An Integrated Approach to Image Watermarking and JPEG-2000 Compression

  • Po-Chyi Su
  • Houng-Jyh Mike Wang
  • C.-C. Jay Kuo
Article

Abstract

A scheme which integrates image compression and image watermarking in an effective way is proposed in this research. The image compression scheme under consideration is EBCOT (Embedded Block Coding with Optimized Truncation) which has been adopted in the verification model (VM) of the emerging JPEG-2000 image compression standard. The watermark is embedded during the process when the compressed bit-stream is formed, and can be detected on the fly in image decoding. Thus, watermark embedding and retrieval can be done very efficiently in comparison with other existing watermarking schemes. In addition to efficiency, the proposed scheme has many interesting features. The embedded watermark is robust against various signal processing attacks such as coding and filtering while the watermarked image maintains good perceptual quality. The watermark retrieval procedure does not require the knowledge of the original image. Furthermore, the watermark can be detected progressively and region of interest (ROI) watermarking can be accomplished easily.

JPEG-2000 EBCOT digital watermark progressive watermark detection ROI 

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References

  1. 1.
    M.D. Swanson, M. Kobayashi, and A.H. Tewfik, “Multimedia Data Embedding and Watermarking Technologies, ” Proceeding of IEEE, vol. 86, no. 6, 1998, pp. 1064–1087.CrossRefGoogle Scholar
  2. 2.
    F. Hartung and M. Kutter, “Multimedia Watermarking Tech-niques, ” Proceeding of IEEE, vol. 87, no. 7, 1999, pp. 1079–1107.Google Scholar
  3. 3.
    R.B. Wolfgang, C.I. Podilchuk, and E.J. Delp, “Perceptual Wa-termarking for Digital Images and Video, ” Proceeding of IEEE, vol. 87, no. 7, 1999, pp. 1108–1126.CrossRefGoogle Scholar
  4. 4.
    G. Caronni, “Assuring Ownership Rights for Digital Images, ” in Proc.VIS 95; Session Reliable IT Systems, Vieweg, Germany, 1995, pp. 251–263.Google Scholar
  5. 5.
    K. Tanaka, Y. Nakamura, and K. Matsui, “Embedding Secret In-formation into a Dithered Multi-Level Image, ” in Proc.1999 IEEE Military Communications Conference, Monterey, CA, 1990, pp. 216–220.Google Scholar
  6. 6.
    R.G. van Schyndel, A.Z. Tirkel, and C.F. Osborne, “A Digital Watermark, ” in Proc.1994 IEEE Int.Conf.on Image Process-ing( ICIP), Austin, TX, 1994, vol. 2, pp. 86–90.Google Scholar
  7. 7.
    W. Bender, D. Gruhl, N. Morimoto, and A. Lu, “Techniques for Data Hiding, ” in IBM Syst.Journal, 1996, vol. 35, no. 3/4, pp. 313–316.CrossRefGoogle Scholar
  8. 8.
    A. Piva, M. Barni, F. Bartolini, and V. Cappellini, “DCT-Based Watermark Recovering Without Resorting to the Uncorrupted Original Image, ” in Proc.1997 IEEE Int.Conf.on Image Pro-cessing( ICIP), Santa Barbara, CA, 1997, vol. 1, pp. 520–523.Google Scholar
  9. 9.
    I.J. Cox, F.T. Leighton, and T. Shamoon, “Secure Spread Spec-trum Watermarking for Images, Audio and Video, ” in Proc.1996 IEEE Int.Conf.on Image Processing(ICIP), Lausanne, Switzerland, 1996, pp. 243–246.Google Scholar
  10. 10.
    X.G. Xia, C.G. Boncelet, and G.R. Arce, “A Multisolution Watermark for Digital Images, ” in Proc.1997 IEEE Int.Cont.on Image Processing(ICIP), Santa Barbara, CA, vol. 1, 1997, pp. 548–551.Google Scholar
  11. 11.
    C.I. Podilchuk and W. Zeng, “Image-Adaptive Watermarking Using Visual Models, ” in IEEE Journal on Selected Areas in Communications, vol. 16, no. 4, 1998, pp. 525–539.CrossRefGoogle Scholar
  12. 12.
    H.-J. Wang, P.-C. Su, and C.-C.J. Kuo, “Wavelet Based Blind Watermark Retrieval Technique, ” in 1998 SPIE Photonics East-Symposium on Voice, Video, and Data Communications, Boston, MA, 1998.Google Scholar
  13. 13.
    C. Chrysafis, D. Taubman, and A. Drukarev, “Overview of JPEG2000, ” in Proc.1999 PICS 52nd Annual Conference, Savannah, GA, 1999, pp. 333–338.Google Scholar
  14. 14.
    JPEG 2000 Document, “JPEG 2000 Verification Model 5.0 (Technical description), ” ISO/IEC JTC1/SC29/WG1 N1409, July 1999.Google Scholar
  15. 15.
    A. Said and W.A. Pearlman, “A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees, ” in IEEE Trans.on Circuits and Systems for Video Technology, vol. 6, 1996, pp. 243–250.CrossRefGoogle Scholar
  16. 16.
    J. Shapiro, “Embedded Image Coding Using Zerotrees of Wavelet Coefficients, ” in IEEE Trans.on Signal Processing, vol. 4, 1993, pp. 3445–3462.CrossRefGoogle Scholar
  17. 17.
    H. Stark and J.W. Woods, Probability, Random Processes and Estimation Theory for Engineers, Englewood Cliffs, NJ: Pren-tice Hall, 1994.Google Scholar
  18. 18.
    M.-Y. Shen and C.-C.J. Kuo, “Artifact Reduction in Low Bit Rate Wavelet Coding with Robust Nonlinear Filtering, ” in Proc.1998 IEEE Second Workshop on Multimedia Signal Processing, Redondo Beach, CA, 1998, pp. 480–485.Google Scholar
  19. 19.
    P.-C. Su, H.-J.M. Wang, and C.-C.J. Kuo, “Digital Image Watermarking in Regions of Interest, ” in Proc.1999 PICS 52nd Annual Conference, Savannah, GA, 1999, pp. 295–300.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Po-Chyi Su
    • 1
  • Houng-Jyh Mike Wang
    • 1
  • C.-C. Jay Kuo
    • 1
  1. 1.Department of Electrical Engineering-SystemsUniversity of Southern CaliforniaLos AngelesUSA

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