5.5.7.3.3 Compressive Sensing, Compressive Imaging, Compressed Sensing, Compression, Reconstruction

Chapter Contents (Back)
Compressive Sensing. Compressed Sensing. See also Other Space Variant Sensors and Models. Signals having sparse representations in some basis can be represented by with a few random projections of the signals. Sample a sparse signal at a rate that is ower than the required Nyquist rate.

Donoho, D.L.,
Compressed sensing,
IT(52), No. 4, 2006, pp. 1289-1306. BibRef 0600

Babacan, S.D., Molina, R., Katsaggelos, A.K.,
Bayesian Compressive Sensing Using Laplace Priors,
IP(19), No. 1, January 2010, pp. 53-63.
IEEE DOI 1001
See also Blind Deconvolution Using a Variational Approach to Parameter, Image, and Blur Estimation. See also Variational Bayesian Blind Deconvolution Using a Total Variation Prior. BibRef

Babacan, S.D.[S. Derin], Ansorge, R.[Reto], Luessi, M.[Martin], Mataran, P.R., Molina, R.[Rafael], Katsaggelos, A.K.[Aggelos K.],
Compressive Light Field Sensing,
IP(21), No. 12, December 2012, pp. 4746-4757.
IEEE DOI 1212
BibRef
Earlier: A1, A3, A3, A5, A6, Only:
Compressive sensing of light fields,
ICIP09(2337-2340).
IEEE DOI 0911
BibRef

Tsiligianni, E., Kondi, L.P.[Lisimachos P.], Katsaggelos, A.K.[Aggelos K.],
Preconditioning for Underdetermined Linear Systems with Sparse Solutions,
SPLetters(22), No. 9, September 2015, pp. 1239-1243.
IEEE DOI 1503
compressed sensing BibRef

He, L., Chen, H., Carin, L.,
Tree-Structured Compressive Sensing With Variational Bayesian Analysis,
SPLetters(17), No. 1, January 2010, pp. 233-236.
IEEE DOI 1001
BibRef

Romberg, J.K.[Justin K.],
Compressive Sensing By Random Convolution,
SIIMS(2), No. 4, 2009, pp. 1098-1128.
DOI Link 1002
compressive sensing; random matrices; L_1 regularization BibRef

Muise, R.[Robert],
Compressive Imaging: An Application,
SIIMS(2), No. 4, 2009, pp. 1255-1276.
DOI Link 1002
compressive imaging; persistent surveillance; image multiplexing Field of view imaging, field of regard imaging. Limit the area to process to improve times. BibRef

Han, B.[Bing], Wu, F.[Feng], Wu, D.P.[Da-Peng],
Image representation by compressive sensing for visual sensor networks,
JVCIR(21), No. 4, May 2010, pp. 325-333.
Elsevier DOI 1006
BibRef
Earlier:
Image representation by compressed sensing,
ICIP08(1344-1347).
IEEE DOI 0810
Image representation; Compressive sensing; Random sampling; Projection onto convex sets; Convex optimization; Image decomposition; Interpolation; Image reconstruction BibRef

Baraniuk, R.G., Candes, E., Elad, M., Ma, Y.,
Applications of Sparse Representation and Compressive Sensing,
PIEEE(98), No. 6, June 2010, pp. 906-909.
IEEE DOI 1006
BibRef

Baraniuk, R.G.[Richard G.], Cevher, V., Wakin, M.B.[Michael B.],
Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective,
PIEEE(98), No. 6, June 2010, pp. 959-971.
IEEE DOI 1006
BibRef

Duarte, M.F.[Marco F.], Davenport, M.A.[Mark A.], Wakin, M.B.[Michael B.], Laska, J.N.[Jason N.], Takhar, D.[Dharmpal], Kelly, K.F.[Kevin F.], Baraniuk, R.G.[Richard G.],
Multiscale Random Projections for Compressive Classification,
ICIP07(VI: 161-164).
IEEE DOI 0709
BibRef

Wakin, M.B., Laska, J.N., Duarte, M.F., Baron, D., Sarvotham, S., Takhar, D., Kelly, K.F., Baraniuk, R.G.,
An Architecture for Compressive Imaging,
ICIP06(1273-1276).
IEEE DOI 0610
BibRef

Duarte, M.F., Baraniuk, R.G.,
Kronecker Compressive Sensing,
IP(21), No. 2, February 2012, pp. 494-504.
IEEE DOI 1201
BibRef

Elad, M., Figueiredo, M.A.T., Ma, Y.,
On the Role of Sparse and Redundant Representations in Image Processing,
PIEEE(98), No. 6, June 2010, pp. 972-982.
IEEE DOI 1006
BibRef

Fadili, M.J., Starck, J.L., Bobin, J., Moudden, Y.,
Image Decomposition and Separation Using Sparse Representations: An Overview,
PIEEE(98), No. 6, June 2010, pp. 983-994.
IEEE DOI 1006
BibRef

Jacques, L.[Laurent], Hammond, D.K.[David Kenric], Fadili, M.J.[M. Jalal],
Weighted fidelity in non-uniformly quantized compressed sensing,
ICIP11(1921-1924).
IEEE DOI 1201
BibRef
Earlier:
De-Quantizing Compressed Sensing with non-Gaussian constraints,
ICIP09(1465-1468).
IEEE DOI 0911
BibRef

Bobin, J., Candes, E.J.,
A fast and accurate first-order algorithm for compressed sensing,
ICIP09(1457-1460).
IEEE DOI 0911
BibRef

Bajwa, W.U., Haupt, J., Sayeed, A.M., Nowak, R.,
Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels,
PIEEE(98), No. 6, June 2010, pp. 1058-1076.
IEEE DOI 1006
BibRef

Yang, A.Y., Gastpar, M., Bajcsy, R., Sastry, S.S.,
Distributed Sensor Perception via Sparse Representation,
PIEEE(98), No. 6, June 2010, pp. 1077-1088.
IEEE DOI 1006
BibRef

Robucci, R., Gray, J.D., Chiu, L.K., Romberg, J.K., Hasler, P.,
Compressive Sensing on a CMOS Separable-Transform Image Sensor,
PIEEE(98), No. 6, June 2010, pp. 1089-1101.
IEEE DOI 1006
BibRef

Yu, L., Barbot, J.P., Zheng, G., Sun, H.,
Compressive Sensing With Chaotic Sequence,
SPLetters(17), No. 8, August 2010, pp. 731-734.
IEEE DOI 1007
BibRef

Fannjiang, A.C.[Albert C.], Strohmer, T.[Thomas], Yan, P.C.[Peng-Chong],
Compressed Remote Sensing Of Sparse Objects,
SIIMS(3), No. 3, 2010, pp. 595-618.
DOI Link compressed sensing; incoherence; threshold aperture; Rayleigh resolution; random sensor array BibRef 1000

Wang, Y.L.[Yi-Lun], Yin, W.T.[Wo-Tao],
Sparse Signal Reconstruction Via Iterative Support Detection,
SIIMS(3), No. 3, 2010, pp. 462-491.
DOI Link compressed sensing; L_1 minimization; iterative support detection; basis pursuit BibRef 1000

Veeraraghavan, A.[Ashok], Reddy, D.[Dikpal], Raskar, R.[Ramesh],
Coded Strobing Photography: Compressive Sensing of High Speed Periodic Videos,
PAMI(33), No. 4, April 2011, pp. 671-686.
IEEE DOI 1103
via temporal modulation, capture high-speed video beyond capability of low-frame-rate camera. Strobe coded projections. BibRef

Reddy, D.[Dikpal], Veeraraghavan, A.[Ashok], Chellappa, R.[Rama],
P2C2: Programmable pixel compressive camera for high speed imaging,
CVPR11(329-336).
IEEE DOI 1106
BibRef

Asif, M.S.[M. Salman], Reddy, D.[Dikpal], Boufounos, P.T.[Petros T.], Veeraraghavan, A.[Ashok],
Streaming Compressive Sensing for high-speed periodic videos,
ICIP10(3373-3376).
IEEE DOI 1009
BibRef

Edwards, J.,
Focus on Compressive Sensing,
SPMag(28), No. 2, 2011, pp. 11-13.
IEEE DOI 1103
Special Reports. Brief survey. BibRef

Ashok, A.[Amit], Neifeld, M.A.[Mark A.],
Compressive imaging: hybrid measurement basis design,
JOSA-A(28), No. 6, June 2011, pp. 1041-1050.
WWW Link. 1101
BibRef

