Enhancing Security in Medical Imaging: Optimized Nature-Inspired Algorithms for Robust Watermarking in Gray scale Images
Vijay Krishna Pallaw, Pancham Kumar, Nawneet Kumar Pandey, Sandeep Kumar Singh · 2025
The significance of watermarking grayscale medical images lies chiefly in ensuring data security and integrity especially in telemedicine applications. Watermarking is enhanced by the use of nature based algorithms that relies on biological processes and natural phenomena as heuristics for optimizing both embedding and extraction functions. The watermarking capacity against different attacks like compression, noise or even geometric distortions can be greatly improved using these algorithms. A number of nature based algorithms employed in this paper include: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Firefly Algorithm (FA) that have significant potential for securing grayscale medical image watermarking systems. This approach makes use of the adaptive and evolutionary aspect of such algorithms thus achieving high level of imperceptibility together with robustness at the same time inputs are secured while maintaining quality disappointing images. Through a thorough comparison and analysis the paper shows how such algorithms can enhance watermarking techniques leading to a better defense against unauthorized access or alteration of sensitive medical data.