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Robust Watermarking Algorithm for Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition

Meng Yang1, Jingbing Li1,2,*, Uzair Aslam Bhatti1,2, Chunyan Shao1, Yen-Wei Chen3

1 School of Information and Communication Engineering, Hainan University, Haikou, 570228, China
2 State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, Haikou, 570228, China
3 Graduate School of Information Science and Engineering, Ritsumeikan University, Kyoto, 5258577, Japan

* Corresponding Author: Jingbing Li. Email: email

Computers, Materials & Continua 2023, 75(3), 5539-5554. https://doi.org/10.32604/cmc.2023.036904

Abstract

With the development of digitalization in healthcare, more and more information is delivered and stored in digital form, facilitating people’s lives significantly. In the meanwhile, privacy leakage and security issues come along with it. Zero watermarking can solve this problem well. To protect the security of medical information and improve the algorithm’s robustness, this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform (NSST) and Schur decomposition. Firstly, the low-frequency subband image of the original medical image is obtained by NSST and chunked. Secondly, the Schur decomposition of low-frequency blocks to get stable values, extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decomposition of each low-frequency block and constructing the transition matrix from it. Then, the mean of the matrix is compared to each element’s value, creating a feature matrix by combining perceptual hashing, and selecting 32 bits as the feature sequence. Finally, the feature vector is exclusive OR (XOR) operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center. Experimental data show that the Normalized Correlation (NC) values of watermarks extracted in random carrier medical images are above 0.5, with higher robustness than traditional algorithms, especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.

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Cite This Article

M. Yang, J. Li, U. A. Bhatti, C. Shao and Y. Chen, "Robust watermarking algorithm for medical images based on non-subsampled shearlet transform and schur decomposition," Computers, Materials & Continua, vol. 75, no.3, pp. 5539–5554, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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