A robust blind watermarking scheme based on lifting wavelet transform and hessenberg decomposition
Abstract
In this paper, a novel robust blind grayscale image digital watermarking scheme is introduced based on lifting wavelet transform (LWT) in combination with discrete cosine transform (DCT), Hessenberg decomposition, and entropy analysis for copyright protection of multimedia information. At first, the two levels of LWT are applied to the host grayscale image to improve the imperceptibility of the watermarking scheme and then the high-frequency sub-band of the 2-level of LWT is decomposed by DCT. Next, the DCT coefficients are divided into 4×4 non-overlapping blocks. After that, Hessenberg decomposition performs on each selected block, whereas the first row, first column element of the upper Hessenberg matrix is utilized to hide the watermark. To evaluate the imperceptibility and robustness of the proposed digital watermarking scheme, the peak signal-to-noise ratio (PSNR), and normalized cross-correlation (NC) are utilized to measure the quality and the ability of the proposed watermarking scheme to robust against signal processing operations and geometric attacks. Experimental and analysis results have demonstrated that the proposed scheme is achieved a very good tradeoff between imperceptibility and robustness. The comparison with other scheme have shown that the proposed digital watermarking schemes have a superior performance in terms of imperceptibility and robustness than other.
Full text article
References
J. C. Patra, J. E. Phua, and C. Bornand, "A novel DCT domain CRT-based watermarking scheme for image authentication surviving JPEG compression," Digital Signal Processing, vol. 20, pp. 1597-1611, 2010.
S.-W. Byun, H.-S. Son, and S.-P. Lee, "Fast and Robust Watermarking Method Based on DCT Specific Location," IEEE Access, vol. 7, pp. 100706-100718, 2019.
V. S. Verma, R. K. Jha, and A. Ojha, "Significant region based robust watermarking scheme in lifting wavelet transform domain," Expert Systems with Applications, vol. 42, pp. 8184-8197, 2015.
B. Lei, Y. Soon, F. Zhou, Z. Li, and H. Lei, "A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition," Signal processing, vol. 92, pp. 1985-2001, 2012.
F. Ernawan and M. N. Kabir, "A block-based RDWT-SVD image watermarking method using human visual system characteristics," The Visual Computer, vol. 36, pp. 19-37, 2020.
S. S. Jamal, T. Shah, S. Farwa, and M. U. Khan, "A new technique of frequency domain watermarking based on a local ring," Wireless Networks, vol. 25, pp. 1491-1503, 2019.
N. M. Makbol, B. E. Khoo, and T. H. Rassem, "Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics," IET Image processing, vol. 10, pp. 34-52, 2016.
A. Zear, A. K. Singh, and P. Kumar, "A proposed secure multiple watermarking technique based on DWT, DCT and SVD for application in medicine," Multimedia Tools and Applications, vol. 77, pp. 4863-4882, 2018.
M. Cedillo-Hernández, F. García-Ugalde, M. Nakano-Miyatake, and H. M. Pérez-Meana, "Robust hybrid color image watermarking method based on DFT domain and 2D histogram modification," Signal, Image and Video Processing, vol. 8, pp. 49-63, 2014.
O. Abodena, M. Agoyi, and E. Celebi, "Hybrid technique for robust image watermarking using discrete time fourier transform," in 2017 25th Signal Processing and Communications Applications Conference (SIU), 2017, pp. 1-4.
Y. Guo and B.-Z. Li, "Blind image watermarking method based on linear canonical wavelet transform and QR decomposition," IET image processing, vol. 10, pp. 773-786, 2016.
M. H. Vali, A. Aghagolzadeh, and Y. Baleghi, "Optimized watermarking technique using self-adaptive differential evolution based on redundant discrete wavelet transform and singular value decomposition," Expert Systems with Applications, vol. 114, pp. 296-312, 2018.
O. Abodena and M. Agoyi, "Colour image blind watermarking scheme based on fast walsh hadamard transform and hessenberg decomposition," Studies in Informatics and Control, vol. 27, pp. 339-348, 2018.
