文献类型：期刊文献

英文题名：Image compression-hiding algorithm based on compressive sensing and integer wavelet transformation

作者：Ye, Guodong[1];Du, Simin[1];Huang, Xiaoling[1]

机构：[1]Guangdong Ocean Univ, Fac Math & Comp Sci, Zhanjiang 524088, Peoples R China

年份：2023

卷号：124

起止页码：576

外文期刊名：APPLIED MATHEMATICAL MODELLING

收录：SCI-EXPANDED(收录号：WOS:001060280700001)、、EI(收录号：20233414613340)、Scopus(收录号：2-s2.0-85168421457)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China (No. 61972103) , the Natural Science Foundation of Guangdong Province of China (No. 2023A1515011207) , the Special Project in Key Area of General University in Guangdong Province of China (No. 2020ZDZX3064) , and the Characteristic Innovation Project of General University in Guangdong Province of China (No. 2022KTSCX051) .

语种：英文

外文关键词：Image compression-hiding algorithm; Three-dimensional chaotic system; Two-dimensional compressive sensing; Getting model; Transformation model

外文摘要：In this paper, a three-dimensional chaotic system is proposed. Based on this chaotic system and two-dimensional compressive sensing, an asymmetric visually meaningful image compression hiding algorithm is presented. Firstly, in the keystream generation stage, a novel parameter transformation model is constructed to pick up the feature information from the plain image as the plaintext key. Then, Rivest-Shamir-Adleman algorithm is employed to encrypt the plaintext key into the ciphertext key seen as public key. Before generating the initial values for the chaotic system, a new initial value getting model is designed to transform both the plaintext and the ciphertext keys. After solving the chaotic system, the keystream is produced which is then used in the image encryption process. Secondly, in the compression and encryption phase, a novel key stream pre-processing model is built to generate new sequences with a confusion performed on the plain image. Then, a newly constructed measurement matrix is designed to do twodimensional compressive sensing on confusing the image to get measurements. Before obtaining the cipher image, a double diffusion operation is applied on these measurements. Thirdly, in the image hiding stage, the carrier image is performed by integer wavelet transformation to obtain coefficient matrices. Then, the cipher image is decomposed in decimal, getting the ones, tens and hundreds of pixels to form three bit matrices, of which are embedded into the three medium-high coefficient matrices of integer wavelet transformation, respectively. Finally, after performing inverse integer wavelet transformation, the carrier image containing secrets, i.e., visually meaningful encrypted image, is obtained. Experimental results also show that at a low compression ratio of 0.25, the normalized correlation coefficient between the original plain image and the recovered image is almost equal to one, while the peak signal-to-noise ratio between the carrier image containing secrets and its original carrier can reach as high as 42 dB. In addition, the proposed image compression-hiding algorithm performs good ability consideing the brute force attack and the cropping attack.