<p>The growing risk of cyber threats highlights the need for advanced encryption methods, particularly to secure image data that exhibit high redundancy and strong pixel correlations.Conventional encryption techniques often fail to address the specific nature of image data, rendering them susceptible to security breaches. This proposed work introduces a novel encryption framework that combines a memristive quantum-inspired chaotic map with a Golden Jackal Optimization (GJO) algorithm to increase security, randomness, and computational efficiency. The proposed approach utilizes a memristor-based chaotic system that incorporates quantum-inspired properties such as superposition and entanglement to generate highly dynamic encryption sequences. By employing GJO, the chaotic parameters are fine-tuned in real time, maximizing key sensitivity, unpredictability, and robustness against attacks. The encryption process is further strengthened through pixel scrambling and diffusion mechanisms guided by optimized chaotic sequences, thereby improving resistance to differential and statistical attacks. Performance evaluations confirm the effectiveness of the proposed method, achieving an information entropy of 7.9989, a unified average changing intensity of 33.90%, and a number of pixels change rate of 99.94%, ensuring strong security and randomness. In addition, the model maintains minimal information loss, making it highly suitable for secure image transmission in applications such as defense, healthcare, and confidential communication.</p>