Skip to content

Advertisement

  • Research Article
  • Open Access

A Secret Image Sharing Method Using Integer Wavelet Transform

EURASIP Journal on Advances in Signal Processing20072007:063281

https://doi.org/10.1155/2007/63281

  • Received: 28 August 2006
  • Accepted: 25 June 2007
  • Published:

Abstract

A new image sharing method, based on the reversible integer-to-integer (ITI) wavelet transform and Shamir's threshold scheme is presented, that provides highly compact shadows for real-time progressive transmission. This method, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficients into shadows, and allows recovery of the complete secret image by using any or more shadows . We take advantages of properties of the wavelet transform multiresolution representation, such as coefficient magnitude decay and excellent energy compaction, to design combination procedures for the transform coefficients and processing sequences in wavelet subbands such that small shadows for real-time progressive transmission are obtained. Experimental results demonstrate that the proposed method yields small shadow images and has the capabilities of real-time progressive transmission and perfect reconstruction of secret images.

Keywords

  • Information Technology
  • Quantum Information
  • Wavelet Transform
  • Secret Image
  • Integer Wavelet

[123456789101112131415161718]

Authors’ Affiliations

(1)
Department of Computer and Communication Engineering, Ming Chuan University, Taoyuan, 333, Taiwan
(2)
Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA

References

  1. Shamir A: How to share a secret. Communications of the ACM 1979,22(11):612-613. 10.1145/359168.359176MathSciNetView ArticleMATHGoogle Scholar
  2. Thien C-C, Lin J-C: Secret image sharing. Computers and Graphics 2002,26(5):765-770. 10.1016/S0097-8493(02)00131-0View ArticleGoogle Scholar
  3. Blakley GR: Safeguarding cryptographic keys. Proceedings of AFIPS National Computer Conference, June 1979, New York, NY, USA 48: 313-317.Google Scholar
  4. Chen S-K, Lin J-C: Fault-tolerant and progressive transmission of images. Pattern Recognition 2005,38(12):2466-2471. 10.1016/j.patcog.2005.04.002View ArticleGoogle Scholar
  5. Wang R-Z, Su C-H: Secret image sharing with smaller shadow images. Pattern Recognition Letters 2006,27(6):551-555. 10.1016/j.patrec.2005.09.021View ArticleGoogle Scholar
  6. Kim H, Li CC: Lossless and lossy image compression using biorthogonal wavelet transforms with multiplierless operations. IEEE Transactions on Circuits and Systems II 1998,45(8):1113-1118. 10.1109/82.718821View ArticleMATHGoogle Scholar
  7. Zandi A, Allen J, Schwartz E, Boliek M: CREW: compression with reversible embedded wavelets. Proceedings of the 5th Data Compression Conference, March 1995, Snowbird, Utah, USA 212-221.View ArticleGoogle Scholar
  8. Calderbank AR, Daubechies I, Sweldens W, Yeo B-L: Wavelet transforms that map integers to integers. Applied and Computational Harmonic Analysis 1998,5(3):332-369. 10.1006/acha.1997.0238MathSciNetView ArticleMATHGoogle Scholar
  9. Adams MD, Ward RK: Symmetric-extension-compatible reversible integer-to-integer wavelet transforms. IEEE Transactions on Signal Processing 2003,51(10):2624-2636. 10.1109/TSP.2003.816886MathSciNetView ArticleGoogle Scholar
  10. Said A, Pearlman WA: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits and Systems for Video Technology 1996,6(3):243-250. 10.1109/76.499834View ArticleGoogle Scholar
  11. Vaishampayan VA: Design of multiple description scalar quantizers. IEEE Transactions on Information Theory 1993,39(3):821-834. 10.1109/18.256491View ArticleMATHGoogle Scholar
  12. Wang Y, Reibman AR, Lin S: Multiple description coding for video delivery. Proceedings of the IEEE 2005,93(1):57-70.View ArticleGoogle Scholar
  13. Sayood K: Introduction to Data Compression. 2nd edition. Morgan Kaufmann, San Francisco, Calif, USA; 2000.MATHGoogle Scholar
  14. Proakis JG, Salehi M: Communication Systems Engineering. 2nd edition. Prentice-Hall, Englewood Cliffs, NJ, USA; 2001.MATHGoogle Scholar
  15. Sherwood PG, Zeger K: Progressive image coding for noisy channels. IEEE Signal Processing Letters 1997,4(7):189-191. 10.1109/97.596882View ArticleGoogle Scholar
  16. Chande V, Farvardin N: Progressive transmission of images over memoryless noisy channels. IEEE Journal on Selected Areas in Communications 2000,18(6):850-860. 10.1109/49.848239View ArticleGoogle Scholar
  17. Boulgouris NV, Thomos N, Strintzis MG: Transmission of images over noisy channels using error-resilient wavelet coding and forward error correction. IEEE Transactions on Circuits and Systems for Video Technology 2003,13(12):1170-1181. 10.1109/TCSVT.2003.819187View ArticleGoogle Scholar
  18. The Library of Congress website http://memory.loc.gov/ammem/gmdhtml/milhome.html

Copyright

Advertisement