Adaptive Medical Image Watermarking Scheme Using Nature-Inspired Optimization Techniques (Particle Swarm Optimization) and Lifting Wavelet Transform for Enhanced Security and Privacy in Telemedicine

In telemedicine, safeguarding sensitive medical data has emerged as the most significant challenge to achieve security, privacy, and integrity in transmission. This paper introduces an adaptive scheme of medical image watermarking with nature-inspired optimization techniques such as particle swarm optimization (PSO) combined with lifting wavelet transform (LWT), aiming at providing robust and secure watermarking in medical images without affecting their diagnostic quality. The proposed framework includes encrypting watermarks within medical images while preserving diagnostic quality. The optimization of key parameters like embedding strength of PSO, balancing the perception and robustness against attacks like compression, noise, and cropping, ensures that frequency domain processing using the LWT has a good and precise localization. Better performance of experimental results compared to the existing methods were found in peak signal-to-noise ratio, structural similarity index measure, normalized correlation, and other robustness metrics. The approach here is adaptive and ensures the telemedicine requirements are complied with, keeping confidentiality and integrity intact. This is highly practical for securing medical images in a digital healthcare ecosystem.

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