A Robust Hybrid Image Watermarking Scheme Based on IWT-DCT-SVD using Entropy and Edge Entropy

M. Iman Wahyudi; Jufriadif  Na`am; Ferda  Ernawan

doi:10.29207/resti.v10i5.7509

Authors

M. Iman Wahyudi Universitas Nusa Mandiri
Jufriadif Na`am Universitas Nusa Mandiri
Ferda Ernawan Universiti Malaysia Pahang Al-Sultan Abdullah

DOI:

https://doi.org/10.29207/resti.v10i5.7509

Keywords:

entropy, edge entropy, hybrid image watermarking, imperceptibility, robustness

Abstract

The rapid expansion of digital multimedia distribution has increased the demand for dependable copyright protection and content authentication. Digital image watermarking has emerged as a principal solution, yet the fundamental challenge remains in balancing imperceptibility and robustness against various signal processing and geometric attacks. This paper proposes a novel hybrid watermarking scheme that combines the Integer Wavelet Transform (IWT), the Discrete Cosine Transform (DCT), and Singular Value Decomposition (SVD), while entropy and edge entropy decide where the watermark is embedded. The use of IWT overcomes the floating-point precision loss inherent in conventional Discrete Wavelet Transform (DWT), ensuring perfect reconstruction and higher accuracy in watermark extraction. DCT is employed to leverage energy compaction in mid frequency bands, while SVD provides exceptional stability against geometric distortions due to the inherent invariance of singular values. The critical innovation lies in the integration of entropy and edge entropy metrics to dynamically identify highly textured image blocks with maximum natural masking capacity. Unlike conventional HVS or variance-based methods that often mischaracterize directional edges, the proposed dual-entropy model precisely quantifies both luminance obliviousness and structural sensitivity, enabling the embedding of stronger watermarks without compromising perceptual quality. Extensive experiments on eight standard 512×512 benchmark images demonstrate consistently high imperceptibility, with an arithmetic average PSNR of 40.46 dB, SSIM of 0.9965, and FSIM of 0.9995. Robustness evaluations under fourteen categories of signal processing and geometric attacks yield Normalized Correlation (NC) values predominantly above 0.99, outperforming four recent state-of-the-art methods in eleven of twenty attack scenarios. The identified limitations include reduced robustness against large-angle rotation attacks, an inherent SVD challenge. The proposed framework demonstrates significant potential for secure, imperceptible digital image watermarking.

Downloads

Download data is not yet available.

References

[1] F. B. Mauro Barni, “Watermarking Systems Engineering: Enabling Digital Assets Security and Other Applications,” Watermarking Syst. Eng., 2004, doi: 10.1201/9780203913512.

[2] I. J. Cox, M. L. Miller, J. A. Bloom, J. Fridrich, and T. Kalker, Digital Watermarking and Steganography, Second Edition. 2007, doi: 10.1016/B978-0-12-372585-1.X5001-3.

[3] A. Mohanarathinam, S. Kamalraj, G. K. D. Prasanna Venkatesan, R. V. Ravi, and C. S. Manikandababu, “Digital watermarking techniques for image security: a review,” J. Ambient Intell. Humaniz. Comput., vol. 11, no. 8, pp. 3221-3229, Sept. 2020, doi: 10.1007/s12652-019-01500-1.

[4] C. I. Podilchuk and E. J. Delp, “Digital watermarking: Algorithm and application,” IEEE Signal Process. Mag., vol. 18, no. 4, pp. 33-46, Jul. 2001, doi: 10.1109/79.939835.

[5] N. F. Johnson and S. Jajodia, “Exploring steganography: Seeing the unseen,” Computer (Long. Beach. Calif)., vol. 31, no. 2, pp. 24-34, Feb. 1998, doi: 10.1109/MC.1998.4655281.

[6] S. P. Mohanty, N. Ranganathan, and R. K. Namballa, “VLSI implementation of invisible digital watermarking algorithms towards the development of a secure JPEG encoder,” in IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation, 2003, pp. 183-188, Aug. 2003, doi: 10.1109/SIPS.2003.1235666.

[7] A. B. Watson, G. Y. Yang, J. A. Solomon, and J. Villasenor, “Visibility of wavelet quantization noise,” IEEE Trans. Image Process., vol. 6, no. 8, pp. 1164-1175, Aug. 1997, doi: 10.1109/83.605413.