Ni, K.Y.[Kang-Yu], Datta, S.[Somantika], Mahanti, P.[Prasun], Roudenko, S.[Svetlana], Cochran, D.[Douglas],
Efficient Deterministic Compressed Sensing for Images with Chirps and Reed-Muller Codes,
SIIMS(4), No. 3, 2011, pp. 931-953.
WWW Link. 1110
BibRef

Li, B.[Bo], Shen, Y.[Yi], Li, J.[Jia],
Dictionaries Construction Using Alternating Projection Method in Compressive Sensing,
SPLetters(18), No. 11, November 2011, pp. 663-666.
IEEE DOI 1112
BibRef

Chen, W., Rodrigues, M.R.D., Wassell, I.J.,
On the Use of Unit-Norm Tight Frames to Improve the Average MSE Performance in Compressive Sensing Applications,
SPLetters(19), No. 1, January 2012, pp. 8-11.
IEEE DOI 1112
BibRef

Chen, W.[Wei], Wassell, I.J., Rodrigues, M.R.D.,
Dictionary Design for Distributed Compressive Sensing,
SPLetters(22), No. 1, January 2015, pp. 95-99.
IEEE DOI 1410
compressed sensing BibRef

Abou Saleh, A., Chan, W.Y., Alajaji, F.,
Compressed Sensing With Nonlinear Analog Mapping in a Noisy Environment,
SPLetters(19), No. 1, January 2012, pp. 39-42.
IEEE DOI 1112
BibRef

Yang, Z., Zhang, C., Xie, L.,
On Phase Transition of Compressed Sensing in the Complex Domain,
SPLetters(19), No. 1, January 2012, pp. 47-50.
IEEE DOI 1112
BibRef

Wu, X., Dong, W., Zhang, X., Shi, G.,
Model-Assisted Adaptive Recovery of Compressed Sensing with Imaging Applications,
IP(21), No. 2, February 2012, pp. 451-458.
IEEE DOI 1201
BibRef

Hong, S.[Seokbeom], Park, H.[Hosung], Shin, B.[Beomkyu], No, J.S.[Jong-Seon], Chung, H.[Habong],
A New Performance Measure Using k -Set Correlation for Compressed Sensing Matrices,
SPLetters(19), No. 3, March 2012, pp. 143-146.
IEEE DOI 1202
BibRef

Fannjiang, A.[Albert], Liao, W.J.[Wen-Jing],
Coherence Pattern-Guided Compressive Sensing with Unresolved Grids,
SIIMS(5), No. 1 2012, pp. 179.
DOI Link 1203
BibRef

Fu, C.J.[Chang-Jun], Ji, X.Y.[Xiang-Yang], Dai, Q.H.[Qiong-Hai],
Adaptive Compressed Sensing Recovery Utilizing the Property of Signal's Autocorrelations,
IP(21), No. 5, May 2012, pp. 2369-2378.
IEEE DOI 1204
BibRef

Wang, L., Wu, X., Shi, G.,
Binned Progressive Quantization for Compressive Sensing,
IP(21), No. 6, June 2012, pp. 2980-2990.
IEEE DOI 1202
BibRef

Zou, J., Fu, Y., Xie, S.,
A Block Fixed Point Continuation Algorithm for Block-Sparse Reconstruction,
SPLetters(19), No. 6, June 2012, pp. 364-367.
IEEE DOI 1202
BibRef

Blanchard, J.D., Davies, M.E.,
Recovery Guarantees for Rank Aware Pursuits,
SPLetters(19), No. 7, July 2012, pp. 427-430.
IEEE DOI 1206
Sparse recovery in sparse multiple measurement vector. BibRef

Xiao, Y.H.[Yun-Hai], Song, H.N.[Hui-Na],
An Inexact Alternating Directions Algorithm for Constrained Total Variation Regularized Compressive Sensing Problems,
JMIV(44), No. 2, October 2012, pp. 114-127.
WWW Link. 1206
BibRef

Guo, W.H.[Wei-Hong], Yin, W.T.[Wo-Tao],
Edge Guided Reconstruction for Compressive Imaging,
SIIMS(5), No. 3 2012, pp. 809-834.
DOI Link 1208
BibRef

Sidiropoulos, N.D., Kyrillidis, A.,
Multi-Way Compressed Sensing for Sparse Low-Rank Tensors,
SPLetters(19), No. 11, November 2012, pp. 757-760.
IEEE DOI 1210
BibRef

Bourquard, A., Unser, M.,
Binary Compressed Imaging,
IP(22), No. 3, March 2013, pp. 1042-1055.
IEEE DOI 1302
BibRef

Zhang, X.[Xue], Wang, A.[Anhong], Zeng, B.[Bing], Liu, L.[Lei], Liu, Z.[Zhuo],
Adaptive Block-Wise Compressive Image Sensing Based on Visual Perception,
IEICE(E96-D), No. 2, February 2013, pp. 383-386.
WWW Link. 1301
BibRef

Lee, H.K.[Hyung-Keuk], Oh, H.[Heeseok], Lee, S.H.[Sang-Hoon], Bovik, A.C.,
Visually Weighted Compressive Sensing: Measurement and Reconstruction,
IP(22), No. 4, April 2013, pp. 1444-1455.
IEEE DOI 1303
BibRef
Earlier: A1, A2, A3, Only:
A new block compressive sensing to control the number of measurements,
ICIP11(2713-2716).
IEEE DOI 1201
BibRef

Zhang, X.Y.[Xiao-Ya], Li, S.[Song],
Compressed Sensing via Dual Frame Based L_1-Analysis With Weibull Matrices,
SPLetters(20), No. 3, March 2013, pp. 265-268.
IEEE DOI 1303
BibRef

Wu, R., Huang, W., Chen, D.R.,
The Exact Support Recovery of Sparse Signals With Noise via Orthogonal Matching Pursuit,
SPLetters(20), No. 4, April 2013, pp. 403-406.
IEEE DOI 1303
BibRef

Liu, Y., Li, M., Pados, D.A.,
Motion-Aware Decoding of Compressed-Sensed Video,
CirSysVideo(23), No. 3, March 2013, pp. 438-444.
IEEE DOI 1303
BibRef

Liu, Y., Pados, D.A.,
Compressed-Sensed-Domain L1-PCA Video Surveillance,
MultMed(18), No. 3, March 2016, pp. 351-363.
IEEE DOI 1603
Computational complexity BibRef

Yu, X., Baek, S.J.,
Sufficient Conditions on Stable Recovery of Sparse Signals With Partial Support Information,
SPLetters(20), No. 5, May 2013, pp. 539-542.
IEEE DOI 1304
BibRef

Patel, V.M.[Vishal M.], Chellappa, R.[Rama],
Sparse Representations and Compressive Sensing for Imaging and Vision,
Springer2013. ISBN 978-1-4614-6380-1.


WWW Link. 1304
Applied to biometrics. BibRef

Yang, Z.[Zhili], Jacob, M.,
Nonlocal Regularization of Inverse Problems: A Unified Variational Framework,
IP(22), No. 8, 2013, pp. 3192-3203.
IEEE DOI 1307
concave programming; compressive sensing; current schemes; robust distance metrics; Noise reduction; nonconvex; nonlocal means BibRef

Carrillo, R.E., McEwen, J.D., van de Ville, D., Thiran, J.P., Wiaux, Y.,
Sparsity Averaging for Compressive Imaging,
SPLetters(20), No. 6, 2013, pp. 591-594.
IEEE DOI 1307
Gaussian processes; single orthonormal basis; spread spectrum scheme BibRef

Auria, A.[Anna], Carrillo, R.E.[Rafael E.], Thiran, J.P.[Jean-Philippe], Wiaux, Y.[Yves],
Sparsity in tensor optimization for optical-interferometric imaging,
ICIP14(6026-6030)
IEEE DOI 1502
Image reconstruction BibRef

Sun, B.[Biao], Chen, Q.[Qian], Xu, X.[Xinxin], He, Y.[Yun], Jiang, J.J.[Jian-Jun],
Permuted and Filtered Spectrum Compressive Sensing,
SPLetters(20), No. 7, 2013, pp. 685-688.
IEEE DOI OFDM modulation; Fourier coefficient; OFDM 1307
BibRef

Du, X.P.[Xin-Peng], Cheng, L.Z.[Li-Zhi], Liu, L.F.[Lu-Feng],
A Swarm Intelligence Algorithm for Joint Sparse Recovery,
SPLetters(20), No. 6, 2013, pp. 611-614.
IEEE DOI 1307
Gaussian processes; compressed sensing theory BibRef

Wu, X.F.[Xiao-Fu], Yang, Z.[Zhen],
Verification-Based Interval-Passing Algorithm for Compressed Sensing,
SPLetters(20), No. 10, 2013, pp. 933-936.
IEEE DOI 1309
iterative methods BibRef

