Abstract
This paper presents an improved image-adaptive watermarking technique. Two image watermarks are embedded in the high entropy 8 × 8 blocks of the host image. DWT is applied on these blocks using the principle of sub band coding. This decomposes the high entropy blocks into four sub band coefficients, wherein the approximation and vertical frequency coefficients are modeled using Gaussian (or Normal) distribution. The two watermarks are inserted in the host image using Adjustable Strength Factor (ASF). It is calculated adaptively using the fourth statistical moment known as kurtosis. A limited side information is also transmitted along with the watermarked image. This side information consists of high entropy block positions and Gaussian distribution parameters. To extract both watermarks from the received watermarked image, the high entropy block positions sent in the side information help in applying DWT to calculate the approximation and vertical frequency coefficients. Gaussian (or Normal) distribution is similarly used for modeling and calculating the distribution parameters. This helps the Maximum Likelihood (ML) decoder to recover the watermarks successfully using a statistical approach. Two important contributions are presented in this paper. Firstly, adjustable kurtosis values are used which improves the capacity and robustness of the proposed technique. Secondly, the proposed work is implemented on medical applications and gives better performance as compared to the existing methods. Further, the efficiency of the proposed work is evaluated by better simulation results using PSNR, NCC, SSIM and GMSD under different attacks. The technique is highly robust as watermarks survive under different attacks. This increases security and ensures copyright protection.
Similar content being viewed by others
References
Aditi Z, Amit SK, Pardeep K (2016) A proposed secure multiple watermarking technique based on DWT, DCT and SVD for application in medicine. Multimed Tools Appl. https://doi.org/10.1007/s11042-016-3862-8
Akhaee MA, Sahraeian SME, Sankur B, Marvasti F (2009) Robust scaling based image watermarking using maximum-likelihood decoder with optimum strength factor. IEEE Transactions on Multimedia 11:822–833
Amirmazlaghani M, Rezghi M, Amindavar H (2015) A novel robust scaling image watermarking scheme based on Gaussian Mixture Model. Expert Syst Appl 42:1960–1971
Amit SK, Mayank D, Anand M (2015) Hybrid technique for robust and imperceptible multiple watermarking using medical images. Multimed Tools Appl. https://doi.org/10.1007/s11042-015-2754-7
Arsalan M, Malik SA, Khan A (2012) Intelligent reversible watermarking in integer wavelet domain for medical images. J Syst Softw 85(4):883–894
Bhatnagar G, Raman B, Swaminathan K (2009) Dual watermarking scheme for copyright protection and authentication. J Digit InfManag 7(1):2–8
Bhatnagar G, Wu JQM (2013) A new robust and efficient multiple watermarking scheme. Multimed Tools Appl 74:8421–8444
Bhinder P, Singh K, Jindal N (2018) Image-adaptive watermarking using maximum likelihood decoder for medical images. Multimed Tools Appl 77:1030310328
Falgun TN, Vijay SK (2016) A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications. Multimed Tools Appl. https://doi.org/10.1007/s11042-016-3928-7
Ganic E, Eskicioglu AM (2004) A DFT-based semi-blind multiple watermarking scheme for images. In: New York metro area networking workshop. The Graduate Center of the City University of New York, New York: 1–10
Giakoumaki A, Pavlopoulos S, Koutsouris D (2006) Secure and efficient health data management through multiple watermarking on medical images. Med Bio EngComput 44:619–631
Hu Y, Kwong S, Huang J (2004) Using invisible watermarks to protect visibly watermarked images. Proceedings of International Symposium on Circuits and Systems 5:584–587
Inamdar VS, Rege PP (2014) Dual watermarking technique with multiple biometric watermarks. Sadhana 39:3–26
Joshi K, Yadav R (2017) A LL Subband Based Digital Watermarking in DWT. I J Engineering and Manufacturing 2:50–63
Kallel M, Lapayre JC, Bouhlel MS (2007) A multiple watermarking scheme for medical image in the spatial domain. GVIP J 7(1):37–42
