Hyper Coupled Map Lattices for Hiding Multiple Images

Rasa Smidtaite, Jurate Ragulskiene, Liepa Bikulciene, Minvydas Ragulskis and Jesus M. Munoz-Pacheco

Complexity, 2023, vol. 2023, 1-20

Abstract: The concept of a hyper coupled map lattice (CML) is presented in this paper. The complexity of the lattice is increased not by adding another spatial dimension of the lattice but by replacing scalar nodal variables by multidimensional square matrices of iterative variables. The proposed scheme exploits the nonlinear effects of the spatiotemporal divergence induced by nilpotent nodal matrices to generate separate secret images at different discrete moments of time during the evolution of the CML. The time variable plays the primary role in the decoding stage of the scheme. The carrying capacity of the proposed scheme is n−1 different dichotomous digital images, where n is the dimension of the nilpotent nodal matrices. Computational experiments are used to demonstrate the efficacy of the proposed scheme.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8831078

DOI: 10.1155/2023/8831078

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