Abstract
This paper proposes a dual watermarking scheme based on subsampling and Compressive Sensing Theory. In this scheme, one robust watermark is embedded into the DCT domain of two sub-images and another watermark is embedded into the CS domain. Bit Correction Rate (BCR) between original secret message and extracted message are used to calculate the accuracy of this method. Extensive experimental results demonstrate the validity of the proposed scheme and high security of security information.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Tirkel A, Rankin G, Van Schyndel R et al (1993) Electronic watermark. In: Proceedings DICTA, vol 12, issue 5, pp 666–672
Shen H, Chen B (2012) From single watermark to dual watermark: a new approach for image watermarking. J Comput Electr Eng 38(5):1310–1324
Cox I, Miller M, Bloom J (2001) Digital watermarking: principles and practice. Morga Kaufman, San Francisco
Candes EJ, Wakin MB (2008) An introduction to compressive sampling. IEEE Signal Process Mag 25(2):21–30. doi:10.1109/MSP.2007.914731
Donoho DL (2006) Compressed sensing. IEEE Trans Inf Theory 52(4):1289–1306. doi:10.1109/TIT.2006.871582
Pan JS, Li W, Yang CS, Yan LJ (2014) Image steganography based on subsampling and compressive sensing. Springer Science+Business Media, New York
Candès E, Romberg J, Tao T (2006) Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inf Theory 52(2):489–509
Zhou YX, Jin W (2011) A novel zero-watermarking scheme based on DWT-SVD. IEEE Trans Inf Theory 57:978–982
Wei F (2014) Research of digital image blind watermarking algorithm based on comperssive sensing. Anhui University, Hefei
Chen GF, Guo SX, Li Y (2012) Digital image watermarking based on compressive sensing. Mod Electr Technol 35(13):98–104
Candes EJ, Romberg J, Tao T (2006) Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inf Theory 52(2):489–509
Valenzise G, Tagliasacchi M, Tubaro S, Cancelli G, Barni M (2009) A compressive sensing based watermarking scheme for sparseimage tampering identification. In: 16th IEEE International Conference on Image Processing (ICIP). IEEE, pp 1265–1268
Rachlin Y, Baron D (2008) The secrecy of compressed sensing measurements. In: 46th Annual Allerton conference on communication, control, and computing. IEEE, pp 813–817
Shannon CE (1949) Communication theory of secrecy systems. Bell Syst Tech J 28(4):656–715
Chambolle A (2004) An algorithm for total variation minimization and applications. J Math Imaging Vis 20(1–2):89–97
Li W, Lin CC, Pan JS (2015) Novel image authentication scheme with fine image quality for BTC-based compressed images. Multimedia Tools Appl 34:1–23
Pan JS, Li W, Lin CC (2014) Novel reversible data hiding scheme for AMBTC-compressed images by reference matrix. In: Multidisciplinary social networks research. Springer, Heidelberg, pp 427–436
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Pan, JS., Duan, JJ., Li, W. (2015). A Dual Watermarking Scheme by Using Compressive Sensing and Subsampling. In: Abraham, A., Jiang, X., Snášel, V., Pan, JS. (eds) Intelligent Data Analysis and Applications. Advances in Intelligent Systems and Computing, vol 370. Springer, Cham. https://doi.org/10.1007/978-3-319-21206-7_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-21206-7_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21205-0
Online ISBN: 978-3-319-21206-7
eBook Packages: EngineeringEngineering (R0)