基于并行压缩感知与混沌映射的图像加密方案设计

朱礼亚; 张曦; 张亮

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基于并行压缩感知与混沌映射的图像加密方案设计

更新时间：2026-09-04

- 基于并行压缩感知与混沌映射的图像加密方案设计
- Design of image encryption scheme based on parallel compressive sensing and chaotic map
- 微电子学与计算机 2019年36卷第10期页码：96-102
- 作者机构：
  
  1. 长安大学电子与控制工程学院,陕西,西安,710064
  2. 空军工程大学航空工程学院,陕西,西安,710038
- 作者简介：
- 基金信息：
  
  陕西省自然科学基金 2018JQ6017中央高校基本科研业务费 300102328110
- DOI：
  中图分类号：
- 纸质出版：2019
- 稿件说明：
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朱礼亚, 张曦, 张亮. 基于并行压缩感知与混沌映射的图像加密方案设计[J]. 微电子学与计算机, 2019, 36(10): 96-102.

ZHU Li-ya, ZHANG Xi, ZHANG Liang. Design of image encryption scheme based on parallel compressive sensing and chaotic map[J]. 2019, 36(10): 96-102.
朱礼亚, 张曦, 张亮. 基于并行压缩感知与混沌映射的图像加密方案设计[J]. 微电子学与计算机, 2019, 36(10): 96-102. DOI：

ZHU Li-ya, ZHANG Xi, ZHANG Liang. Design of image encryption scheme based on parallel compressive sensing and chaotic map[J]. 2019, 36(10): 96-102. DOI：

摘要

为实现灰度图像的同步加密与压缩

将并行压缩感知技术与混沌理论相结合

提出了一种兼顾压缩性能与安全性能的加密方案.明文图像的小波系数矩阵在经过Arnold置乱之后

利用受控的随机分块权重测量矩阵进行线性压缩

然后进行量化和双向扩散得到密文图像.在加密过程中

Lorenz混沌系统产生的伪随机序列作为置乱、构造测量矩阵以及扩散过程的密码流.通过置乱稀疏系数及构造具备良好重建性能的测量矩阵

方案的压缩性能得到有效提升.通过一系列安全性能分析

验证了方案的可靠性及鲁棒性.

Abstract

To encrypt and compress the gray image simultaneously

a novel encryption scheme based on parallel compressive sensing and chaotic theory is proposed

which can form a balance between compression and security performance. Firstly

the wavelet coefficients of plain image are scrambled by Arnold permutation algorithm

and then compressed by the key-controlled partial random block weighing matrix. Finally

the cipher image is obtained after quantization and diffusion. Lorenz chaotic system is introduced to generate the key stream for permutation

construction of measurement matrix and diffusion. Via scrambling the sparse coefficients and constructing the measurement matrix with high reconstruction performance

the compression performance of scheme is enhanced. Moreover

the security and robustness are demonstrated by the security analyses.

关键词

Keywords

references

张勇.混沌数字图像加密[M].北京:清华大学出版社, 2016.

RachlinYaron, BaronDror. The secrecy of compressed sensing measurements [C]// 46th Annual Allerton Conference on Communication, Control, and Computing, Monticello: IEEE, 2008: 813-817.

HU G P, XIAO D, WANG Y, et al. An image coding scheme using parallel compressive sensing for simultaneous compression-encryption applications [J]. Journal of Visual Communication and Image Representation, 2017, 44: 116-127. DOI: 116

CHAI X L, ZHENG X Y, GAN Z H, et al. An image encryption algorithm based on chaotic system and compressive sensing [J]. Signal Processing, 2018, 148: 124-144. DOI: 124

ZHAO H, YE H, WANG R Y. The construction of measurement matrices based on block weighing matrix in compressed sensing [J]. Signal Processing, 2016, 123: 64-74. DOI: 64

ZHANG Y S, ZHOU J T, CHEN F, et al. Embedding cryptographic features in compressive sensing [J]. Neurocomputing, 2016, 205: 472-480. DOI: 472

DonohoDavid L. Compressed sensing [J].IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. DOI: 1289

ZHANG L Y, WONG K W, ZHANG Y S, et al. Bi-level protected compressive sampling [J]. IEEE Transactions on Multimedia, 2016, 18(9): 1720-1732. DOI: 1720

ZHANG Y. A chaotic system based image encryption scheme with identical encryption and decryption algorithm [J]. Chinese Journal of Electronics, 2017, 26(5): 1022-1031. DOI: 1022

CHEN J X, ZHANG Y, QI L, et al. Exploiting chaos-based compressed sensing and cryptographic algorithm for image encryption and compression [J]. Optics and Laser Technology, 2018, 99: 238-248. DOI: 238

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