ON SOME COMMON COMPRESSIVE SENSING RECOVERY ALGORITHMS AND APPLICATIONS

Anđela Draganić, Irena Orović, Srdjan Stanković

DOI Number
10.2298/FUEE1704477D
First page
477
Last page
510

Abstract


Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its’ common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with significantly reduced number of samples needed for accurate signal reconstruction. The basic ideas and motivation behind this approach are provided in the theoretical part of the paper. The commonly used algorithms for missing data reconstruction are presented. The Compressive Sensing applications have gained significant attention leading to an intensive growth of signal processing possibilities. Hence, some of the existing practical applications assuming different types of signals in real-world scenarios are described and analyzed as well.

Keywords

compressive sensing, optimization algorithms, sampling theorem, under-sampled data

Full Text:

PDF

References


G. Pope, “Compressive Sensing: a Summary of Reconstruction Algorithms”, Eidgenossische Technische Hochschule, Zurich, Switzerland, 2008.

E. Candes, J. Romberg, “l1-magic: Recovery of Sparse Signals via Convex Programming”, October 2005.

D. Donoho, “Compressed sensing,” IEEE Transactions on IT, vol. 52, no.4, 2006, pp. 1289 - 1306.

E. J. Candes, J. Romberg, T. Tao, "Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information," IEEE Transactions on Information Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.

LJ. Stankovic, M. Dakovic, S. Stankovic, I. Orovic, "Sparse Signal Processing," in the Book: Digital Signal Processing, L. Stankovic, CreateSpace, Amazon, 2015.

I. Orovic, V. Papic, C. Ioana, X. Li, S. Stankovic, "Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations," Mathematical Problems in Engineering, Review paper, 2016.

E. J. Candes and T. Tao, “Decoding by linear programming,” Information Theory, IEEE Transactions on, vol. 51, no. 12, pp. 4203–4215, 2005.

G. Davis, S. Mallat, and M. Avellaneda, “Adaptive greedy approximations,” Constructive approximation, vol. 13, no. 1, pp. 57–98, 1997.

Y. Arjoune, N. Kaabouch, H. El Ghazi, A. Tamtaoui, "Compressive sensing: Performance comparison of sparse recovery algorithms," In 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, 2017, pp. 1-7.

S. Stankovic, I. Orovic, M. Amin, "L-statistics based Modification of Reconstruction Algorithms for Compressive Sensing in the Presence of Impulse Noise," Signal Processing, vol.93, no.11, November 2013, pp. 2927-2931, 2013.

Y. C. Eldar and G. Kutyniok, "Compressed Sensing: Theory and Applications", Cambridge University Press, May 2012.

S. Stankovic, I. Orovic, E. Sejdic, "Multimedia Signals and Systems: Basic and Advance Algorithms for Signal Processing," Springer-Verlag, New York, 2015.

V.M. Patel and R. Chellappa, “Sparse Representations and Compressive Sensing for Imaging and Vision,” SpringerBriefs in Electrical and Computer Engineering, 2013.

T. Blumensath, M. E. Davies, “Iterative Thresholding for Sparse Approximations”, Journal of Fourier Analysis and Applications, vol. 14, no. 5-6, pp 629-654, December 2008.

T. Blumensath, M. E. Davies, "Gradient Pursuits," IEEE Transactions on Signal Processing, vol.56, no.6, pp.2370-2382, June 2008.

R. Mihajlovic, M. Scekic, A. Draganic, S. Stankovic, "An Analysis of CS Algorithms Efficiency for Sparse Communication Signals Reconstruction," In Proceedings of the 3rd Mediterranean Conference on Embedded Computing, MECO, 2014.

L. I. Rudin, S. Osher, E. Fatemi, “Nonlinear total variation based noise removal algorithms”, Physica D: Nonlinear Phenomena, vol. 60, Issues 1–4, 1 November 1992, pp. 259-268

S. Stankovic, I. Orovic, "Robust Complex-Time Distributions based on Reconstruction Algorithms," In Proceedings of the 2nd Mediterranean Conference on Embedded Computing MECO - 2013, Budva, Montenegro, 2013, pp. 105-108.

