An Image Segmentation Encryption Algorithm Based on Hybrid Chaotic System

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.