Work

Cipher-image compression by using compressive sensing and interweaving permutation

Year: 2024

Type: article

Abstract: Recently, compressing cipher images by using compressive sensing (CS) has attracted a lot of attention. However, the previous CS-based works cannot provide satisfactory compression performance. In this article, a cipher-image compression scheme based on CS and interweaving permutation is proposed to address this concern. Before image compression, the nature image is down-sampled to generate a lot of patches by using interweaving permutation firstly and then each patch is encrypted by a scrambling matrix, where each patch is a down-sampled image. In this way, the encrypted patches are highly correlated from one to each other since they preserve the correlation of the original patches. Therefore, we can encode the cipher image by employing CS and differential pulse-code modulation (DPCM) in an efficient way. To reconstruct the image effectively, an iterative shrinkage-thresholding (IST) algorithm is developed. Compared with the previous CS-based works, our scheme achieves better ratio-distortion (R-D) performance.

Source: Journal of King Saud University - Computer and Information Sciences

DOI: 10.1016/j.jksuci.2024.102046

Authors: Bo Zhang, Xiuling Li, Qiang Wang, Wenjing Zhang, Kai Wang

Language: English

Topic: Advanced Data Compression Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $1,450

Funders: Natural Science Foundation of Chongqing, Chongqing Municipal Education Commission

Awards: G7606170052, G8926056618