High-quality restoration image encryption using DCT frequency-domain compression coding and chaos

Abstract

AbstractWith the arrival of the age of big data, the amount and types of data in the process of information transmission have increased significantly, and the full-disk encryption mode used by traditional encryption algorithms has certain limitations of the times. In order to further improve the bandwidth efficiency of digital images in the transmission process and the information effectiveness of digital image transmission, this paper proposes an algorithm of high-quality restoration image encryption using DCT frequency-domain compression coding and chaos. Firstly, the image hash value is used for the generation of an encryption key with plaintext correlation, then lightweight chaos is generated based on the key to obtain a pseudo-random sequence. Secondly, the image is partitioned into subblock, and converted from time domain into frequency domain by employing Discrete Cosine Transform (DCT) on each block, then perform quantization operation based on frequency domain information to obtain DCT coefficient matrix. Thirdly, the direct current (DC) coefficients and alternating current (AC) coefficients are extracted in the DCT coefficient matrix and compressed by different encoding methods to obtain two sets of bitstream containing DC coefficient and AC coefficient information. Fourthly, permute the DC coefficient bit stream by the chaotic sequence, and reconstruct it with the AC coefficient bit stream to obtain the frequency domain ciphertext image. Finally, the chaotic sequence is used to diffuse ciphertext, and the processed hash value is hidden in the ciphertext to obtain the final ciphertext. The theoretical and experimental analysis showed that the key length reaches 341 bits, and the PSNR value of the restored image is close to 60, all of which satisfy the theoretical value. Therefore, the algorithm has the characteristics of high compression rate, high-quality image restoration large key space, strong plaintext sensitivity, strong key sensitivity and so on. Our method proposed in this paper is expected to provide a new idea for confidential and secure communication in the age of big data.