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Medical image protection using a data-hiding technique based on integer wavelets

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Abstract

Maintaining the secrecy of sensitive data transferred over the Internet while restricting access to approved information is a significant security and protection challenge in telemedicine today. In this work, we present a trustworthy and blind watermarking approach for medical photographs using the Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD) to preserve the privacy of such information. The embedding capacity of contemporary integer wavelet transform (IWT) based watermarking systems may be constrained. To overcome this specific issue, the study offers an IWT-based secure big capacity watermarking method. According to experiment results on imperceptibility and resilience, the suggested technique efficiently preserves a significant amount of quality in watermarked images, and the watermark is resistant to the most common attacks in watermarking.

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The data used to support the findings of this study could be found freely here: https://odir2019.grand-challenge.org/

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Acknowledgment

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

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Authors and Affiliations

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

    Moad Med Sayah & Kafi Med Redouane

  2. Electronics Department, Faculty of Engineering Sciences, Laboratories of Automation and Signals of Annaba (LASA), Badji Mokhtar Annaba University, 23000, Annaba, Algeria

    Zermi Narima

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

    Khaldi Amine

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Correspondence to Khaldi Amine.

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Sayah, M.M., Narima, Z., Amine, K. et al. Medical image protection using a data-hiding technique based on integer wavelets. Multimed Tools Appl 83, 45843–45857 (2024). https://doi.org/10.1007/s11042-023-16771-2

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