Robust Zero-Watermarking Algorithm for Medical Images Using Double-Tree Complex Wavelet Transform and Hessenberg Decomposition

Tongyuan Huang, Jia Xu, Yuling Yang and Baoru Han
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Tongyuan Huang: School of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China
Jia Xu: School of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China
Yuling Yang: School of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China
Baoru Han: College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China

Mathematics, 2022, vol. 10, issue 7, 1-19

Abstract: With the rapid development of smart medical care, copyright security for medical images is becoming increasingly important. To improve medical images storage and transmission safety, this paper proposes a robust zero-watermarking algorithm for medical images by fusing Dual-Tree Complex Wavelet Transform (DTCWT), Hessenberg decomposition, and Multi-level Discrete Cosine Transform (MDCT). First, the low-frequency sub-band of the medical image is obtained through the DTCWT and MDCT. Then Hessenberg decomposition is used to construct the visual feature vector. Meanwhile, the encryption of the watermarking image by combining cryptographic algorithms, third-party concepts, and chaotic sequences enhances the algorithm’s security. In the proposed algorithm, zero-watermarking technology is utilized to assure the medical images’ completeness. Compared with the existing algorithms, the proposed algorithm has good robustness and invisibility and can efficiently extract the watermarking image and resist different attacks.

Keywords: DTCWT; MDCT; Hessenberg decomposition; zero-watermarking; medical image (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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