Fei, X.[Xuan], Wei, Z.H.[Zhi-Hui], Xiao, L.[Liang],
Iterative Directional Total Variation Refinement for Compressive Sensing Image Reconstruction,
SPLetters(20), No. 11, 2013, pp. 1070-1073.
IEEE DOI 1310
compressed sensing BibRef

Satpathi, S., Das, R.L., Chakraborty, M.,
Improving the Bound on the RIP Constant in Generalized Orthogonal Matching Pursuit,
SPLetters(20), No. 11, 2013, pp. 1074-1077.
IEEE DOI 1310
compressive sensing greedy recovery algorithm BibRef

Yu, N.Y., Zhao, N.,
Deterministic Construction of Real-Valued Ternary Sensing Matrices Using Optical Orthogonal Codes,
SPLetters(20), No. 11, 2013, pp. 1106-1109.
IEEE DOI 1310
Coherence BibRef

Shen, Y., Fang, J., Li, H.,
Exact Reconstruction Analysis of Log-Sum Minimization for Compressed Sensing,
SPLetters(20), No. 12, 2013, pp. 1223-1226.
IEEE DOI 1311
Compressed sensing BibRef

Krahmer, F., Ward, R.,
Stable and Robust Sampling Strategies for Compressive Imaging,
IP(23), No. 2, February 2014, pp. 612-622.
IEEE DOI 1402
Fourier transforms BibRef

Huang, T.Y.[Tian-Yao], Liu, Y.M.[Yi-Min], Meng, H.D.[Hua-Dong], Wang, X.[Xiqin],
Adaptive Compressed Sensing via Minimizing Cramer-Rao Bound,
SPLetters(21), No. 3, March 2014, pp. 270-274.
IEEE DOI 1403
adaptive signal processing BibRef

Foucart, S., Koslicki, D.,
Sparse Recovery by Means of Nonnegative Least Squares,
SPLetters(21), No. 4, April 2014, pp. 498-502.
IEEE DOI 1403
Compressed sensing BibRef

Foucart, S., Lecué, G.,
An IHT Algorithm for Sparse Recovery From Subexponential Measurements,
SPLetters(24), No. 9, September 2017, pp. 1280-1283.
IEEE DOI 1708
compressed sensing, minimisation, probability, IHT algorithm, classical restricted isometry property, independent subexponential random variables, L1-minimization, matrix, probability, subexponential measurements, uniform sparse recovery, Compressive sensing, restricted isometry property, sparse recovery, subexponential random variable BibRef

Yu, N.Y.[Nam Yul], Gan, L.[Lu],
Convolutional Compressed Sensing Using Decimated Sidelnikov Sequences,
SPLetters(21), No. 5, May 2014, pp. 591-594.
IEEE DOI 1404
Gaussian processes BibRef

Fang, J., Li, J., Shen, Y., Li, H., Li, S.,
Super-Resolution Compressed Sensing: An Iterative Reweighted Algorithm for Joint Parameter Learning and Sparse Signal Recovery,
SPLetters(21), No. 6, June 2014, pp. 761-765.
IEEE DOI 1404
Compressed sensing BibRef

Mohades, M.M., Mohades, A., Tadaion, A.,
A Reed-Solomon Code Based Measurement Matrix with Small Coherence,
SPLetters(21), No. 7, July 2014, pp. 839-843.
IEEE DOI 1405
Coherence BibRef

Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming], Li, X.[Xin], Ma, Y.[Yi], Huang, F.[Feng],
Compressive Sensing via Nonlocal Low-Rank Regularization,
IP(23), No. 8, August 2014, pp. 3618-3632.
IEEE DOI 1408
biomedical MRI BibRef

Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming], Li, X.[Xin], Peng, K., Wu, J., Guo, Z.,
Color-Guided Depth Recovery via Joint Local Structural and Nonlocal Low-Rank Regularization,
MultMed(19), No. 2, February 2017, pp. 293-301.
IEEE DOI 1702
computational geometry BibRef

Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming], Hu, X.C.[Xiao-Cheng], Ma, Y.[Yi],
Nonlocal Sparse and Low-Rank Regularization for Optical Flow Estimation,
IP(23), No. 10, October 2014, pp. 4527-4538.
IEEE DOI 1410
image sequences BibRef

Feng, J.M.[Joe-Mei], Krahmer, F.,
An RIP-Based Approach to Sigma-Delta Quantization for Compressed Sensing,
SPLetters(21), No. 11, November 2014, pp. 1351-1355.
IEEE DOI 1408
compressed sensing BibRef

Lou, J.T.[Jing-Tao], Li, Y.L.[Yong-Le], Liu, Y.[Yu], Tan, S.[Shuren], Zhang, M.J.[Mao-Jun],
Omni-gradient-based total variation minimisation for sparse reconstruction of omni-directional image,
IET-IPR(8), No. 7, July 2014, pp. 397-405.
DOI Link 1408
compressed sensing BibRef

Li, Y.[Yun], Sankaranarayanan, A.C.[Aswin C.], Xu, L.[Lina], Baraniuk, R.[Richard], Kelly, K.F.[Kevin F.],
Realization of hybrid compressive imaging strategies,
JOSA-A(31), No. 8, August 2014, pp. 1716-1720.
DOI Link 1408
Inverse problems; Computational imaging BibRef

Friedland, S., Li, Q.[Qun], Schonfeld, D.,
Compressive Sensing of Sparse Tensors,
IP(23), No. 10, October 2014, pp. 4438-4447.
IEEE DOI 1410
compressed sensing Compare with Kronecker compressive sensing and multiway compressive sensing. KC is better compression, this is faster. BibRef

Lu, Z.Q.[Zhen-Qi], Ying, R.D.[Ren-Dong], Jiang, S.X.[Sum-Xin], Liu, P.L.[Pei-Lin], Yu, W.X.[Wen-Xian],
Distributed Compressed Sensing off the Grid,
SPLetters(22), No. 1, January 2015, pp. 105-109.
IEEE DOI 1410
compressed sensing BibRef

Rousseau, S., Helbert, D., Carre, P., Blanc-Talon, J.,
Compressive Pattern Matching on Multispectral Data,
GeoRS(52), No. 12, December 2014, pp. 7581-7592.
IEEE DOI 1410
compressed sensing BibRef

Ma, J.J.[Jun-Jie], Yuan, X.J.[Xiao-Jun], Ping, L.[Li],
Turbo Compressed Sensing with Partial DFT Sensing Matrix,
SPLetters(22), No. 2, February 2015, pp. 158-161.
IEEE DOI 1410
compressed sensing BibRef

Ma, J.J.[Jun-Jie], Yuan, X.J.[Xiao-Jun], Ping, L.[Li],
On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices,
SPLetters(22), No. 10, October 2015, pp. 1580-1584.
IEEE DOI 1506
compressed sensing BibRef

Cloninger, A., Czaja, W., Bai, R., Basser, P.,
Solving 2D Fredholm Integral from Incomplete Measurements Using Compressive Sensing,
SIIMS(7), No. 3, 2014, pp. 1775-1798.
DOI Link 1410
BibRef

Yang, J.B.[Jian-Bo], Liao, X.J.[Xue-Jun], Yuan, X.[Xin], Llull, P.[Patrick], Brady, D.J.[David J.], Sapiro, G.[Guillermo], Carin, L.[Lawrence],
Compressive Sensing by Learning a Gaussian Mixture Model From Measurements,
IP(24), No. 1, January 2015, pp. 106-119.
IEEE DOI 1502
Gaussian processes BibRef
Earlier: A1, A3, A2, A4, A6, A5, A7:
Gaussian mixture model for video compressive sensing,
ICIP13(19-23)
IEEE DOI 1402
BibRef

Yang, J.B.[Jian-Bo], Yuan, X.[Xin], Liao, X.J.[Xue-Jun], Llull, P.[Patrick], Brady, D.J.[David J.], Sapiro, G.[Guillermo], Carin, L.[Lawrence],
Video Compressive Sensing Using Gaussian Mixture Models,
IP(23), No. 11, November 2014, pp. 4863-4878.
IEEE DOI 1410
BibRef
Earlier: A2, A1, A4, A3, A6, A5, A7:
Adaptive temporal compressive sensing for video,
ICIP13(14-18)
IEEE DOI 1402
Cameras BibRef

Liu, H.X.[Hai-Xiao], Song, B.[Bin], Tian, F.[Fang], Qin, H.[Hao],
Joint Sampling Rate and Bit-Depth Optimization in Compressive Video Sampling,
MultMed(16), No. 6, October 2014, pp. 1549-1562.
IEEE DOI 1410
compressed sensing BibRef

