Green Compressive Sampling Reconstruction in IoT Networks [PDF]
Sensors, 2018 In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms.
Stefania Colonnese +5 more
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Speech Compressive Sampling Using Approximate Message Passing and a Markov Chain Prior [PDF]
Sensors, 2020 By means of compressive sampling (CS), a sparse signal can be efficiently recovered from its far fewer samples than that required by the Nyquist–Shannon sampling theorem.
Xiaoli Jia, Peilin Liu, Sumxin Jiang
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Informational Analysis for Compressive Sampling in Radar Imaging [PDF]
Sensors, 2015 Compressive sampling or compressed sensing (CS) works on the assumption of the sparsity or compressibility of the underlying signal, relies on the trans-informational capability of the measurement matrix employed and the resultant measurements, operates ...
Jingxiong Zhang, Ke Yang
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Sparsity and Incoherence in Compressive Sampling [PDF]
Inverse Problems, 2006 We consider the problem of reconstructing a sparse signal $x^0\in\R^n$ from a limited number of linear measurements. Given $m$ randomly selected samples of $U x^0$, where $U$ is an orthonormal matrix, we show that $\ell_1$ minimization recovers $x^0 ...
Baraniuk R G Davenport M DeVore R Wakin M +11 more
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Imaging via Compressive Sampling [Introduction to compressive sampling and recovery via convex programming] [PDF]
IEEE Signal Processing Magazine, 2008 There is an extensive body of literature on image compression, but the central concept is straightforward: we transform the image into an appropriate basis and then code only the important expansion coefficients.
Romberg, Justin
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Compressive sampling based on frequency saliency for remote sensing imaging [PDF]
Scientific Reports, 2017 In saliency-based compressive sampling (CS) for remote sensing image signals, the saliency information of images is used to allocate more sensing resources to salient regions than to non-salient regions.
Jin Li, Zilong Liu, Fengdeng Liu
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Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography [PDF]
BMC Medical Imaging, 2017 Background A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared
Tran Quang Huy +3 more
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New Approach Based on Compressive Sampling for Sample Rate Enhancement in DASs for Low-Cost Sensing Nodes [PDF]
Sensors, 2014 The paper deals with the problem of improving the maximum sample rate of analog-to-digital converters (ADCs) included in low cost wireless sensing nodes.
Francesco Bonavolontà +3 more
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PhotoniX, 2022 High-throughput imaging is highly desirable in intelligent analysis of computer vision tasks. In conventional design, throughput is limited by the separation between physical image capture and digital post processing.
Zhihong Zhang +7 more
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A reconfigurable real-time compressive-sampling camera for biological applications. [PDF]
PLoS ONE, 2011 Many applications in biology, such as long-term functional imaging of neural and cardiac systems, require continuous high-speed imaging. This is typically not possible, however, using commercially available systems.
Bo Fu, Mark C Pitter, Noah A Russell
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