Efficient and Robust Medical Image Watermarking Based on Optimal Subband Tree Structuring and Discrete Fractional Fourier Transform

  • Anusha Chacko Karunya Institute of Technology and Science, Coimbatore, and Vimal Jyothi Engineering College, Chemperi
  • Shanty Chacko Karunya Institute of Technology and Science, Coimbatore

Abstract

In order to solve the security problems associated with medical information and improve the robustness of watermarking algorithms for medical images, a unique approach to watermarking based on block operations is presented. This study considers the medical images as the cover image, with the watermark logo considered secret information that needs to be protected over the wireless transmission in telemedicine. In the embedding phase, input with the discrete fractional Fourier transform is first applied to the input, and then level 2 wavelet decomposition is carried out to determine the optimal sub-band tree. For each tree node on level 2, the approximated and detailed coefficient is determined through the feature analysis perspective. The novelty of the adopted methodology is its simplified transformation and embedding process. Upon receiving a complex matrix, it separates the real part from imaginary part where block transformation is carried out for embedding the watermark pixels. In the extraction phase, just a reverse operation is performed. The watermarking evaluation is performed by simulating various image processing attacks on watermarked medical images. The simulation outcome demonstrates the effectiveness of that proposed watermarking scheme against various attacks. The proposed watermarking technique is robust under various attacks based on image statistics such as PSNR, BER, and the correlation coefficient.

Keywords

medical image, watermarking, discrete FFT, decomposition, security,

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Published
Oct 23, 2023
How to Cite
CHACKO, Anusha; CHACKO, Shanty. Efficient and Robust Medical Image Watermarking Based on Optimal Subband Tree Structuring and Discrete Fractional Fourier Transform. Computer Assisted Methods in Engineering and Science, [S.l.], v. 30, n. 4, p. 557–581, oct. 2023. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/547>. Date accessed: 21 june 2024. doi: http://dx.doi.org/10.24423/cames.547.
Section
[-] Computer-Aided Software Design for Multi-Concern Assurance