An Image Segmentation Encryption Algorithm Based on Hybrid Chaotic System

Abstract

Image encryption is an effective technology to protect digital image confidentiality. This paper presents an image segmentation encryption algorithm based on a hybrid chaotic system. First, a chaotic sequence is obtained by iterating a Quantum Cellular Neural Network (QCNN), and then it is scrambled by a 4-D hyperchaotic system to generate a key pool. Second, the chaotic pointers generated by 3-D chaotic systems and QCNN with different initial values are used to get the keys for image segmentation, scrambling, and diffusion from the key pool. Then, the plain-image is divided into two blocks by the chaotic segmentation method and scrambled by intra-block and inter-block pixel exchange. In addition, two blocks are statically diffused, and the cipher-image is obtained by dynamic diffusing after combining the image blocks. Especially, the key pool increases the efficiency of the proposed algorithm, and chaotic segmentation reduces the cipher-image pixel correlation. Finally, the simulation results and performance analysis indicate that the proposed algorithm has a well-security, high sensitivity, and faster speed.