Image compression and encryption scheme based on 2D compressive sensing and fractional Mellin transform

被引：236

作者：

Zhou, Nanrun ^{[1
,2
]}

Li, Haolin ^{[1
]}

Wang, Di ^{[1
]}

Pan, Shumin ^{[1
]}

Zhou, Zhihong ^{[3
]}

机构：

[1] Nanchang Univ, Dept Elect Informat Engn, Nanchang 330031, Peoples R China

[2] Beijing Univ Posts & Telecommun, Informat Secur Ctr, Beijing 100876, Peoples R China

[3] Shanghai Jiao Tong Univ, Shanghai Key Lab Integrate Adm Technol Informat S, Shanghai 200240, Peoples R China

来源：

OPTICS COMMUNICATIONS | 2015年 / 343卷

基金：

中国国家自然科学基金;

关键词：

Compressive sensing; Fractional Mellin transform; NSL0; algorithm; Logistic map; Image encryption; ONLY MULTIMEDIA CIPHERS; QUANTITATIVE CRYPTANALYSIS; INTERFERENCE; ALGORITHM; RESISTANCE; SYSTEM; ATTACK;

D O I：

10.1016/j.optcom.2014.12.084

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Most of the existing image encryption techniques bear security risks for taking linear transform or suffer encryption data expansion for adopting nonlinear transformation directly. To overcome these difficulties, a novel image compression-encryption scheme is proposed by combining 2D compressive sensing with nonlinear fractional Mellin transform. In this scheme, the original image is measured by measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the nonlinear fractional Mellin transform. The measurement matrices are controlled by chaos map. The Newton Smoothed l(0) Norm (NSL0) algorithm is adopted to obtain the decryption image. Simulation results verify the validity and the reliability of this scheme. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：10 / 21

页数：12

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