<p>Image encryption is essential for securing visual content across digital channels, including medical imaging; hence, it is of utmost importance in IoT, communications, and medical imaging. The study of Cellular Automata (CA) has become widely recognised in image security owing to their abstraction of operations, their minimal resource requirements, and the system’s random-like behaviour, which can be traced back to straightforward rules. This paper provides an extensive review of CA-related image encryption techniques, including one-, two-, and three-dimensional CA models, rule-based transformation methods, and hybrid cryptosystems that use chaos, DNA encoding, and classical cryptography such as Advanced Encryption Standard (AES), Data Encryption Standard (DES), and Elliptic Curve Cryptography (ECC). The review classifies encryption processes by the use of permutation, diffusion, randomness, and key generation strategies. Moreover, it reveals security performance based on tests of entropy, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), Correlation Coefficient, Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), key sensitivity, and key space. The results indicate that CA-based encryption provides strong confusion and diffusion at low computational cost, making it suitable for real-time and resource-constrained environments. In addition, the paper points out difficulties in key management, high-resolution scalability, hardware efficiency, and resistance to new forms of attacks. It sketches out future pathways leading to brilliant CA rule creation, quantum-safe key incorporation, and hardware-friendly lightweight encryption frameworks.</p>