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A reversible water marking algorithm for multimedia images using two-dimensional non-causal prediction and ESPVD

  • Yongjie TanEmail author
  • Jie Qin
Article
  • 22 Downloads

Abstract

Reversible image watermarking algorithm is an important branch of information hiding, which can protect the integrity of data. Therefore, it is of great practical significance and practical value to study the reversible image water marking algorithm. A multimedia image watermarking algorithm based on two-dimensional non-causal prediction and edge based sorted pixel value difference (ESPVD) is proposed in this paper, which is used to protect the security of multimedia information. Firstly, the optimum prediction coefficients in the horizontal and vertical directions of image are calculated. Then, two-dimensional non-causal prediction of image is carried out according to raster scanning sequence, and prediction pixels and prediction errors are calculated. Finally, the morphological edge (ME) operator is used to identify edge pixel positions, and the ESPVD technology is used to embed the watermarking information. The experimental results show that the proposed algorithm has better performance than those of other image watermarking algorithms under the same embedding ability.

Keywords

Multimedia images Reversible water marking algorithm Morphological edge (ME) Two-dimensional non-causal prediction Edge based sorted pixel value difference (ESPVD) 

Notes

Acknowledgements

This work is supported by the Natural Science Foundation of China (No. U1504613) and the Soft Science Research Project of Henan Intellectual Property Bureau (No. 20170106036).

References

  1. 1.
    Cao F, An B, Yao H et al (2019) Local complexity based adaptive embedding mechanism for reversible data hiding in digital images[J]. Multimed Tools Appl 78(7):7911–7926CrossRefGoogle Scholar
  2. 2.
    Dragoi IC, Coltuc D (2015) On local prediction based reversible watermarking[J]. IEEE Trans Image Process 24(4):1244–1246MathSciNetCrossRefGoogle Scholar
  3. 3.
    Dragoi IC, Coltuc D (2016) Adaptive pairing reversible watermarking [J]. IEEE Trans Image Process 25(5):2420–2422MathSciNetCrossRefGoogle Scholar
  4. 4.
    Elshazly AR, Nasr ME, Fouad MM et al (2017) High payload multi-channel dual audio watermarking algorithm based on discrete wavelet transform and singular value decomposition[J]. Int J Speech Technol 20:1): 1–1): 8CrossRefGoogle Scholar
  5. 5.
    Gul E, Ozturk S (2019) A novel hash function based fragile watermarking method for image integrity[J]. Multimed Tools Appl 78(13):17701–17718CrossRefGoogle Scholar
  6. 6.
    Haribabu M, Bindu CH, Swamy KV (2016) A Secure & Invisible Image Watermarking Scheme Based on wavelet transform in HSI color space [J]. Procedia Comput Sci 93:462–468CrossRefGoogle Scholar
  7. 7.
    Hsu LY, Hu HT (2015) Blind image watermarking via exploitation of inter-block prediction and visibility threshold in DCT domain[J]. J Vis Commun Image Represent 32(C):130–143CrossRefGoogle Scholar
  8. 8.
    Jiang L, Wang J, Jiang H et al (2018) Prediction model of port throughput based on game theory and multimedia Bayesian regression[J]. Multimed Tools Appl 78(4):4397–4416CrossRefGoogle Scholar
  9. 9.
    Kumar A, Cheruku DR, Chanamallu SR et al (2016) Digital watermarking approach based on edge based sorted pixel value difference (ESPVD) [J]. Indian J Sci Technol 9(S1):100706CrossRefGoogle Scholar
  10. 10.
    Li X, Zhang W, Gui X et al (2017) Efficient reversible data hiding based on multiple histograms modification[J]. IEEE T Inf Foren Sec 10(9):2016–2027Google Scholar
  11. 11.
    Pakdaman Z, Saryazdi S, Nezamabadi-Pour H (2016) A prediction based reversible image watermarking in Hadamard domain[J]. Multimed Tools Appl 76(6):1–29Google Scholar
  12. 12.
    Qin C, Ji P, Wang J et al (2017) Fragile image watermarking scheme based on VQ index sharing and self-embedding[J]. Multimed Tools Appl 76(2):2267–2287CrossRefGoogle Scholar
  13. 13.
    Rahmani P, Dastghaibyfard G (2018) Two reversible data hiding schemes for VQ-compressed images based on index coding[J]. IET Image Process 12(7):1195–1203CrossRefGoogle Scholar
  14. 14.
    Roy A, Laskar RH (2019) Fuzzy SVM based fuzzy adaptive filter for denoising impulse noise from color images[J]. Multimed Tools Appl 78(2):1785–1804CrossRefGoogle Scholar
  15. 15.
    Sakthivel SM, Sankar AR (2018) An ASIC based invisible watermarking of grayscale images using pixel value search algorithm (PVSA)[J]. Multimed Tools Appl 78:4): 1–4):27Google Scholar
  16. 16.
    Shu-Zhi LI, Qin HU, Deng XH (2017) Reversible image watermarking based on gray level co-occurrence matrix texture feature selection clock[J]. J Optoe Laser 28(4):411–418Google Scholar
  17. 17.
    Ustubioglu A, Ulutas G, Ustubioglu B (2019) IWT-MDE based reversible thermal image watermarking enhanced with secret sharing mechanism[J]. Multimed Tools Appl 78:8): 1–8):31CrossRefGoogle Scholar
  18. 18.
    Wu HT, Huang J (2012) Reversible image watermarking on prediction errors by efficient histogram modification[J]. Signal Process 92(12):3000–3009CrossRefGoogle Scholar
  19. 19.
    Xiang Y, Xiang W, Pei Q (2018) Reversible watermarking based on multi-dimensional prediction-error expansion[J]. Multimed Tools Appl 77(14):18085–18104CrossRefGoogle Scholar
  20. 20.
    Zhang XP, Long J (2016) Lossless and reversible data hiding in encrypted images with public-key cryptography[J]. IEEE T Circ Syst Vid 26(9):1622–1631MathSciNetCrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyZhoukou Normal UniversityZhoukouChina

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