LJ. Stankovic, S. Stankovic, M. Amin, "Missing Samples Analysis in Signals for Applications to L-estimation and Compressive Sensing," Signal Processing, vol. 94, Jan 2014, pp. 401-408, 2014.

S. Stankovic, LJ. Stankovic, I. Orovic, "A relationship between the Robust Statistics Theory and Sparse Compressive Sensed Signals Reconstruction," IET Signal Processing, Special issue on Compressive Sensing and Robust Transforms, vol. 8, Issue 3, pp. 223 - 229, May, 2014

S. Bahmani, “Algorithms for Sparsity-Constrained Optimization”, Springer Theses, Series Volume 261, ISBN 978-3-319-01880-5, 2014. M.

T. Zhang, “Sparse Recovery with Orthogonal Matching Pursuit Under RIP,” IEEE Trans. on Information Theory, vol. 57, no. 9, pp. 6215-6221, 2011.

S. Stankovic, I. Orovic, LJ. Stankovic, A. Draganic, "Single-Iteration Algorithm for Compressive Sensing Reconstruction," Telfor Journal, vol. 6, no. 1, pp. 36-41, 2014.

A. Draganic, I. Orovic, N. Lekic, M. Dakovic, S. Stankovic, "Architecture for Single Iteration Reconstruction Algorithm," In Proceedings of the 4th Mediterranean Conference on Embedded Computing.

J. A. Tropp, A. C. Gilbert, “Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit,” IEEE Transaction on Information Theory, vol. 53, no.12, 2007.

LJ. Stanković, M. Daković, and S. Vujović, “Adaptive Variable Step Algorithm for Missing Samples Recovery in Sparse Signals,” IET Signal Processing, vol. 8, no. 3, pp. 246 -256, 2014.

S. Vujovic, M. Dakovic, I. Orovic, S. Stankovic, "An Architecture for Hardware Realization of Compressive Sensing Gradient Algorithm," In Proceedings of the 4th Mediterranean Conference on Embedded Computing MECO - 2015, Budva, Montenegro.

Y. Wang, J. Xiang, Q. Mo, S. He, “Compressed sparse time–frequency feature representation via compressive sensing and its applications in fault diagnosis”, Measurement, vol. 68, pp. 70–81, May 2015.

S. Stankovic, I. Orovic, "An Ideal OMP based Complex-Time Distribution," 2nd Mediterranean Conference on Embedded Computing MECO - 2013, pp. 109-112, June 2013, Budva, Montenegro.

Y. C. Eldar "Sampling Theory: Beyond Bandlimited Systems", Cambridge University Press, April 2015.

P. Flandrin, P. Borgnat, "Time-Frequency Energy Distributions Meet Compressed Sensing," IEEE Transactions on Signal Processing, vol.58, no.6, pp.2974, 2982, June 2010.

I. Orovic, S. Stankovic, T. Thayaparan, "Time-Frequency Based Instantaneous Frequency Estimation of Sparse Signals from an Incomplete Set of Samples," IET Signal Processing, Special issue on Compressive Sensing and Robust Transforms, vol. 8, Issue 3, pp. 239 - 245, May, 2014.

I. Orovic, S. Stankovic, M. Amin, "Compressive Sensing for Sparse Time-Frequency Representation of Nonstationary Signals in the Presence of Impulsive Noise," SPIE Defense, Security and Sensing, Baltimore, Maryland, United States, 2013.

P. Borgnat, and P. Flandrin, "Time-frequency localization from sparsity constraints," In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Proceesing ICASSP-08, Las Vegas (NV), 2008, pp. 3785–3788.

M. Brajović, B. Lutovac, I. Orović, M. Daković, S. Stanković, “Sparse Signal Recovery Based on Concentration Measures and Genetic Algorithm,” In Proceedings of the 13th Symposium on Neural Networks and Applications NEUREL 2016, Belgrade, Serbia, November 2016.

X. Li, G. Bi, “Time-frequency representation reconstruction based on the compressive sensing”, In Proceedings of the 9th IEEE Conference on Industrial Electronics and Applications, Hangzhou, 2014, pp. 1158-1162.

