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Image encryption based on compressive sensing and chaos systems
Optics and Laser Technology, 2020Recently, a new image encryption technique based on compressive sensing (CS) has been proposed. CS allows the signal to be sampled at a much lower rate than the Nyquist- Shannon rate. Furthermore, the signal can be sampled and compressed in a single step
A. H. Brahim, A. Pacha, N. H. Said
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2017
We consider the problem of sparse signal recovery in dynamic sensing scenarios. Specifically, we study the recovery of a sparse time-varying signal from linear measurements of a single static sensor that are taken at two different points in time. This setup can be modelled as observing a single signal using two different sensors – a real one and a ...
Dalitz, Robert +2 more
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We consider the problem of sparse signal recovery in dynamic sensing scenarios. Specifically, we study the recovery of a sparse time-varying signal from linear measurements of a single static sensor that are taken at two different points in time. This setup can be modelled as observing a single signal using two different sensors – a real one and a ...
Dalitz, Robert +2 more
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A fast image encryption algorithm based on compressive sensing and hyperchaotic map
Optics and lasers in engineering, 2019In this paper, we propose a new two-dimensional Sine improved Logistic iterative chaotic map with infinite collapse (ICMIC) modulation map (2D-SLIM) based on the improved two-dimensional closed-loop modulation coupling model.
Qiaoyun Xu, K. Sun, Chun Cao, Congxu Zhu
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An image compression and encryption algorithm based on chaotic system and compressive sensing
Optics and Laser Technology, 2019For a linear image encryption system, it is vulnerable to the chosen-plaintext attack. To overcome the weakness and reduce the correlation among pixels of the encryption image, an effective image compression and encryption algorithm based on chaotic ...
L. Gong +3 more
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A visually secure image encryption scheme based on parallel compressive sensing
Signal Processing, 2019It is generally recognized that encrypting an original image into meaningless cipher image is an ideal method to protect image information. However, during transmission, the meaningless cipher image would draw attention and thus attract attacks. Recently,
Hui Wang +4 more
semanticscholar +1 more source
IEEE Transactions on Information Theory, 2006
Summary: Suppose \(x\) is an unknown vector in \(\mathbb R^m\) (a digital image or signal); we plan to measure \(n\) general linear functionals of \(x\) and then reconstruct. If \(x\) is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements \(n\) can ...
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Summary: Suppose \(x\) is an unknown vector in \(\mathbb R^m\) (a digital image or signal); we plan to measure \(n\) general linear functionals of \(x\) and then reconstruct. If \(x\) is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements \(n\) can ...
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An optical image compression and encryption scheme based on compressive sensing and RSA algorithm
Optics and lasers in engineering, 2019Most of the image encryption algorithms are the private-key cryptosystem, in which the encryption process and the decryption process employ the same keys.
L. Gong +3 more
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Remote sensing image compression and encryption based on block compressive sensing and 2D-LCCCM
Nonlinear dynamics, 2022Shi Nan +3 more
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A novel triple-image encryption and hiding algorithm based on chaos, compressive sensing and 3D DCT
Information Sciences, 2021Xing-yuan Wang, Cheng Liu, D. Jiang
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Demosaicking with compressive sensing
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012Sparse signals can be recovered with less number of measurements compared to standard methods using Compressive Sensing (CS) theory. In digital cameras, color filter arrays (CFA) are used to sample each color band with less measurements than the normal. The color images are reconstructed using interpolation of measured pixel values.
Gürbüz, A. C., İlbeği, H.
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