Image compression and encryption algorithm based on compressive sensing and nonlinear diffusion

Abstract

Compressive sensing is widely used to image compression and encryption algorithms due to its high efficiency, but the existing algorithms have some flaws and insufficiency such as low reconstruction quality, small key space and weak security. Therefore, in this paper, a novel 5D chaotic system is proposed, which has larger key space and more complex key stream. According to the proposed 5D chaotic system, an image compression and encryption algorithm based on compressive sensing and nonlinear diffusion is proposed. In addition, in order to improve the image reconstruction quality of compressive sensing, an algorithm is proposed in this paper to optimize the measurement matrix of compressive sensing. Theoretical analysis shows that the proposed 5D chaotic system is chaotic and it shows many superior properties. The algorithm proposed to optimize the measurement matrix is also proved effective for reconstruction quality. The simulation results show that our algorithm has advantages in compression performance, key sensitivity, key space and time complexity, and it can also resist statistical attack and other common attacks.