S. Stankovic, I. Orovic, M. Amin, "Compressed Sensing Based Robust Time-Frequency Representation for Signals in Heavy-Tailed Noise," In Proceedings of the Information Sciences, Signal Processing and their Applications, ISSPA 2012, Canada, 2012.

P. K. Mishra, R. Bharath, P. Rajalakshmi, U. B. Desai, "Compressive sensing ultrasound beamformed imaging in time and frequency domain," In Proceedings of the 17th International Conference on E-health Networking, Application & Services (HealthCom), Boston, MA, 2015, pp. 523-527.

I. Orovic, S. Stankovic, T. Thayaparan, LJ. Stankovic, "Multiwindow S-method for Instantaneous Frequency Estimation and its Application in Radar Signal Analysis," IET Signal Processing, vol. 4, no. 4, pp. 363-370, 2010

I. Orovic, S. Stankovic, "A Class of Highly Concentrated Time-Frequency Distributions Based on the Ambiguity Domain Representation and Complex-Lag Moment," EURASIP Journal on Advances in Signal Processing, vol. 2009, Article ID 935314, 9 pages, 2009.

S. Stankovic, I. Orovic, LJ. Stankovic, “Polynomial Fourier Domain as a Domain of Signal Sparsity”, Signal Processing, vol. 130, Issue C, pp. 243-253, January 2017.

S. Stankovic, I. Orovic, T. Pejakovic, M. Orovic, "Compressive sensing reconstruction of signals with sinusoidal phase modulation: application to radar micro-Doppler," In Proceedings of the 22nd Telecommunications Forum , TELFOR, 2014.

H. Su, Y. Zhang, "Time-frequency analysis based on Compressive Sensing," In Proceedings of the 2nd International Conference on Cloud Computing and Internet of Things (CCIOT), Dalian, 2016, pp. 138-142.

I. Volaric, V. Sucic, Z. Car, "A compressive sensing based method for cross-terms suppression in the time-frequency plane," In Proceedings of the IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE), Belgrade, 2015, pp. 1-4.

LJ. Stankovic, S. Stankovic, I. Orovic, M. Amin, "Robust Time-Frequency Analysis based on the L-estimation and Compressive Sensing," IEEE Signal Processing Letters, vol. 20, no. 5, pp. 499-502, 2013.

G. Hua, Y. Hiang, G. Bi, “When Compressive Sensing meets Data Hiding”, IEEE Signal Processing Letters, vol. 23, no. 4, April 2016.

A. Draganic, M. Brajovic, I. Orovic, S. Stankovic, "A Software Tool for Compressive Sensing based Time-Frequency Analysis," In Proceedings of the 57th International Symposium, ELMAR-2015, Zadar, Croatia, 2015.

I. Orovic, S. Stankovic, T. Chau, C. M. Steele, E. Sejdic, "Time-frequency analysis and Hermite projection method applied to swallowing accelerometry signals," EURASIP Journal on Advances in Signal Processing, vol. 2010, Article ID 323125, 7 pages, 2010.

A. Krylov, D. Korchagin, “Fast Hermite projection method,” In Proceedings of the 3rd International Conference on Image Analysis and Recognition (ICIAR ’06), vol. 1, pp. 329–338, Povoa de Varzim, Portugal, September 2006.

S. Stankovic, I. Orovic, A. Krylov, "The Two-Dimensional Hermite S-method for High Resolution Inverse Synthetic Aperture Radar Imaging Applications," IET Signal Processing, vol. 4, no. 4, pp. 352-362, 2010.

M. Brajović, I. Orović, M. Daković, S. Stanković, “Compressive Sensing of Signals Sparse in 2D Hermite Transform Domain,” 58th International Symposium ELMAR-2016, Zadar, Croatia, September 2016.

A. Sandryhaila, S. Saba, M. Püschel, J. Kovačević, “Efficient Compression of QRS Complexes Using Hermite Expansion,” IEEE Transactions on Signal Processing, vol. 60, no. 2, pp. 947-955, February 2012.

A. Draganić, I. Orović, S. Stanković, “Robust Hermite transform based on the L-estimate principle,” In Proceedings of the 23rd Telecommunications Forum, TELFOR 2015.

