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A Tunable Bound of the Embedding Level for Reversible Data Hiding with Contrast Enhancement

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Cloud Computing and Security (ICCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10039))

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Abstract

Recently, histogram modification based reversible data hiding (RDH) techniques are exploited to enhance the image contrast. To avoid overflow and underflow, the cover image has to be pre-processed by pre-shifting a number of the histogram bins at the lower and upper ends. When the payload size becomes large, a larger number of histogram bins has to be pre-shifted, and thus the image contrast may be over enhanced. As a result, human eye perceivable image degradation may appear in the over-sharpened image. To avoid image over-sharping, the just noticeable difference measurement is exploited to estimate the maximum number of pre-shiftable histogram bins. In addition, a tunable parameter is designed to balance between the visual degradation and the embedding capacity. The experimental result shows that the proposed work is effective in estimating the bound of embedding level.

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References

  1. Hsu, C.S., Tu, S.F.: Probability-based tampering detection scheme for digital images. Opt. Commun. 283(9), 1737–1743 (2010)

    Article  Google Scholar 

  2. Yang, H., Kot, A.C.: Binary image authentication with tampering localization by embedding cryptographic signature and Block Identifier. IEEE Signal Process. Lett. 13(12), 741–744 (2010)

    Article  Google Scholar 

  3. Thodi, D.M., Rodriguez, J.J.: Expansion embedding techniques for reversible watermarking. IEEE Trans. Image Process. 16(3), 721–730 (2007)

    Article  MathSciNet  Google Scholar 

  4. Sachnev, V., Kim, H.J., Nam, J., Suresh, S., Shi, Y.-Q.: Reversible watermarking algorithm using sorting and prediction. IEEE Trans. Circuits Syst. Video Technol. 19(7), 989–999 (2009)

    Article  Google Scholar 

  5. Li, X., Yang, B., Zeng, T.: Efficient reversible watermarking based on adaptive prediction-error expansion and pixel selection. IEEE Trans. Image Process. 20(12), 3524–3533 (2011)

    Article  MathSciNet  Google Scholar 

  6. Wu, H.-T., Huang, J.: Reversible image watermarking on prediction error by efficient histogram modification. Signal Process. 92(12), 3000–3009 (2012)

    Article  Google Scholar 

  7. Coatrieux, G., Le Guillou, C., Cauvin, J.M., Roux, C.: Reversible watermarking for knowledge digest embedding and reliability control in medical images. IEEE Trans. Inf. Technol. Biomed. 13(2), 158–165 (2009)

    Article  Google Scholar 

  8. Battisti, F., Carli, M., Neri, A.: Secure annotation for medical images based on reversible watermarking in the integer Fibonacci-Haar transform domain. In: Proceedings of SPIE EI, Image Processing: Algorithms and Systems IX, vol. 7870, pp. 78700G–78700G-10 (2011)

    Google Scholar 

  9. Fridrich, J., Goljan, M., Du, R.: Lossless data embedding for all image formats. In: Proceedings SPIE, vol. 4675, pp. 572–583 (2002)

    Google Scholar 

  10. Tian, J.: Reversible data embedding using a difference expansion. IEEE Trans. Circuits Syst. Video Technol. 13(8), 890–896 (2003)

    Article  Google Scholar 

  11. Hong, W., Chen, T.-S., Wu, M.-C.: An improved human visual system based reversible data hiding method using adaptive histogram modification. Opt. Commun. 291, 87–97 (2013)

    Article  Google Scholar 

  12. Ni, Z., Shi, Y.-Q., Ansari, N., Su, W.: Reversible data hiding. IEEE Trans. Circuits Syst. Video Technol. 16(3), 354–362 (2006)

    Article  Google Scholar 

  13. Hong, W., Chen, T.-S.: A local variance-controlled reversible data hiding method using prediction and histogram-shifting. J. Syst. Softw. 83(12), 2653–2663 (2010)