Wu, Q.S.[Qi-Song], Zhang, Y.D., Amin, M.G., Himed, B.,
Multi-Task Bayesian Compressive Sensing Exploiting Intra-Task Dependency,
SPLetters(22), No. 4, April 2015, pp. 430-434.
IEEE DOI 1411
Bayes methods BibRef

Zhou, Z., Liu, K., Fang, J.,
Bayesian Compressive Sensing Using Normal Product Priors,
SPLetters(22), No. 5, May 2015, pp. 583-587.
IEEE DOI 1411
Approximation methods BibRef

Poli, L.[Lorenzo], Oliveri, G.[Giacomo], Ding, P.P.[Ping Ping], Moriyama, T.[Toshifumi], Massa, A.[Andrea],
Multifrequency Bayesian compressive sensing methods for microwave imaging,
JOSA-A(31), No. 11, November 2014, pp. 2415-2428.
DOI Link 1411
Inverse problems BibRef

Wei, K.,
Fast Iterative Hard Thresholding for Compressed Sensing,
SPLetters(22), No. 5, May 2015, pp. 593-597.
IEEE DOI 1411
Approximation algorithms BibRef

Zhang, J.C.[Jing-Chao], Fu, N.[Ning], Peng, X.Y.[Xi-Yuan],
Compressive Circulant Matrix Based Analog to Information Conversion,
SPLetters(21), No. 4, April 2014, pp. 428-431.
IEEE DOI 1403
compressed sensing BibRef

Nichols, J.M., Oh, A.K., Willett, R.M.,
Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search,
SPLetters(21), No. 8, August 2014, pp. 1007-1011.
IEEE DOI 1406
Compressed sensing BibRef

Chen, Z., Molina, R., Katsaggelos, A.K.,
Automated Recovery of Compressedly Observed Sparse Signals From Smooth Background,
SPLetters(21), No. 8, August 2014, pp. 1012-1016.
IEEE DOI 1406
Algorithm design and analysis BibRef

Goertz, N., Guo, C., Jung, A., Davies, M.E., Doblinger, G.,
Iterative Recovery of Dense Signals from Incomplete Measurements,
SPLetters(21), No. 9, September 2014, pp. 1059-1063.
IEEE DOI 1406
Compressed sensing BibRef

Li, F.[Fuwei], Fang, J.[Jun], Li, H.B.[Hong-Bin], Huang, L.[Lei],
Robust One-Bit Bayesian Compressed Sensing with Sign-Flip Errors,
SPLetters(22), No. 7, July 2015, pp. 857-861.
IEEE DOI 1412
Bayes methods BibRef

Lu, W.Z.[Wei-Zhi], Li, W.Y.[Wei-Yu], Kpalma, K., Ronsin, J.,
Compressed Sensing Performance of Random Bernoulli Matrices with High Compression Ratio,
SPLetters(22), No. 8, August 2015, pp. 1074-1078.
IEEE DOI 1502
compressed sensing BibRef

Martin, G., Bioucas-Dias, J.M., Plaza, A.,
HYCA: A New Technique for Hyperspectral Compressive Sensing,
GeoRS(53), No. 5, May 2015, pp. 2819-2831.
IEEE DOI 1502
compressed sensing BibRef

Xu, S.C.[Song-Cen], de Lamare, R.C., Poor, H.V.,
Distributed Compressed Estimation Based on Compressive Sensing,
SPLetters(22), No. 9, September 2015, pp. 1311-1315.
IEEE DOI 1503
compressed sensing BibRef

Miller, T.G., Xu, S., de Lamare, R.C., Poor, H.V.,
Distributed Spectrum Estimation Based on Alternating Mixed Discrete-Continuous Adaptation,
SPLetters(23), No. 4, April 2016, pp. 551-555.
IEEE DOI 1604
Cost function BibRef

Jang, W.Y.[Woo-Yong], Ku, Z.[Zahyun], Urbas, A., Derov, J., Noyola, M.J.,
Plasmonic Superpixel Sensor for Compressive Spectral Sensing,
GeoRS(53), No. 6, June 2015, pp. 3471-3480.
IEEE DOI 1503
feature extraction BibRef

Schaeffer, H.[Hayden], Yang, Y.[Yi], Osher, S.J.[Stanley J.],
Space-Time Regularization for Video Decompression,
SIIMS(8), No. 1, 2015, pp. 373-402.
DOI Link 1503
From compressive sensing method. BibRef

Han, H.[Hong], Gan, L.[Lu], Liu, S.[Sanjun], Guo, Y.[Yuyan],
A Novel Measurement Matrix Based on Regression Model for Block Compressed Sensing,
JMIV(51), No. 1, January 2015, pp. 161-170.
Springer DOI 1503
BibRef

Guo, J.[Jie], Song, B.[Bin], Tian, F.[Fang], Liu, H.X.[Hai-Xiao], Qin, H.[Hao],
Perception of Image Characteristics with Compressive Measurements,
IEICE(E97-D), No. 12, December 2014, pp. 3234-3235.
WWW Link. 1503
BibRef

Liu, F., Lin, L., Jiao, L., Li, L., Yang, S., Hou, B., Ma, H., Yang, L., Xu, J.,
Nonconvex Compressed Sensing by Nature-Inspired Optimization Algorithms,
Cyber(45), No. 5, May 2015, pp. 1028-1039.
IEEE DOI 1505
Algorithm design and analysis BibRef

Liu, J.X.[Ji-Xin], Li, X.F.[Xiao-Fei], Han, G.[Guang], Sun, N.[Ning], Du, K.[Kun], Sun, Q.S.[Quan-Sen],
Colour compressed sensing imaging via sparse difference and fractal minimisation recovery,
IET-IPR(9), No. 5, 2015, pp. 369-380.
DOI Link 1506
compressed sensing BibRef

Nagahara, M.,
Discrete Signal Reconstruction by Sum of Absolute Values,
SPLetters(22), No. 10, October 2015, pp. 1575-1579.
IEEE DOI 1506
compressed sensing BibRef

Saleh, A.A.[A. Abou], Alajaji, F., Chan, W.Y.[Wai-Yip],
Compressed Sensing with Non-Gaussian Noise and Partial Support Information,
SPLetters(22), No. 10, October 2015, pp. 1703-1707.
IEEE DOI 1506
Gaussian noise BibRef

Bi, D.[Dongjie], Xie, Y.[Yongle], Li, X.F.[Xi-Feng], Zheng, Y.R.,
A Sparsity Basis Selection Method for Compressed Sensing,
SPLetters(22), No. 10, October 2015, pp. 1738-1742.
IEEE DOI 1506
compressed sensing BibRef

Cambareri, V., Mangia, M., Pareschi, F., Rovatti, R., Setti, G.,
A Case Study in Low-Complexity ECG Signal Encoding: How Compressing is Compressed Sensing?,
SPLetters(22), No. 10, October 2015, pp. 1743-1747.
IEEE DOI 1506
compressed sensing BibRef

Zhu, S.Y.[Shu-Yuan], Zeng, B.[Bing], Gabbouj, M.[Moncef],
Adaptive sampling for compressed sensing based image compression,
JVCIR(30), No. 1, 2015, pp. 94-105.
Elsevier DOI 1507
Sparsity BibRef

Zhu, S.Y.[Shu-Yuan], Zeng, B.[Bing], Fang, L.[Lu], Gabbouj, M.[Moncef],
Downward spatially-scalable image reconstruction based on compressed sensing,
ICIP14(1352-1356)
IEEE DOI 1502
Compressed sensing BibRef

Schwartz, S.[Shimon], Wong, A.[Alexander], Clausi, D.A.[David A.],
Optimized sampling distribution based on nonparametric learning for improved compressive sensing performance,
JVCIR(31), No. 1, 2015, pp. 26-40.
Elsevier DOI 1508
Compressed sampling BibRef

Qiao, H.[Heng], Pal, P.,
Generalized Nested Sampling for Compressing Low Rank Toeplitz Matrices,
SPLetters(22), No. 11, November 2015, pp. 1844-1848.
IEEE DOI 1509
Toeplitz matrices BibRef

Biswas, S., Achanta, H.K., Jacob, M., Dasgupta, S., Mudumbai, R.,
Recovery of Low Rank and Jointly Sparse Matrices with Two Sampling Matrices,
SPLetters(22), No. 11, November 2015, pp. 1945-1949.
IEEE DOI 1509
compressed sensing BibRef