S. Stankovic, LJ. Stankovic, I. Orovic, "Compressive sensing approach in the Hermite transform domain," Mathematical Problems in Engineering, vol. 2015 (2015), Article ID 286590, 9 pages.

M. Brajovic, I. Orovic, M. Dakovic, S. Stankovic, "The Analysis of Missing Samples in Signals Sparse in the Hermite Transform Domain," In Proceedings of the 23rd Telecommunications Forum TELFOR, 2015, Belgrade, Serbia, 2015.

I. Orovic, S. Stankovic, "Improved Higher Order Robust Distributions based on Compressive Sensing Reconstruction," IET Signal Processing, vol. 8, Issue: 7, pp. 738 - 748, May 2014.

S. Stankovic, I. Orovic, LJ. Stankovic, "An Automated Signal Reconstruction Method based on Analysis of Compressive Sensed Signals in Noisy Environment," Signal Processing, vol. 104, Nov 2014, pp. 43 - 50, 2014.

M. G. Christensen, J. Østergaard, S. H. Jensen, "On compressed sensing and its application to speech and audio signals," Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2009, pp. 356-360.

M. Scekic, R. Mihajlovic, I. Orovic, S. Stankovic, "CS Performance Analysis for the Musical Signals Reconstruction," In Proceedings of the 3rd Mediterranean Conference on Embedded Computing, MECO, 2014.

D. Wu, W. P. Zhu, M. N. S. Swamy, "A compressive sensing method for noise reduction of speech and audio signals," In Proceedings of the IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), Seoul, 2011, pp. 1-4.

L. Sun, X. Shao, Z. Yang, "An Adaptive Multiscale Framework for Compressed Sensing of Speech Signal," In Proceedings of the 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, 2010, pp. 1-4.

M. Dakovic, LJ. Stankovic, S. Stankovic, "A Procedure for Optimal Pulse Selection Strategy in Radar Imaging Systems," In Proceedings of the International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), 19-22 September, Aachen, Germany, 2016.

A. Bacci, E. Giusti, D. Cataldo, S. Tomei, M. Martorella, "ISAR resolution enhancement via compressive sensing: A comparison with state of the art SR techniques," In Proceedings of the 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), Aachen, 2016, pp. 227-231.

S. Costanzo, A. Rocha, M. D. Migliore, “Compressed Sensing: Applications in Radar and Communications”, The Scientific World Journal, vol. 2016 (2016), Article ID 5407415, 2 pages, Editorial.

LJ. Stankovic, S. Stankovic, T. Thayaparan, M. Dakovic, I. Orovic, "Separation and Reconstruction of the Rigid Body and Micro-Doppler Signal in ISAR Part I-Theory ," IET Radar, Sonar & Navigation, vol. 9, no. 9, pp. 1147-1154, 2015.

LJ. Stankovic, S. Stankovic, T. Thayaparan, M. Dakovic, I. Orovic, "Separation and Reconstruction of the Rigid Body and Micro-Doppler Signal in ISAR Part II-Statistical Analysis," IET Radar, Sonar & Navigation, vol. 9, no. 9, pp. 1155-1161, 2015.

A. Draganic, I. Orovic, S. Stankovic, X. Li, "ISAR Reconstruction from Incomplete Data using Total Variation Optimization," In Proceedings of the 5th Mediterranean Conference on Embedded Computing, (MECO 2016).

L. C. Potter, E. Ertin, J. T. Parker, M. Cetin, "Sparsity and Compressed Sensing in Radar Imaging," In Proceedings of the IEEE, vol. 98, no.6, pp.1006-1020, June 2010.

M. Dakovic, LJ. Stankovic, S. Stankovic, "Gradient Algorithm Based ISAR Image Reconstruction From the Incomplete Dataset," In Proceedings of the 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa, 2015.

J. Ender, “On compressive sensing applied to radar”, Signal Processing, vol. 90, Issue 5, May 2010, pp. 1402–1414.

LJ. Stankovic, S. Stankovic, I. Orovic, Y. Zhang, "Time-Frequency Analysis of Micro-Doppler Signals Based on Compressive Sensing," Compressive Sensing for Urban Radar, Ed. M. Amin, CRC-Press, 2014.

