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Compressed Sensing for Biomedical Photoacoustic Imaging: A Review [PDF]

open access: yesSensors
Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging.
Yuanmao Wang   +3 more
doaj   +2 more sources

Single-Shot Compressed Imaging via Random Phase Modulation

open access: yesApplied Sciences, 2022
Compressed sensing (CS) provides an innovative framework for signal sampling, which enables accurate recovery of the sparse or compressible signal from a small set of linear measurements far fewer than the Nyquist rate in traditional signal processing ...
Cheng Zhang   +5 more
doaj   +1 more source

Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching

open access: yesIEEE Access, 2021
The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral imaging system. Compressed sensing technology is one of the important ways to solve this problem.
Hua Xiao, Zhongliang Wang, Xueying Cui
doaj   +1 more source

Algebraic compressed sensing

open access: yesApplied and Computational Harmonic Analysis, 2023
We introduce the broad subclass of algebraic compressed sensing problems, where structured signals are modeled either explicitly or implicitly via polynomials. This includes, for instance, low-rank matrix and tensor recovery. We employ powerful techniques from algebraic geometry to study well-posedness of sufficiently general compressed sensing ...
Breiding, Paul   +3 more
openaire   +2 more sources

From compression to compressed sensing [PDF]

open access: yes2013 IEEE International Symposium on Information Theory, 2013
Can compression algorithms be employed for recovering signals from their underdetermined set of linear measurements? Addressing this question is the first step towards applying compression algorithms for compressed sensing (CS). In this paper, we consider a family of compression algorithms $\mathcal{C}_r$, parametrized by rate $r$, for a compact class ...
Arian Maleki, Shirin Jalali
openaire   +4 more sources

Compression-Based Compressed Sensing [PDF]

open access: yesIEEE Transactions on Information Theory, 2017
Modern compression algorithms exploit complex structures that are present in signals to describe them very efficiently. On the other hand, the field of compressed sensing is built upon the observation that "structured" signals can be recovered from their under-determined set of linear projections.
Farideh E. Rezagah   +3 more
openaire   +2 more sources

Fully Learnable Model for Task-Driven Image Compressed Sensing

open access: yesSensors, 2021
This study primarily investigates image sensing at low sampling rates with convolutional neural networks (CNN) for specific applications. To improve the image acquisition efficiency in energy-limited systems, this study, inspired by compressed sensing ...
Bowen Zheng   +3 more
doaj   +1 more source

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

open access: yesEntropy, 2022
In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption.
Xiaomeng Song   +3 more
doaj   +1 more source

Compressed Sensing in Astronomy [PDF]

open access: yesIEEE Journal of Selected Topics in Signal Processing, 2008
Recent advances in signal processing have focused on the use of sparse representations in various applications. A new field of interest based on sparsity has recently emerged: compressed sensing. This theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory.
Jérôme Bobin   +2 more
openaire   +4 more sources

Distributed Compressed Hyperspectral Sensing Imaging Based on Spectral Unmixing

open access: yesSensors, 2020
The huge volume of hyperspectral imagery demands enormous computational resources, storage memory, and bandwidth between the sensor and the ground stations.
Zhongliang Wang, Hua Xiao
doaj   +1 more source

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