Zhang, J.[Jun], Han, G.J.[Guo-Jun], Fang, Y.[Yi],
Deterministic Construction of Compressed Sensing Matrices from Protograph LDPC Codes,
SPLetters(22), No. 11, November 2015, pp. 1960-1964.
IEEE DOI 1509
binary codes BibRef

Jiang, H.[Hong], Huang, G.[Gang], Wilford, P.[Paul],
Noise analysis for lensless compressive imaging,
SP:IC(36), No. 1, 2015, pp. 70-82.
Elsevier DOI 1509
Lensless compressive imaging BibRef

Wang, X.[Xing], Liang, J.[Jie],
Approximate message passing-based compressed sensing reconstruction with generalized elastic net prior,
SP:IC(37), No. 1, 2015, pp. 19-33.
Elsevier DOI 1509
BibRef
And:
Multi-resolution compressed sensing reconstruction via approximate message passing,
ICIP15(4352-4356)
IEEE DOI 1512
Compressed sensing BibRef

Zhang, Y.L.[Yi-Long], Li, Y.H.[Yue-Hua], He, G.H.[Guan-Hua], Zhang, S.[Sheng],
A Compressive Regularization Imaging Algorithm for Millimeter-Wave SAIR,
IEICE(E98-D), No. 8, August 2015, pp. 1609-1612.
WWW Link. 1509
BibRef

Zhang, Y.L.[Yi-Long], Li, Y.[Yuehua], Safavi-Naeini, S.[Safieddin],
A Spectrum-Based Saliency Detection Algorithm for Millimeter-Wave InSAR Imaging with Sparse Sensing,
IEICE(E100-D), No. 1, February 2017, pp. 388-391.
WWW Link. 1702
BibRef

Warnell, G., Bhattacharya, S., Chellappa, R., Basar, T.,
Adaptive-Rate Compressive Sensing Using Side Information,
IP(24), No. 11, November 2015, pp. 3846-3857.
IEEE DOI 1509
adaptive signal processing BibRef

Li, S.J.[Shuang-Jiang], Qi, H.R.[Hai-Rong],
A Douglas-Rachford Splitting Approach to Compressed Sensing Image Recovery Using Low-Rank Regularization,
IP(24), No. 11, November 2015, pp. 4240-4249.
IEEE DOI 1509
compressed sensing BibRef

Sankaranarayanan, A.C.[Aswin C.], Xu, L.[Lina], Studer, C.[Christoph], Li, Y.[Yun], Kelly, K.F.[Kevin F.], Baraniuk, R.G.[Richard G.],
Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models,
SIIMS(8), No. 3, 2015, pp. 1489-1518.
DOI Link 1511
BibRef
Earlier: A1, A3, A6, Only:
CS-MUVI: Video compressive sensing for spatial-multiplexing cameras,
ICCP12(1-10).
IEEE DOI 1208
BibRef

Holloway, J., Sankaranarayanan, A.C., Veeraraghavan, A., Tambe, S.,
Flutter Shutter Video Camera for compressive sensing of videos,
ICCP12(1-9).
IEEE DOI 1208
BibRef

Yuan, H., Song, H., Sun, X., Guo, K., Ju, Z.,
Compressive sensing measurement matrix construction based on improved size compatible array LDPC code,
IET-IPR(9), No. 11, 2015, pp. 993-1001.
DOI Link 1511
compressed sensing BibRef

Sudhakar, P.[Prasad], Jacques, L.[Laurent], Dubois, X.[Xavier], Antoine, P.[Philippe], Joannes, L.[Luc],
Compressive Imaging and Characterization of Sparse Light Deflection Maps,
SIIMS(8), No. 3, 2015, pp. 1824-1856.
DOI Link 1511
BibRef

Nicodème, M.[Marc], Turcu, F.[Flavius], Dossal, C.[Charles],
Optimal Dual Certificates for Noise Robustness Bounds in Compressive Sensing,
JMIV(53), No. 3, November 2015, pp. 251-263.
WWW Link. 1511
BibRef

Li, G.[Gang], Li, X.[Xiao], Li, S.[Sheng], Bai, H.[Huang], Jiang, Q.[Qianru], He, X.X.[Xiong-Xiong],
Designing robust sensing matrix for image compression,
IP(24), No. 12, December 2015, pp. 5389-5400.
IEEE DOI 1512
compressed sensing BibRef

Chang, K.[Kan], Li, B.X.[Bao-Xin],
Joint modeling and reconstruction of a compressively-sensed set of correlated images,
JVCIR(33), No. 1, 2015, pp. 286-300.
Elsevier DOI 1512
Compressive sensing BibRef

Romero, D., Ariananda, D., Tian, Z., Leus, G.,
Compressive Covariance Sensing: Structure-based compressive sensing beyond sparsity,
SPMag(33), No. 1, January 2016, pp. 78-93.
IEEE DOI 1601
BibRef

Lin, L.P.[Le-Ping], Liu, F.[Fang], Jiao, L.C.[Li-Cheng],
Geometric structure guided collaborative compressed sensing,
SP:IC(40), No. 1, 2016, pp. 16-25.
Elsevier DOI 1601
Geometric structure BibRef

Wang, Y.G.[Ying-Gui], Liu, Z.[Zheng], Yang, L.[Le], Jiang, W.L.[Wen-Li],
Generalized compressive detection of stochastic signals using Neyman-Pearson theorem,
SIViP(9), No. 1 Supp, December 2015, pp. 111-120.
Springer DOI 1601
BibRef

Zayyani, H., Korki, M., Marvasti, F.,
Dictionary Learning for Blind One Bit Compressed Sensing,
SPLetters(23), No. 2, February 2016, pp. 187-191.
IEEE DOI 1602
compressed sensing. the original signal to be reconstructed from one bit linear random measurements is sparse in an unknown domain. BibRef

Zayyani, H., Haddadi, F., Korki, M.,
Double Detector for Sparse Signal Detection From One-Bit Compressed Sensing Measurements,
SPLetters(23), No. 11, November 2016, pp. 1637-1641.
IEEE DOI 1609
compressed sensing BibRef

Sadeghigol, Z.[Zahra], Kahaei, M.H.[Mohammad Hossein], Haddadi, F.[Farzan],
Model based variational Bayesian compressive sensing using heavy tailed sparse prior,
SP:IC(41), No. 1, 2016, pp. 158-167.
Elsevier DOI 1602
Bayesian compressive sensing. based on generalized double Pareto. BibRef

Chang, K., Ding, P.L.K.[P. L. Kevin], Li, B.,
Compressive Sensing Reconstruction of Correlated Images Using Joint Regularization,
SPLetters(23), No. 4, April 2016, pp. 449-453.
IEEE DOI 1604
Compressed sensing BibRef

Sugimura, D.[Daisuke], Tomabechi, M.[Masaru], Hosaka, T.[Tadaaki], Hamamoto, T.[Takayuki],
Compressive multi-spectral imaging using self-correlations of images based on hierarchical joint sparsity models,
MVA(27), No. 4, May 2016, pp. 499-510.
Springer DOI 1605
BibRef

Liu, X.M.[Xian-Ming], Zhai, D.M.[De-Ming], Zhou, J.T.[Jian-Tao], Zhang, X.F.[Xin-Feng], Zhao, D.[Debin], Gao, W.[Wen],
Compressive Sampling-Based Image Coding for Resource-Deficient Visual Communication,
IP(25), No. 6, June 2016, pp. 2844-2855.
IEEE DOI 1605
Codecs BibRef

Eslahi, N.[Nasser], Aghagolzadeh, A.[Ali],
Compressive Sensing Image Restoration Using Adaptive Curvelet Thresholding and Nonlocal Sparse Regularization,
IP(25), No. 7, July 2016, pp. 3126-3140.
IEEE DOI 1606
compressed sensing BibRef

Sasmal, P., Naidu, R.R., Sastry, C.S., Jampana, P.,
Composition of Binary Compressed Sensing Matrices,
SPLetters(23), No. 8, August 2016, pp. 1096-1100.
IEEE DOI 1608
compressed sensing BibRef

Naidu, R.R., Murthy, C.R.,
Construction of Binary Sensing Matrices Using Extremal Set Theory,
SPLetters(24), No. 2, February 2017, pp. 211-215.
IEEE DOI 1702
Gaussian processes BibRef

Guo, J., Song, B., Du, X.,
Significance Evaluation of Video Data Over Media Cloud Based on Compressed Sensing,
MultMed(18), No. 7, July 2016, pp. 1297-1304.
IEEE DOI 1608
cloud computing BibRef