LJ. Stankovic, I. Orovic, S. Stankovic, M. Amin, "Compressive Sensing Based Separation of Non-Stationary and Stationary Signals Overlapping in Time-Frequency," IEEE Transactions on Signal Processing, vol. 61, no. 18, pp. 4562-4572, Sept. 2013.

S. Stankovic, LJ. Stankovic, I. Orovic, "L-statistics combined with compressive sensing," SPIE Defense, Security and Sensing, Baltimore, Maryland, United States, 2013.

M. A. Hadi, S. Alshebeili, K. Jamil, F. E. Abd El-Samie, “Compressive sensing applied to radar systems: an overview”, Signal, Image and Video Processing, December 2015, Volume 9, Supplement 1, pp 25–39.

A. Draganic, I. Orovic, S. Stankovic, "Blind Signals Separation in wireless communications based on Compressive Sensing," In Proceedings of the 22nd Telecommunications Forum, TELFOR, 2014.

L. Zhang, M. Xing, C. W. Qiu J. Li, Z. Bao, “Achieving higher resolution ISAR imaging with limited pulses via compressed sampling,” IEEE Geoscience and Remote Sensing Letters, vol.6, no.3, pp.567–571, 2009.

I. Orovic, A. Draganic, S. Stankovic, "Sparse Time-Frequency Representation for Signals with Fast Varying Instantaneous Frequency," IET Radar, Sonar & Navigation, vol. 9, Issue 9, pp. 1260 – 1267.

S. Li, G. Zhao, W. Zhang, Q. Qiu, H. Sun, "ISAR Imaging by Two-Dimensional Convex Optimization-Based Compressive Sensing," IEEE Sensors Journal, vol. 16, no. 19, pp. 7088-7093, Oct.1, 2016.

P. Zhang, Z. Hu, R. C. Qiu, B. M. Sadler, “A Compressed Sensing Based UltraWideband Communication System,” In Proceedings of the IEEE International Conference on Communications, 14-18 June 2009.

A. Draganic, I. Orovic, S. Stankovic, M. Amin, "Rekonstrukcija FHSS signala zasnovana na principu kompresivnog odabiranja," In Proceedings of the TELFOR 2012, Belgrade, 2012

J. Meng, J. Ahmadi-Shokouh, H. Li, E. J. Charlson, Z. Han, S. Noghanian, E. Hossain, “Sampling Rate Reduction for 60 GHz UWB Communication using Compressive Sensing, ” In Proceedings of the Asilomar Conf. on Signals, Systems, and Computers, Monterey, California, November 2009.

A. Draganic, I. Orovic, S. Stankovic, X. Li, Z. Wang, "Reconstruction and classification of wireless signals based on Compressive Sensing approach," In Proceedings of the 5th Mediterranean Conference on Embedded Computing, (MECO 2016).

B. Jokanovic, M. Amin, S. Stankovic, "Instantaneous frequency and time-frequency signature estimation using compressive sensing," SPIE Defense, Security and Sensing, Baltimore, Maryland, United States, 2013, http://dx.doi.org/10.1117/12.2016636

C. Bernard, C. Ioana, I. Orovic, S. Stankovic, "Analysis of underwater signals with nonlinear time-frequency structures using warping based compressive sensing algorithm," In Proceedings of the MTS/IEEE North American OCEANS conference, October 2015, Washington, DC, United States, 2015.

I. Murgan, A. Digulescu, I. Candel, C. Ioana, “Compensation of position offset of acoustic transducers using compressive sensing concept”, In Proceedings of the OCEANS 2016 MTS/IEEE Monterey, Sep 2016, Monterey, United States. pp. 1-4.

I. Orovic, S. Stankovic, LJ. Stankovic, "Compressive Sensing Based Separation of LFM Signals," In Proceedings of the 56th International Symposium ELMAR 2014, Zadar, Croatia, 2014.

J. Musić, T. Marasović, V. Papić, I. Orović, S. Stanković, "Performance of Compressive Sensing Image Reconstruction for Search and Rescue," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 11, pp. 1739-1743, Nov. 2016.

