An efficient chaos-based image compression and encryption scheme using block compressive sensing and elementary cellular automata

In this paper, an efficient image compression and encryption scheme combining the parameter-varying chaotic system, elementary cellular automata (ECA) and block compressive sensing (BCS) is presented. The architecture of permutation, compression and re-permutation is adopted. Firstly, the plain image is transformed by DWT, and four block matrices are gotten, and they are a low-frequency block with important information and three high-frequency blocks with less important information. Secondly, ECA is used to scramble the four sparse block matrices, which can effectively change the position of the elements in the matrices and upgrade the confusion effect of the algorithm. Thirdly, according to the importance of each block, BCS is adopted to compress and encrypt four scrambled matrices with different compression ratios. In the BCS, the measurement matrices are constructed by a parameter-varying chaotic system, and thus few parameters may produce the large measurement matrices, which may effectively reduce memory space and transmission bandwidth. Finally, the four compressed matrices are recombined into a large matrix, and the cipher image is obtained by re-scrambling it. Moreover, the initial values of the chaotic system are produced by the SHA 256 hash value of the plain image, which makes the proposed encryption algorithm highly sensitive to the original image. Experimental results and performance analyses demonstrate its good security and robustness.

Duke Scholars

Author Yiran Chen Electrical and Computer Engineering