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A wavelet-based watermarking for secure medical image transmission in telemedicine application

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Abstract

One method for securing multimedia data, and images in particular, from malicious attacks is watermarking, which involves adding a signature to the images. Traditional watermarking techniques, however, have drawbacks when used on sensitive images like those used in medicine. A reliable and blind watermarking method is suggested in this work to secure medical image exchanged in telemedicine. Medical image watermarking enables accurate patient identification, prevents scan confusion, and minimizes the risk of diagnostic mistakes that might have detrimental effects. In this method, three distinct transformations are used to get the frequency content of the picture. The low frequency subbands are subsequently subjected to Schur decomposition. In order to incorporate the watermark bits, the resultant upper triangular matrix values are modified. The suggested approaches effectively retain a considerable quality of watermarked images, according to experimental results on imperceptibility and robustness, and are resistant against various common attacks.

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Data availability

The data used to support the findings of this study could be found freely here: https://complexity.cecs.ucf.edu/cbis-ddsm/

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Acknowledgements

This work was supported by “ La Direction Générale de la Recherche Scientifque et du Développement Technologique (DGRSDT)” of Algeria.

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Authors and Affiliations

  1. Computer Science Department, Faculty of Sciences and Technology, Artificial Intelligence and Information Technology Laboratory (LINATI), University of Kasdi Merbah, 30000, Ouargla, Algeria

    Khaldi Amine

  2. Department of Electronics, Faculty of Sciences and Technology, Electrical Engineering Laboratory, University of Kasdi Merbah, 30000, Ouargla, Algeria

    Kafi Med Redouane & Moad Med Sayah

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  1. Khaldi Amine
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Correspondence to Khaldi Amine.

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Amine, K., Redouane, K.M. & Sayah, M.M. A wavelet-based watermarking for secure medical image transmission in telemedicine application. Multimed Tools Appl 82, 35401–35417 (2023). https://doi.org/10.1007/s11042-023-14792-5

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