Results 161 to 170 of about 3,276,837 (200)

ADMM-CSNet: A Deep Learning Approach for Image Compressive Sensing

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Compressive sensing (CS) is an effective technique for reconstructing image from a small amount of sampled data. It has been widely applied in medical imaging, remote sensing, image compression, etc. In this paper, we propose two versions of a novel deep
Yan Yang, Jian Sun, Huibin Li, Zongben Xu   +3 more
semanticscholar   +1 more source

Compressive Sensing

2008 42nd Annual Conference on Information Sciences and Systems, 2008
Richard Baraniuk
semanticscholar   +3 more sources

Kronecker Compressive Sensing

IEEE Transactions on Image Processing, 2012
Compressive sensing (CS) is an emerging approach for the acquisition of signals having a sparse or compressible representation in some basis. While the CS literature has mostly focused on problems involving 1-D signals and 2-D images, many important applications involve multidimensional signals; the construction of sparsifying bases and measurement ...
Marco F, Duarte, Richard G, Baraniuk
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Accelerating SENSE using compressed sensing

Magnetic Resonance in Medicine, 2009
AbstractBoth parallel MRI and compressed sensing (CS) are emerging techniques to accelerate conventional MRI by reducing the number of acquired data. The combination of parallel MRI and CS for further acceleration is of great interest. In this paper, we propose a novel method to combine sensitivity encoding (SENSE), one of the standard methods for ...
Dong, Liang, Bo, Liu, Jiunjie, Wang, Leslie, Ying   +3 more
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Image encryption and hiding algorithm based on compressive sensing and random numbers insertion

Signal Processing, 2020
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.
G. Ye, Chen Pan, Youxia Dong, Yang Shi, Xiaoling Huang   +4 more
semanticscholar   +1 more source

An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding

, 2020
In this paper, an efficient visually meaningful image compression and encryption (VMICE) scheme is proposed by combining compressive sensing (CS) and Least Significant Bit (LSB) embedding.
Xiu-li Chai, Haiyang Wu, Zhihua Gan, Yushu Zhang, Yiran Chen, Kent W. Nixon   +5 more
semanticscholar   +1 more source

A robust meaningful image encryption scheme based on block compressive sensing and SVD embedding

Signal Processing, 2020
In this paper, an efficient and robust meaningful image encryption (MIE) scheme is developed by combining block compressive sensing (BCS) and singular value decomposition (SVD) embedding.
Liya Zhu, Huansheng Song, Xi Zhang, M. Yan, Tao Zhang, Xiaoyan Wang, Juan Xu   +6 more
semanticscholar   +1 more source

An effective image encryption algorithm based on compressive sensing and 2D-SLIM

Optics and lasers in engineering, 2020
This paper presents an image encryption algorithm based on the compressive sensing and a hyperchaotic map, which includes the permutation, compression and diffusion processes.
Qiaoyun Xu, K. Sun, Shaobo He, Congxu Zhu   +3 more
semanticscholar   +1 more source

A Compressive Sensing-Based Approach to End-to-End Network Traffic Reconstruction

IEEE Transactions on Network Science and Engineering, 2020
Estimation of end-to-end network traffic plays an important role in traffic engineering and network planning. The direct measurement of a network's traffic matrix consumes large amounts of network resources and is thus impractical in most cases.
Dingde Jiang, Wenjuan Wang, Lei Shi, Houbing Song   +3 more
semanticscholar   +1 more source

Foveated Compressed Sensing

Circuits, Systems, and Signal Processing, 2011
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