[8] A. R. Calderbank, I. Daubechies, W. Sweldens, and B. L. Yeo, “Wavelet Transforms That Map Integers to Integers,” Appl. Comput. Harmon. Anal., vol. 5, no. 3, pp. 332-369, Jul. 1998, doi: 10.1006/acha.1997.0238.

[9] R. Liu and T. Tan, “An SVD-based watermarking scheme for protecting rightful ownership,” IEEE Trans. Multimed., vol. 4, no. 1, pp. 121-128, Mar. 2002, doi: 10.1109/6046.985560.

[10] J. L. Mannos and D. J. Sakrison, “The Effects of a Visual Fidelity Criterion on the Encoding of Images,” IEEE Trans. Inf. Theory, vol. 20, no. 4, pp. 525-536, Jul. 1974, doi: 10.1109/TIT.1974.1055250.

[11] N. Agani, M. I. Wahyudi, N. Agani, and M. I. Wahyudi, “Document Authentication Using Print-Scan Image Watermarking Based on DCT (Discrete Cosine Transform) Algorithm,” Information Systems International Conference (ISICO), 2013, pp. 465-470, Dec. 2013. available: https://is.its.ac.id/pubs/oajis/index.php/home/detail/1155/

[12] F. Peng, “Print-scan resilient binary map watermarking based on DCT and scrambling,” Int. J. Digit. Crime Forensics, vol. 10, no. 4, pp. 80–89, Oct. 2018, doi: 10.4018/IJDCF.2018100106.

[13] Z. Yuan, D. Liu, X. Zhang, and Q. Su, “New image blind watermarking method based on two-dimensional discrete cosine transform,” Optik (Stuttg)., vol. 204, Feb. 2020, doi: 10.1016/j.ijleo.2019.164152.

[14] M. Begum and M. S. Uddin, “Multiple Image Watermarking with Discrete Cosine Transform,” J. Comput. Commun., vol. 09, no. 03, pp. 88-94, Mar. 2021, doi: 10.4236/jcc.2021.93006.

[15] Krishna Kumar Bohra and Vinod Kumar Soni, “Invisible watermarking using Discrete Cosine Transform (DCT): A comprehensive exploration,” World J. Adv. Res. Rev., vol. 24, no. 2, pp. 2639-2645, Nov. 2024, doi: 10.30574/wjarr.2024.24.2.3623.

[16] D. Kundur and D. Hatzinakos, “Digital watermarking using multiresolution wavelet decomposition,” in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1998, vol. 5, pp. 2969-2972, May 1998, doi: 10.1109/ICASSP.1998.678149.

[17] S. P. Ingale and P. C. A. Dhote, “Digital Watermarking Algorithm using DWT Technique,” Int. J. Comput. Sci. Mob. Comput., vol. 5, no. 5, pp. 1-9, May 2016. available: https://ijcsmc.com/docs/papers/May2016/V5I5201601.pdf

[18] A. Tiwari, A. Arya, and S. Shukla, “Digital Watermarking Encryption and Decryption Using DWT,” Int. Res. J. Eng. Technol., vol. 2, no. 2, pp. 602-607, May 2015. available: https://www.irjet.net/archives/V2/i2/Irjet-v2i2111.pdf

[19] S. E. Naffouti, A. Kricha, and A. Sakly, “A sophisticated and provably grayscale image watermarking system using DWT-SVD domain,” Vis. Comput., vol. 39, no. 9, pp. 4227–4247, Jul. 2023, doi: 10.1007/s00371-022-02587-y.

[20] E. Kapoor, A. Mahendru, K. Goswami, and R. K. Yadav, “Hybrid DCT-DWT-SVD Watermarking: A Comparative Performance Analysis,” in Digital Watermarking in Cloud Environments For Copyright Protection, pp. 245-260, Aug. 2025. doi: 10.4018/979-8-3373-3785-2.ch011

[21] M. Begum, J. Ferdush, and M. S. Uddin, “A Hybrid robust watermarking system based on discrete cosine transform, discrete wavelet transform, and singular value decomposition,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 8, pp. 5856-5867, Sept. 2022, doi: 10.1016/j.jksuci.2021.07.012.

[22] B. M. K. Prasad, N. Ruhil, K. Singh, K. Negi, and R. Chauhan, “DCT, DWT, SVD & integrated DCT-DWT based robust digital image watermarking algorithm,” The International Conference on Communication and Computing Systems (ICCCS-2016) pp. 3-9, Nov. 2016, doi: 10.1201/9781315364094-3.