J. Music, I. Orovic, T. Marasovic, V. Papic, S. Stankovic, "Gradient Compressive Sensing for Image Data Reduction in UAV based Search and Rescue in the Wild," Mathematical Problems in Engineering, November, 2016

A. Akbari, D. Mandache, M. Trocan and B. Granado, "Adaptive saliency-based compressive sensing image reconstruction," In Proceedings of the IEEE International Conference on Multimedia & Expo Workshops (ICMEW), Seattle, WA, 2016, pp. 1-6.

N. Eslahi, A. Aghagolzadeh, "Compressive Sensing Image Restoration Using Adaptive Curvelet Thresholding and Nonlocal Sparse Regularization," IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3126-3140, July 2016.

J. Wen, Z. Chen, Y. Han, J. D. Villasenor, S. Yang, "A compressive sensing image compression algorithm using quantized DCT and noiselet information," In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Dallas, TX, 2010, pp. 1294-1297.

I. Stankovic, I. Orovic, S. Stankovic, M. Dakovic, "Iterative Denoising of Sparse Images," In Proceedings of the 39th International Convention on Information and Communication Technology, Electronics and Microelectronics, (MIPRO 2016), 2016.

M. Medenica, S. Zukovic, A. Draganic, I. Orovic, S. Stankovic, "Comparison of the algorithms for CS image reconstruction," ETF Journal of Electrical Engineering 2014, 09/2014; vol. 20, no. 1, pp. 29-39.

C.-S. Lu, H.-W. Chen, “Compressive image sensing for fast recovery from limited samples: A variation on compressive sensing”, Information Sciences, vol. 325, 20 December 2015, Pages 33–47.

M. Maric, I. Orovic, S. Stankovic, "Compressive Sensing based image processing in TrapView pest monitoring system," In Proceedings of the 39th International Convention on Information and Communication Technology, Electronics and Microelectronics, (MIPRO 2016).

S. Stankovic, I. Orovic, "An Approach to 2D Signals Recovering in Compressive Sensing Context," Circuits Systems and Signal Processing, 2016.

Z. Zhu, K. Wahid, P. Babyn, D. Cooper, I. Pratt, Y. Carter, “Improved Compressed Sensing-Based Algorithm for Sparse-View CT Image Reconstruction”, Computational and Mathematical Methods in Medicine, vol. 2013 (2013), Article ID 185750, 15 pages.

I. Stankovic, I. Orovic, S. Stankovic, "Image Reconstruction from a Reduced Set of Pixels using a Simplified Gradient Algorithm," In Proceedings of the 22nd Telecommunications Forum TELFOR 2014, Belgrade, Serbia, 2014.

M. Lustig, D. Donoho, J. Pauly, “Sparse MRI: The application of compressed sensing for rapid MR imaging,” Magn. Reson. Med., vol. 58, no. 6, pp. 1182–1195, 2007

C. G. Graff, E. Y. Sidky, “Compressive sensing in medical imaging”, Applied Optics, 2015 Mar 10; vol. 54, no. 8, C23–C44.

J. M. Bioucas-Dias, M. A. T. Figueiredo, "A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration," IEEE Transactions on Image Processing, vol. 16, no. 12, pp. 2992-3004, Dec. 2007.

M. F. Duarte et al., "Single-Pixel Imaging via Compressive Sampling," IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 83-91, March 2008.

R. Fergus, A. Torralba, W. T. Freeman, “Random lens imaging”, MIT CSAIL Technical Report, September 2006.

M. Trakimas, R. D'Angelo, S. Aeron, T. Hancock, S. Sonkusale, “A Compressed Sensing Analog-to-Information Converter With Edge-Triggered SAR ADC Core”, IEEE Transactions on Circuits and Systems I: Regular Papers, pp. 1135- 1148, vol. 60, Issue: 5, 2013

M. Lustig, D.L Donoho, J.M Santos, J.M Pauly “Compressed Sensing MRI”, IEEE Signal Processing Magazine, 2008, vol. 25, no. 2, pp. 72-82.