R. Thanki, A. Kothari, and D. Trivedi, "Hybrid and blind watermarking scheme in DCuT–RDWT domain," Journal of Information Security and Applications, vol. 46, pp. 231-249, 2019.
H.-T. Hu, J.-R. Chang, and S.-J. Lin, "Synchronous blind audio watermarking via shape configuration of sorted LWT coefficient magnitudes," Signal Processing, vol. 147, pp. 190-202, 2018.
N. Brahimi, T. Bouden, T. Brahimi, and L. Boubchir, "A novel and efficient 8-point DCT approximation for image compression," Multimedia Tools and Applications, pp. 1-17, 2020.
Q. Su and B. Chen, "A novel blind color image watermarking using upper Hessenberg matrix," AEU-International Journal of Electronics and Communications, vol. 78, pp. 64-71, 2017.
W. Sweldens, "The lifting scheme: A construction of second generation wavelets," SIAM journal on mathematical analysis, vol. 29, pp. 511-546, 1998.
B. Kazemivash and M. E. Moghaddam, "A robust digital image watermarking technique using lifting wavelet transform and firefly algorithm," Multimedia Tools and Applications, vol. 76, pp. 20499-20524, 2017.
A. Bhardwaj, V. S. Verma, and R. K. Jha, "Robust video watermarking using significant frame selection based on coefficient difference of lifting wavelet transform," Multimedia Tools and Applications, vol. 77, pp. 19659-19678, 2018.
L. Sun, S. Liang, P. Chen, and Y. Chen, "Encrypted digital watermarking algorithm for quick response code using discrete cosine transform and singular value decomposition," Multimedia Tools and Applications, vol. 80, pp. 10285-10300, 2021.
O. Abodena and A. Alashtir, "HIGH HIDING CAPACITY AUDIO WATERMARKING METHOD BASED ON DISCRETE COSINE TRANSFORM," Internation Journal Of Advance Research And Innovative Ideas In Education, vol. 7, pp. 677-684, 2021.
Q. Su, "Novel blind colour image watermarking technique using Hessenberg decomposition," IET image processing, vol. 10, pp. 817-829, 2016.
S. Kumar and B. K. Singh, "Entropy based spatial domain image watermarking and its performance analysis," Multimedia Tools and Applications, vol. 80, pp. 9315-9331, 2021.
S. Kumar and B. K. Singh, "DWT based color image watermarking using maximum entropy," Multimedia Tools and Applications, vol. 80, pp. 15487-15510, 2021.
A. G. Weber, "The USC-SIPI image database: Version 5," http://sipi. usc. edu/database/, 2006.
A. K. Yadav, R. Mehta, R. Kumar, and V. P. Vishwakarma, "Lagrangian twin support vector regression and genetic algorithm based robust grayscale image watermarking," Multimedia Tools and Applications, vol. 75, pp. 9371-9394, 2016.
R. Keshavarzian and A. Aghagolzadeh, "ROI based robust and secure image watermarking using DWT and Arnold map," AEU-International Journal of Electronics and Communications, vol. 70, pp. 278-288, 2016.
Authors
Copyright (c) 2022 Journal of Pure & Applied Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
In a brief statement, the rights relate to the publication and distribution of research published in the journal of the University of Sebha where authors who have published their articles in the journal of the university of Sebha should how they can use or distribute their articles. They reserve all their rights to the published works, such as (but not limited to) the following rights:
- Copyright and other property rights related to the article, such as patent rights.
- Research published in the journal of the University of Sebha and used in its future works, including lectures and books, the right to reproduce articles for their own purposes, and the right to self-archive their articles.
- The right to enter a separate article, or for a non-exclusive distribution of their article with an acknowledgment of its initial publication in the journal of Sebha University.
Privacy Statement The names and e-mail addresses entered on the Sabha University Journal site will be used for the aforementioned purposes only and for which they were used.