Ultrasonic Echo Image Adaptive Watermarking Using the Just-Noticeable Difference Estimation
Authors: Amnach Khawne, Kazuhiko Hamamoto, Orachat Chitsobhuk
Abstract:
Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.
Keywords: Medical image watermarking, Human Visual System, Image Adaptive Watermark
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330459
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[1] G. Coatrieux, H. Maitre, B. Sankur, Y. Rolland, R. Collorec, "Relevance of Watermarking in Medical Imaging", IEEE International Conference ITAB, USA, pp. 250-255, Nov. 2000.
[2] G. Coatrieux, L. Lecornu, C. Roux, B. Sankur,"A Review of Image Watermarking Applications in Healthcare", Int. Conference on Engineering in Medicine and Biology, Sep. 2006.
[3] G. Coatrieux C. Quantin, J. Montagner, M. Fassa, F. Allaert,and C. Roux, "Watermarking medical images with anonymous patient identification to verify authenticaticity", Studies in health technology and informatics ,pp. 667-672, IOS press,2008.
[4] K.A. Navas and M. Sasikumar, "Survey of Medical Image Watermarking Algorithms", 4rth International Conference: Sciences of Electronic, Technologies of Information and Telecommunications,pp.1-6, Mar. 2007.
[5] K.A. Navas, M. Sasikumar and S. Sreevidya, "A benchmark for medical image watermarking", Proc. 6th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services,pp.237- 240, Jun. 2007.
[6] K.A. Navas, S.A. Thampy, and M. Sasikumar, "EPR Hiding in Medical Images for Telemedicine", International Journal of Biological, Biomedical and Medical Sciences, Vol.28, pp. 292-295, 2008.
[7] K.A. Navas, G. Issac, and M. Sasikumar, "Standards for EPR Data hiding", Proc. International Conference on Sensors, Signal Processing, Communication, Control and Instrumentation, Jan. 2008.
[8] A. Giakoumaki, S. Pavlopoulos, D. Koutsouris, "A Multiple Watermarking Scheme Applied to Health information Management", IEEE trans on info. tech. in biomedicine, vol.10, no.4, Oct. 2006.
[9] S. Dandapat, O. Chutatape and S.M. Krishnan, "Perceptual Model Based Data Embedding in Medical Images",International Conference on Image Processing, Vol.4,pp. 2315- 2318, Oct. 2004.
[10] X. Zhang, W. Lin and P. Xue, "Just-noticeable difference estimation with pixels in images",Journal of Visual Communication and Image Representation,Vol. 19, Issue 1,pp.30-41, Jan. 2008.
[11] G. Xie, M.N.S. Swamy and M.O. Ahmad, "Perceptual-shaping comparison of DWT-based pixel-wise masking model with DCT- based Watson model", International Conference on Image Processing, pp. 1381-1384, Oct. 2006.
[12] M. Li, R. Poovandran, and S. Narayanan, "Protecting patient privacy against unauthorized release of medical images in a group communication environment", Computerized Medical Imaging and Graphics, Vol. 29, pp.367-383. 2005.