A New Image Watermarking Method in Wavelet Domain Using Hessenberg and Grey Wolf Optimizer Decomposition
Subject Areas : International Journal of Smart Electrical Engineering
mohammad mehdi piroozmandan
1
*
1 - Department of Computer Engineering, Eram Higher Education Institute, Shiraz, Iran.
Keywords: Grey Wolf Optimizer, Invariant wavelet transform, Image watermarking, Optimization, Hessenberg decomposition.,
Abstract :
This paper proposes a novel robust image watermarking scheme in the wavelet domain based on Grey Wolf Optimizer (GWO) using Hessenberg decomposition. The proposed method consists of three new algorithms. The first new algorithm applies the redistributed invariant discrete wavelet transform (RIDWT) to the host image to obtain an invariant wavelet domain. Following the RIDWT transform, the low-frequency sub-band of wavelet transformed image is segmented into non-overlapping blocks. Subsequently, the most suitable blocks are selected using the sum of visual and edge entropies for the watermark embedding. In this algorithm, the watermark embedding process is performed by Hessenberg decomposition. In the second new algorithm, the watermark extraction process from the watermarked host image is performed using Hessenberg decomposition. Furthermore, the Grey Wolf Optimizer (GWO) is employed in the third proposed algorithm to obtain optimized threshold and compensation parameters. The proposed method in this paper was evaluated using two standard measures, NC and PSNR, and demonstrated significantly better performance than other methods. In addition to its simplicity, this method exhibits strong robustness against image variations and manipulations and substantially improves image quality.
[1] S. P. Mohanty , B. K. Bhargava, "Invisible watermarking based on creation and robust insertion-extraction of image adaptive watermarks," ACM Transactions on Multimedia Computing Communications and Applications, 5(2), pp. 1-24,2008.
[2] S. Fazli , M. Moeinib, , "Robust image watermarking method based on DWT, DCT, and SVD using a new technique for correction of main geometric attacks," Optik, 127, pp. 964-972,2016.
[3] S. A. Parah, J. A. Sheikh, N. A. Loan and G. M. Bhat, "Robust and blind watermarking technique in DCT domain using inter-block coefficient differencing," Digital Signal Processing, 53, pp. 11-24, 2016.
[4] A. Benoraira, K. Benmahammed and N. Boucenna, , "Blind image watermarking technique based on differential embedding in DWT and DCT domains," EURASIP Journal on Advances in Signal Processing, 2015, pp. 1-11,2015.
[5] E. Najafi and K. Loukhaoukha, "Hybrid secure and robust image watermarking scheme based on SVD and sharp frequency localized contourlet transform," Journal of Information Security and Applications, 44, pp. 144-156,2019.
[6] I. A. Ansari and M. Pant, "Multipurpose image watermarking in the domain of DWT based on SVD and ABC," Pattern Recognition Letters, 94, pp. 228-236, 2017.
[7] J. L. D. Shivani and R. K. Senapati, , "False-positive-free, robust and blind watermarking scheme based on Shuffled SVD and RDWT," Journal of Advanced Research in Dynamical & Control Systems, 10(06)-Special Issue, pp. 1971-1981,2018.
[8] Hu, Y., and Z. Wang, "A geometric distortion resilient image watermark algorithm based on DWT-DFT," Journal of Software, 6 (9), pp. 1805-1812, 2011.
[9] H. B. Kekre, T. Sarode and S. Natu, "Robust watermarking for color images using SVD with row/column wavelet transform in low and mid-frequency spectrum of host," Advances in Image and Video Processing, 2 (6), 2014.
[10] X. L. Liu, C. C. Lin and S. M. Yuan, "Blind dual watermarking for color images’ authentication and copyright protection," IEEE Transactions on Circuits and Systems for video technology, (28) 5, pp. 1047-1055, 2018.
[11] T. Huynh-The, C. H. Hua, N. A. Tu, T. Hur, J. Bang, D. Kim, M. B. Amin, B. H. Kang, H. Seung and S. Lee, "Selective bit embedding scheme for robust blind color image watermarking," Information Sciences, 426, pp. 1-18, 2018.
[12] S. T. Chen, H. N. Huang, W. M. Kung and C. Y. Hsu, "Optimization-based image watermarking with integrated Quantization embedding in the wavelet domain," Multimedia Tools and Applications, 75(10), pp. 5493-5511, 2016.
[13] Q. Su, Y. Niu, G. Wang, S. Jia and J. Yue, "Color image blind watermarking scheme based on QR decomposition," Signal Processing, 94, pp. 219-235, 2014.
[14] L. Laur, P. Rasti, M. Agoyi and G. Anbarjafari, "A robust color image watermarking scheme using entropy and QR decomposition," Radioengineering, 24(4), pp. 1025-1031, 2015.
[15] M. Mardanpour and M. A. Z. Chahooki, "Robust transparent image watermarking with Shearlet transform and bidiagonal singular value decomposition," International Journal of Electronics and Communications, 70, pp. 790-798, 2016.
[16] Luo, Y., et al., A multi-scale image watermarking based on integer wavelet transform and singular value decomposition. Expert Systems with Applications, 168: p. 114272, 2021.
[17] Qu, G., et al., Optical color watermarking based on single-pixel imaging and singular value decomposition in invariant wavelet domain. Optics and Lasers in Engineering, 137: p. 106376, 2021.
