Secure frequency-domain image compressed sensing with matrix-inversion-free recovery
Image encryption should be performed prior to image compression in many real-world applications. This results in the requirement of compressing the encrypted image. Compressed sensing (CS) is an attractive tool for compressing encrypted images. Unfortunately, most existing CS-based image encryption-...
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| Published in: | Optik (Stuttgart) Vol. 276; p. 170677 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier GmbH
01.04.2023
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| ISSN: | 0030-4026, 1618-1336 |
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| Abstract | Image encryption should be performed prior to image compression in many real-world applications. This results in the requirement of compressing the encrypted image. Compressed sensing (CS) is an attractive tool for compressing encrypted images. Unfortunately, most existing CS-based image encryption-then-compression (ETC) schemes face several critical challenges, such as low security, high-complexity sampling and recovery. Therefore, this paper presents a secure frequency-domain image CS scheme with matrix-inversion-free (MIF) recovery for ETC applications to address the above challenges. More specifically, the bilateral permutation and nonzero entry diffusion encryption operations are utilized to encrypt the frequency-domain image orderly. Surprisingly, the above two encryption operations do not compromise recovery performance with proper parameters. Then, the encrypted frequency-domain image is simultaneously compressed and sampled with low complexity by an untrusted bandwidth-constrained channel provider. Additionally, we design an accompanying access password as a defence layer, and it can further enhance security. Finally, an extension orthogonal matching pursuit (OMP) recovery algorithm is investigated by avoiding pseudo-inverse and multiple encryption and decryption to reduce computational complexity, named MIF OMP (MIFOMP). Theoretical analyses and simulation results demonstrate the proposed scheme can achieve high security, low-complexity sampling and recovery, and satisfy the expected recovery performance. |
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| AbstractList | Image encryption should be performed prior to image compression in many real-world applications. This results in the requirement of compressing the encrypted image. Compressed sensing (CS) is an attractive tool for compressing encrypted images. Unfortunately, most existing CS-based image encryption-then-compression (ETC) schemes face several critical challenges, such as low security, high-complexity sampling and recovery. Therefore, this paper presents a secure frequency-domain image CS scheme with matrix-inversion-free (MIF) recovery for ETC applications to address the above challenges. More specifically, the bilateral permutation and nonzero entry diffusion encryption operations are utilized to encrypt the frequency-domain image orderly. Surprisingly, the above two encryption operations do not compromise recovery performance with proper parameters. Then, the encrypted frequency-domain image is simultaneously compressed and sampled with low complexity by an untrusted bandwidth-constrained channel provider. Additionally, we design an accompanying access password as a defence layer, and it can further enhance security. Finally, an extension orthogonal matching pursuit (OMP) recovery algorithm is investigated by avoiding pseudo-inverse and multiple encryption and decryption to reduce computational complexity, named MIF OMP (MIFOMP). Theoretical analyses and simulation results demonstrate the proposed scheme can achieve high security, low-complexity sampling and recovery, and satisfy the expected recovery performance. |
| ArticleNumber | 170677 |
| Author | Xiao, Di Li, Xinyan Huang, Hui |
| Author_xml | – sequence: 1 givenname: Hui surname: Huang fullname: Huang, Hui organization: Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, College of Computer Science, Chongqing University, Chongqing 400044, China – sequence: 2 givenname: Di orcidid: 0000-0002-6958-5807 surname: Xiao fullname: Xiao, Di email: dixiao@cqu.edu.cn organization: Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, College of Computer Science, Chongqing University, Chongqing 400044, China – sequence: 3 givenname: Xinyan surname: Li fullname: Li, Xinyan organization: School of Mathematics and Statistics, Yangtze Normal University, Chongqing 408100, China |
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| Cites_doi | 10.1109/TIT.2007.909108 10.1016/j.ijleo.2022.169357 10.1109/TIT.2006.871582 10.1109/TMM.2020.3014489 10.1016/j.chaos.2022.112296 10.1109/TIT.2021.3088090 10.1016/j.ins.2016.09.045 10.1109/TSP.2004.833860 10.1587/transfun.E101.A.526 10.1109/TMM.2019.2931400 10.1016/j.sigpro.2020.107765 10.1109/TMI.2018.2820120 10.1109/TMM.2019.2923111 10.1109/LSP.2010.2052243 10.1007/s11071-018-4689-9 10.1016/j.optlastec.2016.02.018 10.1109/ACCESS.2016.2569421 10.1016/j.ijleo.2021.166748 10.1109/TVLSI.2019.2933722 10.1016/j.aej.2022.01.015 10.1007/s11704-022-1419-8 10.1016/j.neucom.2016.04.053 10.1016/j.ins.2020.10.007 10.1109/JIOT.2017.2781737 10.1016/j.chaos.2022.112215 |
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| Keywords | Nonzero entry diffusion encryption Matrix-inversion-free orthogonal matching pursuit Accompanying access password Encryption-then-compression Bilateral permutation |
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| Snippet | Image encryption should be performed prior to image compression in many real-world applications. This results in the requirement of compressing the encrypted... |
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| SubjectTerms | Accompanying access password Bilateral permutation Encryption-then-compression Matrix-inversion-free orthogonal matching pursuit Nonzero entry diffusion encryption |
| Title | Secure frequency-domain image compressed sensing with matrix-inversion-free recovery |
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