An Effective Visually Meaningful Image Encryption Based on Compressive Sensing and Multi-Objective Optimization Algorithm

With the swift rise in the number of digital images, their transmission and storage are facing severe challenges. Although traditional encryption algorithms can effectively protect image privacy, the noise-like features they generate may attract more attention from attackers. To address these problems, a new visually meaningful image encryption algorithm based on compressive sensing and a multi-objective optimization method is proposed. The proposed algorithm includes an improvement method for measurement matrix based on singular value decomposition and an advanced embedding method, and a multi-objective optimization algorithm is used for parameter selection. Simulation results show that the proposed algorithm performs well in reconstruction quality, visual security, and efficiency. Compared with existing algorithms, the proposed method demonstrates significant advantages in efficiency, reconstruction quality, embedding rate, and robustness.