A Robust Medical Image Watermarking Approach Using Beta Chaotic Map, DWT, and SVD
Rayen Ben Salah, Mourad Zaied · 2023
In today’s era of rapid computer network advancements, an enormous volume of messages is exchanged daily, touching several sectors, including the medical field. While the Internet provides flexible communication capabilities, it also presents many security challenges including data theft, data duplication, data leakage, and copyright protection. One potential solution to address this issue is the application of watermarking. This paper presents a robust watermarking algorithm for medical images that combines the Beta Chaotic Map (BCM), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD). Initially, the watermark undergoes encryption using BCM. Subsequently, the medical image is decomposed into four sub-bands (LL, LH, HL, and HH) through DWT. The low-frequency region LL contains the embedded watermark information, which is obtained by computing the embedding singular value using SVD. In the extraction process, the watermarked medical image is decomposed using DWT, and the watermark is extracted by reversing the SVD. Finally, the watermark is decrypted by applying BCM. To ensure the invisibility of the watermark in the host image and robustness against various attacks (e.g., JPEG compression, JPEG2000 compression, sharpening, noise, and filtering), the algorithm employs metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). Experimental results validate the algorithm’s effectiveness through tests based on Normalized Correlation (NC).