[23] S. Jose, R. Cherian Roy, and S. S. Nambiar, “Robust Image Watermarking based on DCT-DWT-SVD Method,” Int. J. Comput. Appl., vol. 58, no. 21, pp. 12-16, Nov. 2012, doi: 10.5120/9406-3798.

[24] B. Mokashi, V. S. Bhat, J. D. Pujari, S. Roopashree, T. R. Mahesh, and D. S. Alex, “Efficient Hybrid Blind Watermarking in DWT-DCT-SVD with Dual Biometric Features for Images,” Contrast Media Mol. Imaging, vol. 2022, pp. 1-14, Sept. 2022, doi: 10.1155/2022/2918126.

[25] A. Abdussalam and E. R. Pramudya, “Compression Run Length Encoding On Watermarking Using a Combination of DCT, DWT and SVD,” J. Appl. Intell. Syst., vol. 8, no. 2, pp. 129-139, Jul. 2023, doi: 10.33633/jais.v8i2.7524.

[26] V. Sundhararaj, B. Meenakshipriya, P. N. Devi, and K. E. Vignesh, “DWT-DCT-SVD: A Hybrid Image Watermarking Algorithm with FPP Resistant Enhancement,” Circuits, Syst. Signal Process., vol. 44, no. 9, pp. 6650–6675, Apr. 2025, doi: 10.1007/s00034-025-03097-7.

[27] S. Shubuh, F. Ernawan, A. Amrullah, and P. Wahyu, “Robust Image Watermarking Based on IWT-DCT-SVD for Copyright Protection,” Iraqi J. Comput. Sci. Math., vol. 5, no. 4, pp. 27-35, Nov. 2024, doi: 10.52866/2788-7421.1201.

[28] M. I. Wahyudi, I. Fauzi, and D. Atmojo, “Robust Image Watermarking Based on Hybrid IWT-DCT-SVD,” IJACI Int. J. Adv. Comput. Informatics, vol. 1, no. 2, pp. 89–98, Jul. 2025, doi: 10.71129/ijaci.v1.i2.pp89-98.

[29] P. Garg and R. R. Kishore, “Optimized color image watermarking through watermark strength optimization using particle swarm optimization technique,” J. Inf. Optim. Sci., vol. 41, no. 6, pp. 1499–1512, Aug. 2020, doi: 10.1080/02522667.2020.1802124.

[30] I. A. Ansari and M. Pant, “Quality assured and optimized image watermarking using artificial bee colony,” Int. J. Syst. Assur. Eng. Manag., vol. 9, no. 1, pp. 274–286, Feb. 2018, doi: 10.1007/s13198-016-0568-2.

[31] Y. Zhang, “Blind watermark algorithm based on HVS and RBF neural network in DWT domain,” WSEAS Trans. Comput., vol. 8, no. 1, pp. 174-183, Jan. 2009. doi: 10.5555/1534462.1534478

[32] Y. Dong, R. Yan, Q. Zhang, and X. Wu, “A Hybrid Domain Color Image Watermarking Scheme Based on Hyperchaotic Mapping,” Mathematics, vol. 12, no. 12, pp. 1–18, Jun. 2024, doi: 10.3390/math12121859.

[33] Y. Dong, R. Yan, and C. Yin, “An adaptive robust watermarking scheme based on chaotic mapping,” Sci. Rep., vol. 14, no. 24735, Oct. 2024, doi: 10.1038/s41598-024-76101-w.

[34] R. Dwivedi and V. K. Srivastava, “IWT based robust and secure color image watermarking using Hessenberg decomposition and SVD,” J. Opt., vol. 54, pp. 2866–2877, Nov. 2024, doi: 10.1007/s12596-024-02141-0.

[35] M. Sahir, T. Bekkouche, F. Belilita, and N. Amardjia, “An Optimized Color Image Watermarking Scheme based on HD and SVD in DWT Domain,” Eng. Technol. Appl. Sci. Res., vol. 15, no. 2, pp. 21639-21646, Apr. 2025, doi: 10.48084/etasr.9504.

[36] L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM: A feature similarity index for image quality assessment,” IEEE Trans. Image Process., vol. 20, no. 8, pp. 2378-2386, Jan. 2011, doi: 10.1109/TIP.2011.2109730.

[37] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans. Image Process., vol. 6, no. 12, pp. 1673-1687, Dec. 1997, doi: 10.1109/83.650120.