期刊
IEEE SIGNAL PROCESSING LETTERS
卷 29, 期 -, 页码 2033-2037出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2022.3209145
关键词
Ciphers; Image coding; Image reconstruction; Encryption; Privacy; Iterative algorithms; Approximation algorithms; Compressed sensing; nonlocal low-rank prior reconstruction; cipher-image coding; image encryption; encryption-then-compression
资金
- National Key R&D Program of China [2020YFB1805400]
- National Natural Science Foundation of China [62072063]
In this letter, a 2D compressed sensing (2DCS) scheme using nonlocal low-rank prior (NLP) reconstruction is proposed. By applying scrambling encryption and an iterative singular value thresholding (ISVT) algorithm, the proposed method outperforms previous CS-based methods in terms of R-D performance.
In recent years, cipher-image coding by using compressed sensing (CS) has became a hot topic. However, the ratio-distortion (R-D) performance of the previous methods are barely satisfactory. In order to address this concern, a 2D CS (2DCS) scheme by using nonlocal low-rank prior (NLP) reconstruction is proposed in this letter. Firstly, the scrambling encryption is applied to mask the plaintext image. Secondly, the cipher image is compressed by 2DCS. Lastly, an iterative singular value thresholding (ISVT) algorithm is developed, which can reconstruct the image effectively by exploring the NLP information of the image. Simulation results show that the proposed method outperforms the previous CS-based methods in terms of R-D performance.
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