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Comparative Analysis of Watermarking Techniques for Improved Compression of Images
Abstract
Digital Watermarking is a technique which provides embedded copyright information in images. This paper focuses on the capability of visible and invisible watermarking schemes based on DWT and Integer wavelet Transform to hide the original image. There are many techniques available in watermarking the digital image based on spatial and frequency domain. The spatial domain techniques carry less computations and it is not robust against attacks too because in that no transforms are used. In frequency domain techniques, DCT and DWT transforms are used and they provide good robust against attacks such as salt and pepper noise, degradations, histogram modifications, compression and filtering etc., Wavelet based watermarking techniques exploit the frequency and spatial information of the transformed data in multiple resolutions to improve the compression rate. The above cited watermarking techniques are performed by using MATLAB tool which provides better peak signal to noise ratio for digital images.
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References
Scott Craver, Nasir Memon, Boon-Lock Yeo, and Minerva M. Yeung, “Resolving Rightful Ownerships with Invisible Watermarking Techniques” in IEEE journal on selected areas in communications, vol. 16, no. 4, may 1998.
S. Craver, N. Memon, B. L. Yeo, and M. M. Yeung, “Can invisible watermarks resolve rightful ownerships,” in Proc., SPIE Storage and Retrieval for Still Image and Video Databases V, vol. SPIE 3022, Feb. 1997.
Chun-Hsiang Huang and Ja-Ling Wu, “Attacking Visible Watermarking Schemes” IEEE transactions on multimedia, vol. 6, no. 1, February 2004.
J. Meng and S. F. Chang, “Embedding Visible watermarks in the compresse domain,” presented at the ICIP 98.
Chuhong Fei, Deepa Kundur, and Raymond H. Kwong, “Analysis and Design of Watermarking Algorithms for Improved Resistance to Compression” IEEE transactions on image processing, vol. 13, no. 2, february 2004.
J. Eggers and B. Girod, “Informed Watermarking,” Norwell, MA:Kluwer, 2002.
Ehsan Nezhadarya Z. Jane Wang and Rabab Kreidieh Ward,’ Robust Image Watermarking Based on Multiscale Gradient Direction Quantization” IEEE transactions on information forensics and security, vol. 6, No. 4, December 2011.
Jian Cao and Jiwu Huang,” Controllable Secure Watermarking Technique for Tradeoff Between Robustness an Security” IEEE transactions on information forensics and security, vol. 7, no. 2, April 2012.
F. Cayre, C. Fontaine, and T. Furon, “Watermarking security: Theoryand practice,” IEEE Trans. Signal Process., vol. 53, no. 10, pp 3976–3987, Oct. 2005.
Dr.S. Jayaraman, S. Esakkirajan, T. Veerakumar; Title: Digital Image Processing; Publisher: TMH; New Delhi.
J. Tian, “Wavelet–based reversible watermarking for authentication”, Security and Watermarking of Multimedia Contents IV, vol. 4675, pp. 679–690, 2002.
R. C. Gonzalez, R. E. Woods and S. L. Eddins, “Digital Image Processing using MATLAB”, Pearson Education, 2004.
S. Jayasudha, “Integer Wavelet Transform based Steganographic Method using OPA Algorithm” Coimbatore Institute of Information Technology 978-1-4675-2248-9, 2012.
C. Chan and L. M. Cheng, “Hiding data in images by simple LSB substitution," Pattern Recognition, pp. 469-474, Mar. 2004.
Senthilkumar, C., & Gnanamurthy, R. K. (2014). A Performance Analysis of EZW, SPIHT Wavelet Based Compressed Images. Asian Journal of Information Technology, 13(11), 684-688
M.A. Raja, C. Senthilkumar, B. Arunadevi and P. Divya, 2016. “A Region-based Approach on Segmentation of Medical Image Compression”, International Journal of Printing, Packaging and Allied Sciences, Vol.04, Dec 2016
Senthilkumar, C., & Gnanamurthy, R. K. (2012). International Journal of Scientific & Engineering Research, Volume 3, Issue 4, April-2012, ISSN 2229-5518
Ramazan Gençay, Faruk Selçuk and Brandon Whitcher, An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press, 2001, ISBN 0-12-279670-5.
Haar A., Zur Theorie der orthogonalen Funktionensysteme, Mathematische Annalen, 69, pp 331–371, 1910.
Barbara Burke Hubbard, "The World According to Wavelets: The Story of a Mathematical Technique in the Making", AK Peters Ltd, 1998, ISBN 1568810725, ISBN 978-1568810720.
Gerald Kaiser, A Friendly Guide to Wavelets, Birkhauser, 1994, ISBN 0-8176-3711-7.
Stéphane Mallat, "A wavelet tour of signal processing" 2nd Edition, Academic Press, 1999, ISBN 0-12-466606-x.
Donald B. Percival and Andrew T. Walden, Wavelet Methods for Time Series Analysis, Cambridge University Press, 2000, ISBN 0-5216-8508-7.
Press, WH; Teukolsky, SA; Vetterling, WT; Flannery, BP (2007), "Section 13.10. Wavelet Transforms", Numerical Recipes: The Art of Scientific Computing (3rd ed.), New York: Cambridge University Press, ISBN 978-0-521-88068-8.
P. P. Vaidyanathan, Multirate Systems and Filter Banks, Prentice Hall, 1993, ISBN 0-13-605718-7.
Mladen Victor Wickerhauser, Adapted Wavelet Analysis from Theory to Software, A K Peters Ltd, 1994, ISBN 1-56881-041-5.
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