An novel dynamic compressed sensing method for image encryption based on a new coupled map lattices model

In this paper, a new logistic-sine coupled map lattices (LSSCML) is proposed, which has a large parameter space and all lattices are in stable chaotic state. The characteristics of LSSCML system better satisfy the cryptography compared with the traditional coupled map lattices (CML) model. Moreover, we propose a dynamic compressed sensing method, which significantly improves compression performance and efficiency. Based on the LSSCML system and dynamic compressed sensing, an image compression and encryption scheme is proposed. It contains several steps. Firstly, the plain information is associated with external keys to generate initial values of LSSCML system which used to generate a group of control sequence for overall process of image encryption and compression. Then plain image matrix is converted to coefficient matrix by discrete wavelet transform. Next, a group of measurement matrix for dynamic compressed sensing which structured according to different compression ratio are generated by LSSCML system. Subsequently, the coefficient matrix is compressed by dynamic compressed sensing, and the compressed matrix is grouping quantized to generate quantized matrix. Finally, we proposed a Fisher-Yates simultaneous permutation-diffusion algorithm to do diffusion and permutation of quantized matrix. The test results show that our proposed image cryptosystem has excellent compression and security performance.