Liu, S.C.[Sheng-Cai], Zhang, J.S.[Jiang-She], Liu, J.M.[Jun-Min], Yin, Q.Y.[Qing-Yan],
L1/2,1 group sparse regularization for compressive sensing,
SIViP(10), No. 5, May 2016, pp. 861-868.
WWW Link. 1608
BibRef

Ye, J.C.[Jong Chul],
Low-rank Fourier interpolation for compressed sensing imaging,
SPIE(Newsroom), July 27, 2016
DOI Link 1608
A novel annihilating filter-based low-rank Hankel matrix approach can be combined with classical analytic reconstruction techniques for application to several compressed sensing imaging problems. BibRef

Dziwoki, G.,
Averaged Properties of the Residual Error in Sparse Signal Reconstruction,
SPLetters(23), No. 9, September 2016, pp. 1170-1173.
IEEE DOI 1609
Gaussian processes BibRef

Zhang, L.Y., Wong, K.W., Zhang, Y., Zhou, J.,
Bi-level Protected Compressive Sampling,
MultMed(18), No. 9, September 2016, pp. 1720-1732.
IEEE DOI 1609
compressed sensing BibRef

Zhang, L.[Lei], Wei, W.[Wei], Tian, C.N.[Chun-Na], Li, F.[Fei], Zhang, Y.N.[Yan-Ning],
Exploring Structured Sparsity by a Reweighted Laplace Prior for Hyperspectral Compressive Sensing,
IP(25), No. 10, October 2016, pp. 4974-4988.
IEEE DOI 1610
BibRef
Earlier: A1, A2, A5, A3, A4:
Reweighted laplace prior based hyperspectral compressive sensing for unknown sparsity,
CVPR15(2274-2281)
IEEE DOI 1510
Bayes methods BibRef

Zhang, L.[Lei], Wei, W.[Wei], Zhang, Y.N.[Yan-Ning], Shen, C.H.[Chun-Hua], van den Hengel, A., Shi, Q.F.[Qin-Feng],
Dictionary Learning for Promoting Structured Sparsity in Hyperspectral Compressive Sensing,
GeoRS(54), No. 12, December 2016, pp. 7223-7235.
IEEE DOI 1612
BibRef
And:
Cluster Sparsity Field for Hyperspectral Imagery Denoising,
ECCV16(V: 631-647).
Springer DOI 1611
Bayes methods BibRef

Zhang, L.[Lei], Wei, W.[Wei], Zhang, Y.N.[Yan-Ning], Li, F.[Fei], Shen, C.H.[Chun-Hua], Shi, Q.F.[Qin-Feng],
Hyperspectral Compressive Sensing Using Manifold-Structured Sparsity Prior,
ICCV15(3550-3558)
IEEE DOI 1602
Correlation BibRef

Sankaranarayanan, A.C., Herman, M.A., Turaga, P., Kelly, K.F.,
Enhanced Compressive Imaging Using Model-Based Acquisition: Smarter sampling by incorporating domain knowledge,
SPMag(33), No. 5, September 2016, pp. 81-94.
IEEE DOI 1610
compressed sensing BibRef

Feng, L.[Lei], Sun, H.J.[Huai-Jiang], Sun, Q.S.[Quan-Sen], Xia, G.Y.[Gui-Yu],
Image compressive sensing via Truncated Schatten-p Norm regularization,
SP:IC(47), No. 1, 2016, pp. 28-41.
Elsevier DOI 1610
Compressive sensing BibRef

Choi, J.,
Secure Transmissions via Compressive Sensing in Multicarrier Systems,
SPLetters(23), No. 10, October 2016, pp. 1315-1319.
IEEE DOI 1610
compressed sensing BibRef

Ahn, J.H.,
Compressive Sensing and Recovery for Binary Images,
IP(25), No. 10, October 2016, pp. 4796-4802.
IEEE DOI 1610
Hadamard matrices BibRef

Testa, M.[Matteo], Magli, E.[Enrico],
Compressive Estimation and Imaging Based on Autoregressive Models,
IP(25), No. 11, November 2016, pp. 5077-5087.
IEEE DOI 1610
autoregressive processes BibRef

Bai, H.[Huang], Li, S.[Sheng], He, X.X.[Xiong-Xiong],
Sensing Matrix Optimization Based on Equiangular Tight Frames With Consideration of Sparse Representation Error,
MultMed(18), No. 10, October 2016, pp. 2040-2053.
IEEE DOI 1610
compressed sensing BibRef

Canh, T.N.[Thuong Nguyen], Dinh, K.Q.[Khanh Quoc], Jeon, B.W.[Byeung-Woo],
Compressive sensing reconstruction via decomposition,
SP:IC(49), No. 1, 2016, pp. 63-78.
Elsevier DOI 1609
BibRef
Earlier: A2, A1, A3:
Compressive sensing of video with weighted sensing and measurement allocation,
ICIP15(2065-2069)
IEEE DOI 1512
Compressive sensing. Compressive sensing of video BibRef

Chien, T.V.[Trinh Van], Dinh, K.Q.[Khanh Quoc], Jeon, B.W.[Byeung-Woo], Burger, M.[Martin],
Block compressive sensing of image and video with nonlocal Lagrangian multiplier and patch-based sparse representation,
SP:IC(54), No. 1, 2017, pp. 93-106.
Elsevier DOI 1704
Block compressive sensing BibRef

Feng, L.[Lei], Sun, H.J.[Huai-Jiang], Sun, Q.S.[Quan-Sen], Xia, G.Y.[Gui-Yu],
Blind compressive sensing using block sparsity and nonlocal low-rank priors,
JVCIR(42), No. 1, 2017, pp. 37-45.
Elsevier DOI 1701
Blind compressive sensing BibRef

Choi, J.,
Successive Hypothesis Testing Based Sparse Signal Recovery and Its Application to MUD in Random Access,
SPLetters(24), No. 2, February 2017, pp. 166-170.
IEEE DOI 1702
compressed sensing BibRef

Baraniuk, R.G., Goldstein, T., Sankaranarayanan, A.C., Studer, C., Veeraraghavan, A., Wakin, M.B.,
Compressive Video Sensing: Algorithms, architectures, and applications,
SPMag(34), No. 1, January 2017, pp. 52-66.
IEEE DOI 1702
Survey, Compressive Sensing. compressed sensing BibRef

Wang, Y.G.[Ying-Gui], Yang, L.[Le], Tang, Z.Y.[Ze-Ying], Gao, Y.[Yong],
Multitask classification and reconstruction using extended Turbo approximate message passing,
SIViP(11), No. 2, February 2017, pp. 219-226.
Springer DOI 1702
BibRef

Tu, H.[Hao], Bu, W.H.[Wei-Hua], Wang, W.J.[Wen-Jing], Gao, B.[Bingxi], Feng, H.[Hui], Wu, S.[Shuai],
Applicability of Hadamard relaxation method to MMW and THz Imaging with compressive sensing,
SIViP(11), No. 3, March 2017, pp. 399-406.
Springer DOI 1702
BibRef

Hu, G.Q.A.[Gui-Qi-Ang], Xiao, D.[Di], Wang, Y.[Yong], Xiang, T.[Tao],
An image coding scheme using parallel compressive sensing for simultaneous compression-encryption applications,
JVCIR(44), No. 1, 2017, pp. 116-127.
Elsevier DOI 1703
Compressive sensing BibRef

Unde, A.S.[Amit Satish], Deepthi, P.P.,
Block compressive sensing: Individual and joint reconstruction of correlated images,
JVCIR(44), No. 1, 2017, pp. 187-197.
Elsevier DOI 1703
Compressive sensing BibRef

Xu, J.[Jin], Zhang, Y.[Yan], Fu, Z.Z.[Zhi-Zhong], Zhou, N.[Ning],
Perceptual Distributed Compressive Video Sensing via Reweighted Sampling and Rate-Distortion Optimized Measurements Allocation,
IEICE(E100-D), No. 4, April 2017, pp. 918-922.
WWW Link. 1704
BibRef

Trigano, T., Cohen, J.,
Intensity Estimation of Spectroscopic Signals With an Improved Sparse Reconstruction Algorithm,
SPLetters(24), No. 5, May 2017, pp. 530-534.
IEEE DOI 1704
compressed sensing BibRef

Wen, Z.D.[Zai-Dao], Hou, B.[Biao], Jiao, L.C.[Li-Cheng],
Joint Sparse Recovery With Semisupervised MUSIC,
SPLetters(24), No. 5, May 2017, pp. 629-633.
IEEE DOI 1704
MUSIC: multiple signal classification. compressed sensing BibRef

