A novel plaintext-related image encryption and compression method based on a new coupled map lattices model

Abstract

Abstract In this paper, we propose a new Sine-Logistic Map Coupled Map Lattices (SLMCML) model, which exhibits enhanced chaotic characteristics and more suitable for image encryption compared with the classical coupled map lattices. Based on the SLMCML system, we propose an image encryption and compression method. To improve the plaintext sensitivity of image cryptosystem, we propose a novel plaintext-related internal keys generation method, which can obviously improve the plaintext sensitivity of initial values of SLMCML system, thus improve the plaintext sensitivity of whole process of compression and encryption. Our proposed image encryption scheme contains several steps. Initially, the discrete wavelet transform (DWT) is utilized to convert original image into coefficient matrix. Then a plaintext relation method is constructed, which generate internal keys as initial values of SLMCML system. Next the coefficient matrix is permutated by permutation sequences generated by SLMCML system to cyclic shift for making the energy evenly distributed. Next the coefficient matrix is done sparse processing. The compressed sensing is employed to compress coefficient matrix. Subsequently, the compressive image is permutated with spiral traversal and twice zigzag transform. Finally, the permutated image is diffused with column diffusion to generate cipher image. Through some common security analyses, our proposed image encryption scheme has good security performance and excellent image recovery quality.