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Image-adaptive watermarking using maximum likelihood decoder for medical images

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Abstract

In this paper, a new medical image-adaptive watermarking technique is proposed in which embedding of the watermark is done in low frequency coefficients for achieving high robustness using an adjustable dynamic strength factor. The low frequency coefficients are modeled using Gaussian distribution to design a Maximum Likelihood (ML) decoder. The decoder recovers the watermark with the help of side information containing the adjustable dynamic strength factor, position of blocks (used for embedding), mean and variances of low frequency coefficients. The method contributes towards a highly flexible and easily adjustable dynamic strength factor for achieving the best imperceptibility with the highest robustness. The validity of the new technique is verified against various attacks and the results are compared with other watermarking schemes. The proposed technique is found to generate better results.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their insightful and constructive comments that greatly contributed to improving the quality of the paper. The authors are also indebted to the Editors for their generous support during the review process.

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Authors and Affiliations

  1. Thapar University, Patiala, Punjab, India

    Preeti Bhinder, Kulbir Singh & Neeru Jindal

  2. Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, India

    Preeti Bhinder

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  1. Preeti Bhinder
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  2. Kulbir Singh
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Correspondence to Neeru Jindal.

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Bhinder, P., Singh, K. & Jindal, N. Image-adaptive watermarking using maximum likelihood decoder for medical images. Multimed Tools Appl 77, 10303–10328 (2018). https://doi.org/10.1007/s11042-018-5635-z

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