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Snapshot compressed sensing: performance bounds and algorithms [article]

Shirin Jalali, Xin Yuan
2019 arXiv   pre-print
Snapshot compressed sensing (CS) refers to compressive imaging systems in which multiple frames are mapped into a single measurement frame.  ...  The proposed methods are iterative and employ compression codes to define and impose the structure of the desired signal. Theoretical convergence guarantees are derived for both algorithms.  ...  In this paper, we focus on and analyze such snapshot compressed sensing systems.  ... 
arXiv:1808.03661v2 fatcat:siuckxmbffbarc3x2pw2ka3ezy

Single snapshot DOA estimation using compressed sensing

Stefano Fortunati, Raffaele Grasso, Fulvio Gini, Maria Sabrina Greco
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
In particular, an estimation algorithm based on the emerging theory of Compressed Sensing (CS) is analyzed and its statistical properties are investigated.  ...  We show that, unlike the classical Fourier beamformer, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g. Capon and MUSIC).  ...  Recently, new estimation algorithms, based on the emerging field of the Compressed Sensing (CS) theory have been proposed in the array processing literature (see e.g. [14] , [15] and [16] ).  ... 
doi:10.1109/icassp.2014.6854009 dblp:conf/icassp/FortunatiGGG14 fatcat:lgrwh4chw5fz7gqohlhvqydx6y

Sparsity order estimation for single snapshot compressed sensing

F. Romer, A. Lavrenko, G. Del Galdo, T. Hotz, O. Arikan, R. S. Thoma
2014 2014 48th Asilomar Conference on Signals, Systems and Computers  
In this paper we discuss the estimation of the sparsity order for a Compressed Sensing scenario where only a single snapshot is available.  ...  We discuss the choice of the parameters and show that an increasing amount of block overlap improves the sparsity order estimation but it increases the coherence of the sensing matrix.  ...  Moreover, this would even allow us to adapt our reconstruction strategy, i.e., to choose a recovery algorithm whose performance and complexity is best suited to the current sparsity order.  ... 
doi:10.1109/acssc.2014.7094653 dblp:conf/acssc/RomerLGHAT14 fatcat:lznrfv56vje4fmhrfc7gfppati

Single-snapshot DOA estimation by using Compressed Sensing

Stefano Fortunati, Raffaele Grasso, Fulvio Gini, Maria S Greco, Kevin LePage
2014 EURASIP Journal on Advances in Signal Processing  
In particular, four estimation algorithms based on the theory of compressed sensing (CS), i.e., the classical ℓ 1 minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth  ...  We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case.  ...  Recently, new algorithms, based on the emerging field of the Compressed Sensing (CS) theory have been proposed in the array processing literature (see e.g., [16] [17] [18] ).  ... 
doi:10.1186/1687-6180-2014-120 fatcat:q3hxxsmeh5crjefzkqun7tpvke

Optimal arrays for compressed sensing in snapshot-mode radio interferometry

Clara Fannjiang
2013 Astronomy and Astrophysics  
A possible remedy can be found in the promising new theory of compressed sensing (CS), which allows for the accurate recovery of sparse signals from sub-Nyquist sampling given certain measurement conditions  ...  We provide an introductory assessment of optimal arrays for CS in snapshot-mode radio interferometry, using orthogonal matching pursuit (OMP), a widely used CS recovery algorithm similar in some respects  ...  The author is grateful for financial support of the work from the Intel Science Talent Search, the Intel International Science and Engineering Fair, and the Junior Science & Humanities Symposium.  ... 
doi:10.1051/0004-6361/201321079 fatcat:hyjquykhe5dfbb3umqs7wuwupa

Ensemble learning priors unfolding for scalable Snapshot Compressive Sensing [article]

Chengshuai Yang, Shiyu Zhang, Xin Yuan
2022 arXiv   pre-print
Snapshot compressive imaging (SCI) can record the 3D information by a 2D measurement and from this 2D measurement to reconstruct the original 3D information by reconstruction algorithm.  ...  Extensive results on both simulation and real datasets demonstrate the superiority of our proposed algorithm. The code and models will be released to the public.  ...  Conclusions and Future Work Inspired by ensemble learning and iterative based optimization algorithm, we develop the ensemble learning priors unfolding for scalable snapshot compressive imaging.  ... 
arXiv:2201.10419v1 fatcat:75xz6tbou5db3nmwejjbcqeasq

Plug-and-Play Algorithms for Large-scale Snapshot Compressive Imaging [article]

Xin Yuan, Yang Liu, Jinli Suo, Qionghai Dai
2020 arXiv   pre-print
Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D) images using a 2D sensor (detector) in a single snapshot.  ...  In this paper, we develop fast and flexible algorithms for SCI based on the plug-and-play (PnP) framework.  ...  Conclusions We proposed plug-and-play algorithms for the reconstruction of snapshot compressive video imaging systems.  ... 
arXiv:2003.13654v2 fatcat:uxgidxljxffdlnuhkvh5kcixdm

Multiple and single snapshot compressive beamforming

Peter Gerstoft, Angeliki Xenaki, Christoph F. Mecklenbräuker
2015 Journal of the Acoustical Society of America  
For a sound field observed on a sensor array, compressive sensing (CS) reconstructs the direction-of-arrival (DOA) of multiple sources using a sparsity constraint.  ...  Here, the sparse source distribution is derived using maximum a posteriori (MAP) estimates for both single and multiple snapshots.  ...  Algorithm for the LASSO path Although many algorithms exist for solving the LASSO problem, we have good experience with the new algorithm for compressive beamforming in Table I as it is reasonably fast  ... 
doi:10.1121/1.4929941 pmid:26520284 fatcat:adkycaduwfeljhccshgfhjlx2m

