Joint image compression–encryption scheme using entropy coding and compressive sensing

被引:2
|
作者
Yanjie Song
Zhiliang Zhu
Wei Zhang
Li Guo
Xue Yang
Hai Yu
机构
[1] Northeastern University,Software College
[2] Northeastern University,School of Computer Science and Engineering
来源
Nonlinear Dynamics | 2019年 / 95卷
关键词
Joint image compression–encryption; Compressive sensing; Entropy coding; Chaos; Bit-plane;
D O I
暂无
中图分类号
学科分类号
摘要
Recently, compressive sensing (CS)-based joint compression–encryption schemes have been widely investigated due to their high efficiency and good security for images. However, the existing schemes typically have a lower compression ratio (CR), and there may be a flaw during their compression processes. Therefore, in this paper, according to the intrinsic features of images, we propose a novel compression architecture to enhance the CR. Meanwhile, based on this architecture, a joint image compression–encryption scheme using entropy coding and CS is designed to implement a complete compression and encryption process. In this joint scheme, a presented bit-level lossless compression–encryption algorithm based on entropy coding for the higher bit-planes is incorporated to improve the quality of the reconstructed image and ensure the security. Alternately, this joint scheme also contains an improved CS-based lossy compression–encryption algorithm for the lower bit-planes, which can guarantee the efficiency and security. Through the cooperation between the proposed lossless and lossy coding, the higher reconstruction performance can be achieved. SHA-256 is combined with all initial keys in the proposed joint scheme to generate the updated keys for chaos cryptosystem to maintain high security and resist some common attacks. Experimental and analytical results illustrate the superiority of the proposed joint scheme compared with the existing compression–encryption schemes and JPEG, as well as good encryption performance.
引用
收藏
页码:2235 / 2261
页数:26
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