A Novel Image Compression-Encryption Scheme Based on Chaos and Compression Sensing

Abstract

In this paper, a novel image compression–encryption hybrid algorithm is proposed. First, a Gauss random matrix and a random scrambling matrix are generated by using Chebyshev mapping and Logistic mapping, respectively. Then, based on the principle that a scrambling Gauss matrix is still a Gauss matrix, a compression scheme for ciphertext images is designed. It is dependent on the Gauss random matrix and the random scrambling matrix, which mainly consists of three parts: the permutation-based encryption using random scrambling matrix by Alice, the encoding with Gauss random matrix by Charlie, and the joint decryption and decoding by Bob. It has a special application scenario, that is, Alice requires semi integrity Charlie to transmit images to Bob through a channel. Experimental results show that the scheme has strong robustness against noise and chosen-plaintext attack, and further the peak signal-to-noise ratio (PSNR) and subjective visual quality of reconstructed images can be improved by comparing with the similar methods.

Keywords

• Compressed sensing
• Gauss measurement matrix
• random permutation matrix
• chaos mapping
• chosen plain text attack