression standard-JPEG. Encyclopedia of Information Science and Technology, Third Edition. IGI Global, pp. 295–305Google Scholar
  37. 37.
    Xin CHEN (2015) JPEG2000 standard and its comparison with JPEG standard. Information Technology 4:037Google Scholar
  38. 38.
    Xuan G et al (2006) Lossless data hiding using histogram shifting method based on integer wavelets. International Workshop on Digital Watermarking. Springer, Berlin, HeidelbergGoogle Scholar
  39. 39.
    Zeng X-T, Ping L-D, Pan X-Z (2010) A lossless robust data hiding scheme. Pattern Recogn 43(4):1656–1667CrossRefGoogle Scholar
  40. 40.
    Zhu W, Xiong Z, Zhang Y-Q (1999) Multiresolution watermarking for images and video. IEEE Transactions on Circuits and Systems for Video Technology 9(4):545–550CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Sasan Golabi
    • 1
  • Mohammad Sadegh Helfroush
    • 1
    Email author
  • Habibollah Danyali
    • 1
  1. 1.Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran

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