    Article  MathSciNet  Google Scholar 

  14. Li, X., Zhang, W., Gui, X., Yang, B.: A novel reversible data hiding scheme based on two-dimensional difference-histogram modification. IEEE Trans. Inf. Forensics Secur. 8(7), 1091–1100 (2013)

    Article  Google Scholar 

  15. Ou, B., Li, X., Zhao, Y., Ni, R., Shi, Y.-Q.: Pairwise prediction-error expansion for efficient reversible data hiding. IEEE Trans. Image Process. 22(12), 5010–5021 (2013)

    Article  MathSciNet  Google Scholar 

  16. Li, X., Zhang, W., Gui, X., Yang, B.: Efficient reversible data hiding based on multiple histograms modification. IEEE Trans. Inf. Forensics Secur. 10(9), 2016–2027 (2015)

    Article  Google Scholar 

  17. Hong, W., Chen, T.S., Chen, J.: Reversible data hiding using Delaunay triangulation and selective embedment. Inf. Sci. 308, 140–154 (2015)

    Article  MathSciNet  Google Scholar 

  18. Wu, H.-T., Dugelay, J.L., Shi, Y.-Q.: Reversible image data hiding with contrast enhancement. IEEE Signal Process. Lett. 22(1), 81–85 (2015)

    Article  Google Scholar 

  19. Wu, H.-T., Huang, J., Shi, Y.-Q.: Reversible data hiding method with contrast enhancement for medical images. J. Vis. Commun. Image Represent. 31, 146–153 (2015)

    Article  Google Scholar 

  20. Gao, G., Shi, Y.-Q.: Reversible data hiding using controlled contrast enhancement and integer wavelet transform. IEEE Signal Process. Lett. 22(11), 2078–2082 (2015)

    Article  Google Scholar 

  21. Lin, W., Dong, L., Xue, P.: Visual distortion gauge based on discrimination of noticeable contrast changes. IEEE Trans. Circuits Syst. Video Technol. 15, 900–909 (2005)

    Article  Google Scholar 

  22. Lubin, J.: A visual discrimination model for imaging system design and evaluation. Vis. Models Target Detect. Recogn. 2, 245–357 (1995)

    Article  Google Scholar 

  23. Jung, S.W., Ko, S.J.: A new histogram modification based reversible data hiding algorithm considering the human visual system. IEEE Signal Process. Lett. 18(2), 95–98 (2011)

    Article  Google Scholar 

  24. The USC-SIPI Image Database. http://sipi.usc.edu/database

  25. Gao, M.-Z., Wu, Z.-G., Wang, L.: Comprehensive evaluation for HE based contrast enhancement techniques. Adv. Intell. Syst. Appl. 2, 331–338 (2013)

    Google Scholar 

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Acknowledgment

This work is supported in part by National Natural Science Foundation of China under Grant 61379156, in part by the National Research Foundation for the Doctoral Program of Higher Education of China under Grant 20120171110037, and in part by the Key Program of Natural Science Foundation of Guangdong under Grant S2012020011114.

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Sun Yat-sen University, Guangzhou, China

    Haishan Chen & Jiangqun Ni

  2. Nanfang College of Sun Yat-sen University, Guangzhou, China

    Haishan Chen, Wien Hong & Junying Yuan

Authors
  1. Haishan Chen
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  2. Wien Hong
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  3. Jiangqun Ni
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  4. Junying Yuan
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Corresponding author

Correspondence to Junying Yuan .

Editor information

Editors and Affiliations

  1. University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Michigan State University , EAST LANSING, Michigan, USA

    Alex Liu

  3. National Dong Hwa University , Shoufeng, Taiwan

    Han-Chieh Chao

  4. Purdue University , West Lafayette, Indiana, USA

    Elisa Bertino

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Chen, H., Hong, W., Ni, J., Yuan, J. (2016). A Tunable Bound of the Embedding Level for Reversible Data Hiding with Contrast Enhancement. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10039. Springer, Cham. https://doi.org/10.1007/978-3-319-48671-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-48671-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48670-3

  • Online ISBN: 978-3-319-48671-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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