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Image encryption and hiding algorithm based on compressive sensing and random numbers insertion  ( SCI-EXPANDED收录 EI收录)   被引量:125

文献类型:期刊文献

英文题名:Image encryption and hiding algorithm based on compressive sensing and random numbers insertion

作者:Ye, Guodong[1];Pan, Chen[1];Dong, Youxia[1];Shi, Yang[2];Huang, Xiaoling[1]

机构:[1]Guangdong Ocean Univ, Fac Math & Comp Sci, Zhanjiang 524088, Peoples R China;[2]Tongji Univ, Sch Software Engn, Shanghai 200092, Peoples R China

年份:2020

卷号:172

外文期刊名:SIGNAL PROCESSING

收录:SCI-EXPANDED(收录号:WOS:000531095200030)、、EI(收录号:20201108304619)、Scopus(收录号:2-s2.0-85081660810)、WOS

基金:The authors would like to thank the three anonymous reviewers for their valuable comments and the editor's helpful suggestions. This work was supported in part by the National Natural Science Foundations of China (No. 61702116, 61972103, 61772371), the Natural Science Foundation of Guangdong Province of China (No. 2019A1515011361), the Postgraduate Education Innovation Project of Guangdong Ocean University of China (No. 521005038), and the Project of Enhancing School with Innovation of Guangdong Ocean University of China (No. Q18306).

语种:英文

外文关键词:Image encryption; Compressive sensing; Random numbers insertion; Discrete wavelet transform

外文摘要:Most current image encryption algorithms encrypt plain images directly into meaningless cipher images. Visually, a few of them are vulnerable to illegal attacks on a few sharing platforms or open channels when being transmitted. Therefore, this paper proposes a new meaningful image encryption algorithm based on compressive sensing and information hiding technology, which hides the existence of the plain image and reduces the possibility of being attacked. Firstly, the discrete wavelet transform (DWT) is employed to sparse the plain image. This is followed by confusion operation on pixel positions, where logistic-tent map is employed to produce a confusion sequence. And then the image is compressed and encrypted by compressive sensing to form an intermediate cipher image. Here, measurement matrix is generated using low-dimension complex tent-sine system. To further enhance recovery quality, we suggest that the intermediate cipher image be filled with random numbers according to the compression ratio and confusing them to obtain the secret image. Finally, two-dimensional (2D) DWT of the carrier image is performed, followed by singular value decomposition. The singular values of the secret image are embedded into the singular values of the carrier image with certain embedding strength to obtain the final visually meaningful encrypted image. (C) 2020 Elsevier B.V. All rights reserved.

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