M. Lustig, J.M. Santos, D.L. Donoho, and J.M. Pauly, “k-t Sparse: High frame rate dynamic MRI exploiting spatio-temporal sparsity,” In Proceedings of the 13th Annual Meeting ISMRM, Seattle, WA, 2006, p. 2420.

S. Zukovic, M. Medenica, A. Draganic, I. Orovic, S. Stankovic, "A Virtual Instrument for Compressive Sensing of Multimedia Signals," In Proceedings of the 56th International Symposium ELMAR 2014, Zadar, Croatia, 2014.

M. Hong, Y. Yu, H. Wang, F. Liu, S. Crozier “Compressed sensing MRI with singular value decomposition-based sparsity basis”, Physics in Medicine and Biology, vol. 56 (2011), pp. 6311–6325.

D. Craven, B. McGinley, L. Kilmartin, M. Glavin, E. Jones, "Compressed Sensing for Bioelectric Signals: A Review," IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 2, pp. 529-540, March 2015.

Y. Liu, M. De Vos, S. Van Huffel, "Compressed Sensing of Multichannel EEG Signals: The Simultaneous Cosparsity and Low-Rank Optimization," IEEE Transactions on Biomedical Engineering, vol. 62, no. 8, pp. 2055-2061, Aug. 2015.

A. M. Abdulghani, A. J. Casson, E. Rodriguez-Villegas, "Quantifying the Feasibility of Compressive Sensing in Portable Electroencephalography Systems," In Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009, San Diego, CA, 2009, pp. 319-328.

S. Senay, L. F. Chaparro, M. Sun, R. J. Sclabassi, "Compressive sensing and random filtering of EEG signals using slepian basis," In Proceedings of the 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, 2008.

Z. Zhang, T. P. Jung, S. Makeig, B. D. Rao, "Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware," IEEE Transactions on Biomedical Engineering, vol. 60, no. 1, pp. 221-224, Jan. 2013.

J. K. Pant, S. Krishnan, "Reconstruction of ECG signals for compressive sensing by promoting sparsity on the gradient," In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, BC, 2013, pp. 993-997.

L. F. Polanía, R. E. Carrillo, M. Blanco-Velasco, K. E. Barner, "Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems," IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 2, pp. 508-519, March 2015.

O. Kerdjidj, K. Ghanem, A. Amira, F. Harizi, F. Chouireb, "Real ECG signal acquisition with shimmer platform and using of compressed sensing techniques in the offline signal reconstruction," In Proceedings of the IEEE International Symposium on Antennas and Propagation (APSURSI), Fajardo, 2016, pp. 1179-1180.

K. Wilhelm, Y. Massoud, "Compressive sensing based classification of intramuscular electromyographic signals," In Proceedings of the IEEE International Symposium on Circuits and Systems, Seoul, 2012, pp. 273-276.

M. Brajović, I. Orović, M. Daković, S. Stanković, “Gradient-based signal reconstruction algorithm in the Hermite transform domain,” Electronics Letters, vol. 52, Issue 1, pp. 41-43, 2016.

M. Brajovic, I. Orovic, M. Dakovic, S. Stankovic, "On the Parameterization of Hermite Transform with Application to the Compression of QRS Complexes," Signal Processing, vol. 131, February 2017, Pages 113–119.

M. Brajovic, I. Orovic, S. Stankovic, "The Optimization of the Hermite transform: Application Perspectives and 2D Generalization," In Proceedings of the 24th Telecommunications Forum TELFOR 2016, November 2016, Belgrade, Serbia, 2016.

G. Teschke “Sparse Recovery and Compressive Sampling in Inverse and Ill-Posed Problems”, Lecture Notes.

J. Trzasko, A. Manduca, "Highly Undersampled Magnetic Resonance Image Reconstruction via Homotopic ell _{0} -Minimization," IEEE Transactions on Medical Imaging, vol. 28, no. 1, pp. 106-121, Jan. 2009.

P. Zhang, Z. Hu, R. C. Qiu, B. M. Sadler, "A Compressed Sensing Based Ultra-Wideband Communication System," In Proceedings of the IEEE International Conference on Communications, Dresden, 2009, pp. 1-5.