Song, X., Peng, X., Xu, J., Shi, G., Wu, F.,
Distributed Compressive Sensing for Cloud-Based Wireless Image Transmission,
MultMed(19), No. 6, June 2017, pp. 1351-1364.
IEEE DOI 1705
BibRef
Earlier:
Compressive sensing based image transmission with side information at the decoder,
VCIP15(1-4)
IEEE DOI 1605
Bandwidth, Correlation, Decoding, Image coding, Scalability, Signal to noise ratio, Silicon, Distributed compressive sensing (CS), graceful degradation (GD), image transmission, side, information, (SI) BibRef

Gholami, M., Alinia, M.,
Explicit APM-LDPC Codes With Girths 6, 8, and 10,
SPLetters(24), No. 6, June 2017, pp. 741-745.
IEEE DOI 1705
matrix algebra, parity check codes, affine permutation matrices, explicit APM-LDPC codes, exponent matrices, low-density parity-check codes, novel explicit constructions, Computers, Decoding, Hardware, Linear codes, Mathematics, Parity check codes, Simulation, Explicit constructions, girth, low-density, parity-check, codes, from, affine, permutation, matrices, (APM-LDPC, codes) BibRef

Ravazzi, C., Coluccia, G.[Giulio], Magli, E.[Enrico],
Curl-Constrained Gradient Estimation for Image Recovery From Highly Incomplete Spectral Data,
IP(26), No. 6, June 2017, pp. 2656-2668.
IEEE DOI 1705
compressed sensing, data compression, image coding, least squares approximations, minimisation, l1-minimization methods, Fourier transform, compressed Fourier measurements, compressed sensing problem, curl-constrained gradient estimation, gradient field, gradient recovery methods, gradient recovery problem, gradient-based methods, highly incomplete spectral data, image recovery, image recovery methods, least squares estimation, signal processing, spectral coefficients, Estimation, Fourier transforms, Image reconstruction, Magnetic resonance imaging, Minimization, Signal processing algorithms, TV, Compressed sensing, Fourier transform, sparse recovery, spectral graph theory, total, variation BibRef

Bioglio, V.[Valerio], Coluccia, G.[Giulio], Magli, E.[Enrico],
Sparse image recovery using compressed sensing over finite alphabets,
ICIP14(1287-1291)
IEEE DOI 1502
Compressed sensing BibRef

Dinh, K.Q.[Khanh Quoc], Shim, H.J.[Hiuk Jae], Jeon, B.W.[Byeung-Woo],
Small-block sensing and larger-block recovery in block-based compressive sensing of images,
SP:IC(55), No. 1, 2017, pp. 10-22.
Elsevier DOI 1705
Compressive sensing BibRef

Geng, T., Sun, G., Xu, Y., Li, Z.,
Image compressive sensing using group sparse representation via truncated nuclear norm minimization,
WSSIP17(1-5)
IEEE DOI 1707
Compressed sensing, Convergence, Convex functions, Dictionaries, Image processing, Minimization, Sparse matrices, Compressive sensing, dictionary learning, group sparse representation, truncated, nuclear, norm, minimization BibRef

Yan, B.[Bai], Zhao, Q.[Qi], Wang, Z.H.[Zhi-Hai], Zhao, X.Y.[Xin-Yuan],
A hybrid evolutionary algorithm for multiobjective sparse reconstruction,
SIViP(11), No. 6, September 2017, pp. 993-1000.
Springer DOI 1708
BibRef

Wang, L.Z.[Li-Zhi], Xiong, Z.W.[Zhi-Wei], Shi, G.M.[Guang-Ming], Wu, F.[Feng], Zeng, W.J.[Wen-Jun],
Adaptive Nonlocal Sparse Representation for Dual-Camera Compressive Hyperspectral Imaging,
PAMI(39), No. 10, October 2017, pp. 2104-2111.
IEEE DOI 1709
Hyperspectral imaging, Compressive sensing, dual-camera, hyperspectral imaging, nonlocal similarity, sparse, representation BibRef


Li, Q.[Qun], Bernal, E.A.[Edgar A.],
An Algorithm for Parallel Reconstruction of Jointly Sparse Tensors with Applications to Hyperspectral Imaging,
PBVS17(218-225)
IEEE DOI 1709
Complexity theory, Hyperspectral imaging, Image reconstruction, Matrix decomposition, Niobium, Tensile, stress BibRef

Li, Z.[Zhou], Cui, C.[Chen], Yi, R.[Renjie],
A sparsity adaptive signal reconstruction algorithm,
ICIVC17(852-857)
IEEE DOI 1708
adaptive, multipath matching pursuit, regularized, retrospective, tracing BibRef

Ren, M.J.[Meng-Jie], Chen, S.[Shenpei], Chen, D.[Dong],
Research on missile-borne image transmission technology based on compressive sensing,
ICIVC17(773-777)
IEEE DOI 1708
Bandwidth, Encoding, Image coding, Image reconstruction, Sensors, compressive sensing, missile-borne image, transmission, technology BibRef

Sato, S., Wakai, N., Nobori, K., Azuma, T., Miyata, T., Nakashizuka, M.,
Compressive color sensing using random complementary color filter array,
MVA17(43-46)
DOI Link 1708
Color, Compressed sensing, Image color analysis, Image edge detection, Image reconstruction, Imaging, Optical, filters BibRef

Wang, Z.E.[Zhong-Eng], Chen, S.F.[Shou-Fa],
Performance comparison of image block compressive sensing based on chaotic sensing matrix using different basis matrices,
ICIVC17(620-623)
IEEE DOI 1708
Compressed sensing, Discrete Fourier transforms, Discrete cosine transforms, Discrete wavelet transforms, Image reconstruction, Sparse matrices, compressive sensing, image processing, peak signal-to-noise ratio, sparse, basis, matrix BibRef

Jellali, Z.[Zakia], Atallah, L.N.[Leïla Najjar], Cherif, S.[Sofiane],
Data acquisition by 2D compression and ID reconstruction techniques for WSN spatially correlated data,
ISIVC16(224-229)
IEEE DOI 1704
Correlation BibRef

Kulkarni, K.[Kuldeep], Lohit, S.[Suhas], Turaga, P.K.[Pavan K.], Kerviche, R.[Ronan], Ashok, A.[Amit],
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements,
CVPR16(449-458)
IEEE DOI 1612
BibRef

Ou, W.F., Yang, C.L., Li, W.H., Ma, L.H.,
A two-stage multi-hypothesis reconstruction scheme in compressed video sensing,
ICIP16(2494-2498)
IEEE DOI 1610
Adaptation models BibRef

Zhao, C., Zhang, J., Ma, S., Xiong, R., Gao, W.,
A dual structured-sparsity model for compressive-sensed video reconstruction,
VCIP15(1-4)
IEEE DOI 1605
Compressed sensing BibRef

Ebrahim, M., Chai, W.C.,
Multi-phase joint reconstruction framework for multi-view video compression using block-based compressive sensing,
VCIP15(1-4)
IEEE DOI 1605
Compressed sensing BibRef

Xu, J., Djahel, S., Qiao, Y., Fu, Z.,
Perceptually-aware distributed compressive video sensing,
VCIP15(1-4)
IEEE DOI 1605
Codecs BibRef

Zhang, Y., Comerford, L., Beer, M., Kougioumtzoglou, I.,
Compressive sensing for power spectrum estimation of multi-dimensional processes under missing data,
WSSIP15(162-165)
IEEE DOI 1603
compressed sensing BibRef

Ebadi, S.E., Izquierdo, E.,
Approximated RPCA for fast and efficient recovery of corrupted and linearly correlated images and video frames,
WSSIP15(49-52)
IEEE DOI 1603
compressed sensing BibRef

Chen, B., Perona, P.,
Scotopic Visual Recognition,
Extreme15(659-662)
IEEE DOI 1602
Computational modeling. From a small number of photons. BibRef

Che, W.B.[Wen-Bin], Gao, X.W.[Xin-Wei], Fan, X.P.[Xiao-Peng], Jiang, F.[Feng], Zhao, D.B.[De-Bin],
Spatial-temporal recovery for hierarchical frame based video compressed sensing,
ICIP15(1110-1114)
IEEE DOI 1512
Video compressed sensing BibRef

Francis, K.J., Rajalakshmi, P., Channappayya, S.S.[Sumohana S.],
Distributed compressed sensing for photo-acoustic imaging,
ICIP15(1513-1517)
IEEE DOI 1512
Distributed Compressive Sensing BibRef

Rueda, H.[Hoover], Arguello, H.[Henry], Arce, G.R.[Gonzalo R.],
Dual-ARM VIS/NIR compressive spectral imager,
ICIP15(2572-2576)
IEEE DOI 1512
Compressive sensing BibRef

