An Image Compression-Encryption Algorithm Based on Cellular Neural Network and Compressive Sensing

Abstract

In this paper, an image encryption algorithm on the basis of cellular neural networks (CNN) and compressive sensing (CS) is proposed. Firstly, four CNN with hyper chaotic behavior is introduced to generate chaotic sequence. Then, the index of the sorted chaotic sequence is used to control the generation of measurement matrix in CS procedure. Moreover, Lissajous map is served to produce asymptotic deterministic random measurement matrix instead of the common random measurement matrix. In addition, the chaotic sequence is normalized to 8-bit integer to diffuse the result after applying CS operation on the plain image, and the image after compression and encryption is obtained. The simulation results and analysis verify the proposed algorithm owns good security and ideal performance.