High robustness image encryption scheme utilizing memristive hyperchaotic map and Manhattan distance

The popularity of UAVs in various fields has led to the proliferation of images, and the need for information security to protect these images is increasing. This paper proposes a unique highly robustness image encryption scheme founded upon a memristor enhanced Hénon map, designated as 3D-IHM. The proposed 3D-IHM is a hyperchaotic system that exhibits superior chaotic properties and initial value sensitivity, as evidenced by several performance tests. This makes it particularly suitable for image encryption applications. The encryption algorithm utilises the Manhattan distance as the basis for grouping image pixels, and the subsequent Manhattan distance permutation and diffusion can hide the image information well. Performance analysis shows that the obtained NPCR and UACI scores can pass the strict significance test. Robustness analysis shows that the algorithm can withstand different types and degrees of noise estimation, and even if 15% of the ciphertext data is lost, it is still capable of recovering the majority of the image information from the reconstructed image. Furthermore, the algorithm demonstrates superior performance in terms of encryption efficiency when compared to some of the most advanced algorithms currently in use.