Spectral & Memory Trade-Offs in Multiplexed Fourier Domain Chaotic Image Encryption

This work presents a Fourier-domain encryption scheme for multiplexed image databases that integrates virtual-optical multiplexing with chaotic diffusion. By combining chaotic encryption with spectral-domain symmetry reduction, the proposed approach secures large multiplexed image datasets while reducing memory requirements and preserving reconstruction fidelity. A dataset of 2025 grayscale images ($512\times 512$ pixels) is multiplexed and encrypted using linear chaotic transformations applied separately to the amplitude (A) and phase ($\varphi$) components. To improve storage efficiency, the symmetry conditions of both spectral components are exploited, allowing a reduced portion of the Fourier plane to be stored while preserving accurate reconstruction. A performance landscape relating the correlation coefficient (CC), memory consumption, and the retained Fourier-plane percentage (FPP) is constructed to identify stable operating regions that balance reconstruction fidelity and compression under increasing multiplexing load. The encryption key consists of a 22-symbol ASCII string from which 84 seed parameters for a deterministic pseudorandom chaotic map are derived. Security and sensitivity analyses demonstrate strong key dependence and resistance to statistical attacks, while maintaining high reconstruction fidelity. The proposed scheme provides an efficient and scalable solution for secure large-scale image repositories.