Exploiting 3D fractal cube and chaos for effective multi-image compression and encryption

At present, some image compression and encryption algorithms have been presented to protect digital images by combining chaos and compressed sensing (CS). However, some of them still suffer from security and efficiency shortcomings. To solve these issues, a multi-image compression and encryption based on 3D fractal cube, CS and chaos is introduced in this paper. Firstly, the multiple plain images are sparsified by the Haar Wavelet Transform (HWT), and measured by CS to obtain the measurement value matrices. Herein, a four-wing hyperchaotic system is adopted to generate the measurement matrix for CS. Subsequently, a 3D fractal cube (3D-FC) is defined and generated iteratively by constructing the initial 3D-FC. Based on it, the obtained measurement value matrices are shuffled to reduce the high correlation between the adjacent pixels. Next, the cipher images are obtained after the cipher-associated adaptive diffusion based on GF (28) is performed on the confused image. Moreover, we have conducted extensive experiments to verify the encryption efficiency, compression performance, and security. Both simulation results and performance analysis confirm that the present algorithm has satisfactory performance in these aspects.