[18] Sivananthamaitrey, P. and P.R. Kumar,” Optimal Dual Watermarking of Color Images with SWT and SVD Through Genetic Algorithm”, Circuits, Systems, and Signal Processing, 41(1): p. 224-248, 2022.
[19] Singha, A. and M.A. Ullah, “An image watermarking technique using hybrid signals as watermarks”, Multimedia Systems, 27(1): p. 89-109, 2021.
[20] Ahmadi, S.B.B., et al., “An intelligent and blind dual color image watermarking for authentication and copyright protection”, Applied Intelligence, 51(3): p. 1701-1732, 2021.
[21] Gong, L.-H., et al., “Robust and imperceptible watermarking scheme based on Canny edge detection and SVD in the contourlet domain”, Multimedia Tools and Applications, 80(1): p. 439-461, 2021.
[22] Altay, Ş.Y. and G. Ulutaş, “Self-adaptive step firefly algorithm based robust watermarking method in DWT-SVD domain”, Multimedia Tools and Applications, 80(15): p. 23457-23484, 2021.
[23] T.S Nguyen,” Fragile watermarking for image authentication based on DWT-SVD-DCT techniques”. Multimedia Tools and Applications, 80(16): p. 25107-25119, 2021.
[24] Kumar C, Singh AK, Kumar P ,” A recent survey on image watermarking techniques and its application in e-governance”, Multimedia Tools Appl, 77:3597–3622, 2018.
[25] Bagheri M, Mohrekesh M, Karimi N, Samavi S, Shirani S, Khadivi P ,” Image watermarking with region of interest determination using deep neural networks”, In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, pp 1067–1072, 2020.
[26] Wei Q, Wang H, Zhang G,” A robust image watermarking approach using cycle variational Autoencoder”. Secur Commun Netw, 2020.
[27] Ge S, Xia Z, Fei J, Sun X, Weng J , “A robust document image watermarking scheme using deep neural network”, arXiv preprint arXiv:2202.13067,2022.
[28] Zhong X, Huang PC, Mastorakis S, Shih FY ,”An automated and robust image watermarking scheme based on deep neural networks” IEEE Trans Multimedia 23:1951–1961, 2022.
[29] Ding W, Ming Y, Cao Z, Lin CT ,” A generalized deep neural network approach for digital watermarking analysis”, IEEE Trans Emerg Top Comput Intell 6(3):613–627, 2021.
[30] M. Ali, C.W. Ahn, “An optimized watermarking technique based on self-adaptive DE in DWT–SVD transform domain”, Signal Process. 545–556, 2014.
[31] L. Li, H.-H. Xu, C.-C. Chang, Y.-Y. Ma, “A novel image watermarking in redistributed invariant wavelet domain”, J. Syst. Softw. 923–929, 2011.
[32] R. Liu, T. Tan, “An SVD-based watermarking scheme for protecting rightful ownership”, IEEE Trans. Multimed. 121–128,2 003.
[33] M.M.Piroozmandan, F.Farokhi, K.Kangarloo, M.Jahanshahi,” Removing High Density Impulse Noise via a Novel Two Phase Method Using Fuzzy Cellular Automata”, International Journal of Smart Electrical Engineering, 177 – 186, 2021.
[34] M.M.Piroozmandan, F.Farokhi, K.Kangarloo, M.Jahanshahi,” Removing the impulse noise from images based on fuzzy cellular automata by using a two-phase innovative method”, Optik –International Journal for Light and Electron Optics , 168-713, 2022.
https://doi.org/10.1016/j.ijleo.2022.168713.
[35] Mohammad Mehdi Piroozmandan , Fardad Farokhi , Mohammad Ali Piroozmandan, “International Journal of Smart Electrical Engineering “, 147 – 155, 2024.
[36] G.H Golub, C,F,V Loan,”Matrix computations”, Johns Hopkins University Press, Baltimore, 1996.
[37] M. Ali , Ch.W Ahn , M. Pant , P. Siarry , “An image watermarking scheme in wavelet domain with optimized compensation of singular value decomposition via artificial bee colony”, Information Sciences, 2015, http://dx.doi.org/10.1016/j.ins.2014.12.042.
[38] E.H. Elshazly, O.S. Faragallah, A.M. Abbas, M.A. Ashour, E.-S.M. El-Rabaie, H. Kazemian, et al, “Robust and secure fractional wavelet image watermarking”, Signal, Image Video Process. 2014, http://dxdoi.org/10.1007/s11760-014-0684-x.
[39] Md.A Hussian, P. bora, “Novel Watermarking Technique Using Encryption Steganography”, Chaotic Logistic Map and Multiple Embedding, Procedia Computer Science,2020. https://doi.org/10.1016/j.procs.2020.04.227.
[40] H.K Singh , A. Kumar Singh, “Digital image watermarking using deep learning”, Multimedia Tools and Applications,2024, https://doi.org/10.1007/s11042-023-15750-x.
[41] D. Liu, D. Liu, B. Wang, P. Zheng, “Hybrid domain digital watermarking scheme based on improved differential evolution algorithm and singular value block embedding”, IET Image Processing,(2023),https:// 10.1049/ipr2.12814.
[42] Q. Wei, H. Wang, G. Zhang ,” A robust image watermarking approach using cycle variational autoencoder”. Secur Commun Netw, 2020.
[43] X. Zhong, PC. Huang, S. Mastorakis, FY. Shih, “An automated and robust image watermarking scheme based on deep neural networks”, IEEE Trans Multimedia, 2020.