B. Zhang, X. Cheng, N. Zhang, Y. Cui, Y. Li, Q. Liang, “Sparse target counting and localization in sensor networks based on compressive sensing,” In Proceedings of the IEEE INFOCOM, 2011, pp. 2255–2263.

M. Weiss, “Passive WLAN radar network using compressed sensing,” In Proceedings of the IET International Conference on Radar Systems (Radar 2012), Glasgow, UK, 2012, pp. 1-6.

J. Bazerque, G. Giannakis, “Distributed spectrum sensing for cognitive radio networks by exploiting sparsity,” IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1847–1862, Mar. 2010.

M. Brajovic, A. Draganic, I. Orovic, S. Stankovic, "FHSS signal sparsification in the Hermite transform domain," In Proceedings of the 24th Telecommunications Forum TELFOR 2016, November 2016, Belgrade, Serbia, 2016.

Y. Lu, W. Guo, X. Wang, W. Wang, "Distributed Streaming Compressive Spectrum Sensing for Wide-Band Cognitive Radio Networks," In Proceedings of the IEEE 73rd Vehicular Technology Conference (VTC Spring), Yokohama, 2011, pp. 1-5.

I. Stanković, I. Orović, M. Daković, S. Stanković, “Denoising of Sparse Images in Impulsive Disturbance Environment,” Multimedia Tools and Applications, in print, 2017.

J. Wu, F. Liu, L. C. Jiao, X. Wang and B. Hou, "Multivariate Compressive Sensing for Image Reconstruction in the Wavelet Domain: Using Scale Mixture Models," IEEE Transactions on Image Processing, vol. 20, no. 12, pp. 3483-3494, Dec. 2011.

J. Bobin, J. L. Starck, R. Ottensamer, "Compressed Sensing in Astronomy," IEEE Journal of Selected Topics in Signal Processing, vol. 2, no. 5, pp. 718-726, Oct. 2008.

J. Bobin, J.-L. Starck, “Compressed sensing in astronomy and remote sensing: a data fusion perspective”, In Proc. SPIE 7446, Wavelets XIII, 74460I (September 04, 2009).

R. G. Baraniuk, T. Goldstein, A. C. Sankaranarayanan, C. Studer, A. Veeraraghavan, M. B. Wakin, "Compressive Video Sensing: Algorithms, architectures, and applications," IEEE Signal Processing Magazine, vol. 34, no. 1, pp. 52-66, Jan. 2017.

I. Orovic, S. Park, S. Stankovic, "Compressive sensing in Video applications," In Proceedings of the 21st Telecommunications Forum TELFOR, Novembar, 2013.

L.-W. Kang, C.-S. Lu, “Distributed compressive video sensing,” In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '09), 2009, pp. 1169–1172.

X. Liao, K. Li, J. Yin, “Separable data hiding in encrypted image based on compressive sensing and discrete Fourier transform”, Multimedia Tools and Applications, pp. 1-15, 2016.

M. W. Fakhr, “Robust Watermarking Using Compressed Sensing Framework with Application to MP3 Audio”, International Journal of Multimedia & Its Applications 2013.

X. Tang, Z. Ma, X. Niu, Y. Yang, "Compressive Sensing-Based Audio Semi-fragile Zero-Watermarking Algorithm," Chinese Journal of Electronics, vol. 24, no. 3, pp. 492-497, 07 2015.

I. Orovic, S. Stankovic, "Compressive Sampling and Image Watermarking," In Proceedings of the 55th International Symposium ELMAR 2013, Zadar, Croatia, Sept. 2013.

M. Orovic, T. Pejakovic, A. Draganic, S. Stankovic, "MRI watermarking in the Compressive Sensing context," In Proceedings of the 57th International Symposium ELMAR-2015, Zadar, Croatia, 2015.

I. Orovic, A. Draganic, S. Stankovic, "Compressive Sensing as a Watermarking Attack," In Proceedings of the 21st Telecommunications Forum TELFOR 2013, Novembar, 2013.


Refbacks

  • There are currently no refbacks.


ISSN: 0353-3670 (Print)

ISSN: 2217-5997 (Online)

COBISS.SR-ID 12826626