Traditional multi-secret sharing (MSS) schemes generate random shares to secure secrets, but their noisy appearance can raise suspicion. To address this, we present an advanced \((n+1, n+1)\) MSS scheme that generates meaningful, high-quality visual shares, reducing the risk of detection by attackers. Our scheme combines arithmetic Modulo, discrete wavelet transform (DWT), and particle swarm optimization (PSO), balancing security and visual appeal. The scheme operates through two main processes: the first involves the generation of randomized shares and the embedding of watermarks in the meaningful share generation process, while the second focuses on the extraction of randomized shares or watermark images from meaningful shares and the reconstruction of the secret during the secret reconstruction process. PSO optimizes embedding factors, achieving an ideal balance between imperceptibility and visual quality, often exceeding that of the meaningful cover images. Quantitative assessments with metrics like correlation, mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) show marked improvements in both robustness and visual quality of the shared images. This solution addresses the limitations of traditional schemes, providing a secure and visually appealing approach to multi-secret image sharing.