Lu W, Sun W, Lu H (2012) Novel robust image watermarking based on subsampling and DWT. Multimed Tools Appl 60:31–46
Luo L, Chen Z, Chen M, Zeng X, Xiong Z (2010) Reversible image watermarking using interpolation technique. IEEE Trans Inf Forensics Secur 5(1):187–193
Mihcak MK, Kozintsey I, Ramchandran K, Moulin P (1999) Low complexity image modeling based on statistical modeling of wavelet coefficients. IEEE Signal Processing Letters 6(12):300–303
Mohammed AHA, (2010): Advanced Techniques in Multimedia Watermarking: Image, Video and Audio Applications
Mohanty SP, Ramakrishnan K, Kankanhalli M (1999) A dual watermarking technique for images. ACM Multimedia, Orlando, pp 49–51
Nezhadarya E, Wang ZJ, Ward RK (2011) Robust image watermarking based on multi-scale gradient direction quantization. IEEE Trans Inf Forensics Secur 6(4):1200–1213
Parah AS, Sheikh AJ, Ahad F, Loan AN, Bhat GM (2015) Information hiding in medical images: a robust medical image watermarking system for E-healthcare. Multimed Tools Appl 76(8):10599–10633
Peter PHW, Oscar CA, Yeung YM (2003) A novel blind multiple watermarking technique for images. IEEE Trans Circuits Syst Video Technol 13(8):813–830
Rangel-Espinoza K, Fragoso-Navarro E, Cruz-Ramos C (2018) Adaptive removable visible watermarking technique using dual watermarking for digital color images. Multimed Tools Appl 77:13047–13074
Roy S, Pal AK (2017) A robust blind hybrid image watermarking scheme in RDWT-DCT domain using Arnold Scrambling. Multimed Tools Appl 76:3577–3616
Singh AK, Dave M, Mohan A (2015) Multilevel encrypted text watermarking on medical images using spread-spectrum in DWT domain. Wireless Personal Comm 83(3):2133–2150
Singh H, Kaur L, Singh K (2014) Fractional M-band dual tree complex wavelet transform for digital watermarking. Sadhana 39:345–361
Singh H, Kaur L, Singh K (2014) A novel robust logo watermarking scheme using fractional M_band wavelet transform. J Commun Technol Electron 59:1234–1246
Song C, Sudirman S, Merabti M (2012) A robust region-adaptive dual image watermarking technique. J Vis Commun Image Represent 23(3):549–568
Taoa P, Eskicioglub AM (2004) A robust multiple watermarking scheme in the discrete wavelet transform domain. In: Proceedings of the SPIE: Internet Multimedia Management Systems V, 5601, 133–144
Thodi DM, Rodríguez JJ (2007) Expansion embedding techniques for reversible watermarking. IEEE Trans Image Process 16(3):721–730
Tian J (2002) Wavelet-based reversible watermarking for authentication. In: Proceedings of the SPIE 4675, Security and Watermarking of Multimedia Contents IV, pp. 679–690.
Verma VS, Jha RK, Ojha A (2015) Digital watermark extraction using support vector machine with principal component analysis based feature reduction. J Vis Commun Image R 31:75–85
Xue W, Zhang L, Mou X, Bovik AC (2014) Gradient magnitude similarity deviation: A highly efficient perceptual image quality index. IEEE Trans Image Process 23(2)
Yadav N (2017) DWT-SVD-WHT watermarking using varying strength factor derived from means of the WHT coefficients. Arab J Sci Eng 43(8):4131–4143
Yadav N, Singh K (2014) Robust image-adaptive watermarking using an adjustable dynamic strength factor. SIViP 9(7):1531–1542
Yadav N, Singh K (2015) Transform domain robust image-adaptive watermarking: prevalent techniques and their evaluation. IEEE International Conference on Computing, Communication and Automation (ICCCA2015), 1121–1126
Yaghmaee F, Jamzad M (2008) Introducing a Two Dimensional Measure for Watermarking Capacity in Images. In: Campilho A., Kamel M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg.
Yao T, Que DS, Su QT (2013) A dual watermarking algorithm based on chaotic in contourlet-domain. AdvSciLett 19(4):1234–1237
Acknowledgements
The authors would like to thank the anonymous reviewers for their valuable comments which have helped to improve the quality of the paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bhinder, P., Jindal, N. & Singh, K. An improved robust image-adaptive watermarking with two watermarks using statistical decoder. Multimed Tools Appl 79, 183–217 (2020). https://doi.org/10.1007/s11042-019-07941-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-07941-2