Unsupervised Spatial-spectral Network Learning for Hyperspectral Compressive Snapshot Reconstruction [article]

Yubao Sun, Ying Yang, Qingshan Liu, Mohan Kankanhalli
2021 arXiv   pre-print
Hyperspectral compressive imaging takes advantage of compressive sensing theory to achieve coded aperture snapshot measurement without temporal scanning, and the entire three-dimensional spatial-spectral  ...  Its core issue is how to reconstruct the underlying hyperspectral image using compressive sensing reconstruction algorithms.  ...  Under the framework of compressed sensing theory, [40] studies theoretical analysis of snapshot CS systems and demonstrates that the reconstruction error of the CASSI system is bounded. IV.  ... 
arXiv:2012.12086v2 fatcat:4tkqsqkx5be5ld4dlafkveih44

Adaptive Deep PnP Algorithm for Video Snapshot Compressive Imaging [article]

Zongliang Wu, Chengshuai Yang, Xiongfei Su, Xin Yuan
2022 arXiv   pre-print
Video Snapshot compressive imaging (SCI) is a promising technique to capture high-speed videos, which transforms the imaging speed from the detector to mask modulating and only needs a single measurement  ...  Extensive results on both simulation and real datasets verify the superiority of our adaptive deep PnP algorithm.  ...  Conclusions We have proposed an adaptive plug-and-play framework for video snapshot compressive imaging reconstruction.  ... 
arXiv:2201.05483v2 fatcat:3xty5lejfjgihe44a5hgx6r3ju

10-mega pixel snapshot compressive imaging with a hybrid coded aperture [article]

Zhihong Zhang, Chao Deng, Yang Liu, Xin Yuan, Jinli Suo, Qionghai Dai
2021 arXiv   pre-print
Towards this end, snapshot compressive imaging (SCI) was proposed as a promising solution to improve the throughput of imaging systems by compressive sampling and computational reconstruction.  ...  Both simulation and real data experiments verify the feasibility and performance of our proposed HCA-SCI scheme.  ...  The results demonstrate the feasibility of high through-483 put imaging under snapshot compressive sensing scheme and hold 484 great potential for future applications in industrial visual inspection or  ... 
arXiv:2106.15765v2 fatcat:i2gk4luyrregjow4lzjcz2qtnu

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging [article]

Zhuoyuan Wu, Jian Zhang, Chong Mou
2021 arXiv   pre-print
Snapshot compressive imaging (SCI) aims to record three-dimensional signals via a two-dimensional camera.  ...  For the sake of building a fast and accurate SCI recovery algorithm, we incorporate the interpretability of model-based methods and the speed of learning-based ones and present a novel dense deep unfolding  ...  Introduction As a major branch of compressive sensing (CS) [7, 45, 47] , snapshot compressive imaging (SCI) develops for the aim of capturing high dimensional signals such as video [21] or spectral  ... 
arXiv:2109.06548v1 fatcat:3ezhwljt5fgr5oo3jfcu3m4m54

Cost-aware compressive sensing for networked sensing systems

Liwen Xu, Xiaohong Hao, Nicholas D. Lane, Xin Liu, Thomas Moscibroda
2015 Proceedings of the 14th International Conference on Information Processing in Sensor Networks - IPSN '15  
We design Cost-Aware Compressive Sensing (CACS), which incorporates the cost-diversity of samples into the compressive sensing framework, and we apply CACS in networked sensing systems.  ...  with provable recovery bounds.  ...  This is in contrast to existing compressive sensing work, in which provable recovery lower bounds have been based on the sensing matrix and the so-called Restricted Isometry Property (RIP).  ... 
doi:10.1145/2737095.2737105 dblp:conf/ipsn/XuHLLM15 fatcat:ooctkep3prhdfotf5spqba4tau

COMPRESSIVE SENSING

Abhilasha Sharma
2020 International Journal of Engineering Technologies and Management Research  
This paper presents the basic concept of compressive sensing and area of applications, where we can apply this technique.  ...  Compressive sensing is a relatively new technique in the signal processing field which allows acquiring signals while taking few samples.  ...  Compressed sensing is used in single-pixel cameras. Single-pixel camera that takes stills using repeated snapshots of randomly chosen apertures from a grid.  ... 
doi:10.29121/ijetmr.v5.i2.2018.655 fatcat:4nsoeflis5g4vgspxzbssyq6hy

Research on Conventional Beamforming Based on Compressive Sensing

J. Shi, H.Y. Song, B.S. Liu, C.Y. Yang, M. Diao
2017 DEStech Transactions on Engineering and Technology Research  
With the rapid development of the theory and algorithms for sparse recovery in finite dimensions, compressive sensing has already inspired some notable investigation in the context of Direction Of Arrival  ...  Compressive sensing, or compressive sampling (for short, CS) is a novel sensing/sampling paradigm.  ...  Compressive sensing is a novel sensing/sampling paradigm that captures and represents compressible signals at a rate significantly below the Nyquist rate (Yonina & Gitta 2012) .  ... 
doi:10.12783/dtetr/mcemic2016/9511 fatcat:ix3qukmr2vhmrpxvvsr3dvfc6m
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