Tran, D.N.[Dung N.], Tran, D.N.[Duyet N.], Chin, S.P.[Sang Peter], Tran, T.D.[Trac D.],
Local sensing with global recovery,
ICIP15(4313-4316)
IEEE DOI 1512
Compressed sensing; imaging; sparse representation BibRef

Wang, J.[Jian], Gupta, M., Sankaranarayanan, A.C.,
LiSens- A Scalable Architecture for Video Compressive Sensing,
ICCP15(1-9)
IEEE DOI 1511
data compression BibRef

Spinoulas, L.[Leonidas], Cossairt, O.[Oliver], Katsaggelos, A.K.[Aggelos K.],
Sampling optimization for on-chip compressive video,
ICIP15(3329-3333)
IEEE DOI 1512
CMOS sensor; Sampling optimization; compressive sensing; high-speed video BibRef

Spinoulas, L.[Leonidas], He, K.[Kuan], Cossairt, O.[Oliver], Katsaggelos, A.[Aggelos],
Video compressive sensing with on-chip programmable subsampling,
CCD15(49-57)
IEEE DOI 1510
Cameras BibRef

Lohit, S.[Suhas], Kulkarni, K.[Kuldeep], Turaga, P.K.[Pavan K.],
Direct inference on compressive measurements using convolutional neural networks,
ICIP16(1913-1917)
IEEE DOI 1610
Correlation BibRef

Lohit, S.[Suhas], Kulkarni, K.[Kuldeep], Turaga, P.K.[Pavan K.], Wang, J.[Jian], Sankaranarayanan, A.C.[Aswin C.],
Reconstruction-free inference on compressive measurements,
CCD15(16-24)
IEEE DOI 1510
Correlation BibRef

Chen, H.[Huaijin], Asif, M.S.[M.Salman], Sankaranarayanan, A.C.[Aswin C.], Veeraraghavan, A.[Ashok],
FPA-CS: Focal plane array-based compressive imaging in short-wave infrared,
CVPR15(2358-2366)
IEEE DOI 1510
BibRef

Sato, S.[Satoshi], Ishii, M.[Motonori], Kato, Y.[Yoshihisa], Nobori, K.[Kunio], Azuma, T.[Takeo],
Compressive sensing reconstruction using collaborative sparsity among color channels,
MVA15(406-409)
IEEE DOI 1507
Cameras BibRef

Mourchid, Y., El Hassouni, M.,
Comparative study between different bases of transformation for compressive sensing of images,
ISCV15(1-7)
IEEE DOI 1506
compressed sensing BibRef

Dong, H.F.[Hai-Feng], Zhuang, B.[Bojin], Su, F.[Fei], Zhao, Z.C.[Zhi-Cheng],
A novel distributed compressive video sensing based on hybrid sparse basis,
VCIP14(320-323)
IEEE DOI 1504
compressed sensing BibRef

Zhao, C.[Chen], Ma, S.W.[Si-Wei], Gao, W.[Wen],
Video compressive sensing via structured Laplacian modelling,
VCIP14(402-405)
IEEE DOI 1504
Laplace equations BibRef

Kerviche, R.[Ronan], Zhu, N.[Nan], Ashok, A.[Amit],
Information optimal scalable compressive imager demonstrator,
ICIP14(2177-2179)
IEEE DOI 1502
System delivers high-resolution images from low resolution sensor with near real-time snapshots. BibRef

Hou, X.S.[Xing-Song], Tian, W.W.[Wen-Wen], Gong, C.[Chen],
Robust and efficient SAR image coding transmission based on compressive sensing,
ICIP14(2512-2516)
IEEE DOI 1502
Compressed sensing BibRef

Hou, Y.[Ying], Zhang, Y.[Yanning],
Effective Image Block Compressed Sensing,
ICPR14(1085-1090)
IEEE DOI 1412
Compressed sensing BibRef

Li, Y.[Yong], Xiong, H.K.[Hong-Kai], Ye, X.W.[Xin-Wei],
Compressive video sampling from a union of data-driven subspaces,
VCIP13(1-6)
IEEE DOI 1402
compressed sensing Sample and recover an unknown signal from a union of data-driven subspaces. BibRef

Li, X.W.[Xiang-Wei], Lan, X.G.[Xu-Guang], Yang, M.[Meng], Xue, J.R.[Jian-Ru], Zheng, N.N.[Nan-Ning],
Optimized truncation model for adaptive compressive sensing acquisition of images,
VCIP15(1-4)
IEEE DOI 1605
BibRef
Earlier:
Universal and low-complexity quantizer design for compressive sensing image coding,
VCIP13(1-5)
IEEE DOI 1402
Adaptation models. codecs BibRef

Dinh, K.Q.[Khanh Quoc], Shim, H.J.[Hiuk Jae], Jeon, B.W.[Byeung-Woo],
Measurement coding for compressive imaging using a structural measuremnet matrix,
ICIP13(10-13)
IEEE DOI 1402
Compressed sensing BibRef

Iliadis, M.[Michael], Watt, J.[Jeremy], Spinoulas, L.[Leonidas], Katsaggelos, A.K.[Aggelos K.],
Video compressive sensing using multiple measurement vectors,
ICIP13(136-140)
IEEE DOI 1402
Compressed sensing BibRef

Anaraki, F.P.[Farhad Pourkamali], Hughes, S.M.[Shannon M.],
Kernel compressive sensing,
ICIP13(494-498)
IEEE DOI 1402
Compressed sensing BibRef

Yang, F.[Fei], Jiang, H.[Hong], Shen, Z.[Zuowei], Deng, W.[Wei], Metaxas, D.[Dimitris],
Adaptive low rank and sparse decomposition of video using compressive sensing,
ICIP13(1016-1020)
IEEE DOI 1402
Cameras BibRef

Zhang, J.[Jian], Zhao, D.B.[De-Bin], Jiang, F.[Feng],
Spatially directional predictive coding for block-based compressive sensing of natural images,
ICIP13(1021-1025)
IEEE DOI 1402
Bit rate BibRef

Huang, G.[Gang], Jiang, H.[Hong], Matthews, K.[Kim], Wilford, P.[Paul],
Lensless imaging by compressive sensing,
ICIP13(2101-2105)
IEEE DOI 1402
Compressive sensing;imaging;lensless;sensor BibRef

Hua, B.S.[Binh-Son], Sato, I.[Imari], Low, K.L.[Kok-Lim],
Direct and progressive reconstruction of dual photography images,
ICIP13(3157-3161)
IEEE DOI 1402
compressive sensing;dual photography BibRef

Chu, X.[Xiaoyu], Stamm, M.C.[Matthew C.], Liu, K.J.R.[K. J. Ray],
Forensic identification of compressively sensed signals,
ICIP12(257-260).
IEEE DOI 1302
BibRef

Zhang, X.Y.[Xin-Yu], Wen, J.T.[Jiang-Tao],
Compressive video sensing using non-linear mapping,
ICIP12(885-888).
IEEE DOI 1302
BibRef

Rao, N.S.[Nikhil S.], Nowak, R.D.[Robert D.],
Correlated gaussian designs for compressive imaging,
ICIP12(921-924).
IEEE DOI 1302
BibRef

Golbabaee, M.[Mohammad], Vandergheynst, P.[Pierre],
Joint trace/TV norm minimization: A new efficient approach for spectral compressive imaging,
ICIP12(933-936).
IEEE DOI 1302
BibRef

Kumar, N.R., Xiang, W.[Wei], Soar, J.,
A Novel Image Compressive Sensing Method Based on Complex Measurements,
DICTA11(175-179).
IEEE DOI 1205
BibRef

Papandreou, G.[George], Yuille, A.L.[Alan L.],
Efficient variational inference in large-scale Bayesian compressed sensing,
ITCVPR11(1332-1339).
IEEE DOI 1201
BibRef

Shu, X.B.[Xian-Biao], Yang, J.C.[Jian-Chao], Ahuja, N.,
Non-local compressive sampling recovery,
ICCP14(1-8)
IEEE DOI 1411
compressed sensing BibRef

Shu, X.B.[Xian-Biao], Ahuja, N.[Narendra],
Imaging via three-dimensional compressive sampling (3DCS),
ICCV11(439-446).
IEEE DOI 1201
I.e. sample below Nyquist rate. A lot of theory, but no camera yet. BibRef

Le Montagner, Y.[Yoann], Marim, M.M.[Marcio M.], Angelini, E.D.[Elsa D.], Olivo-Marin, J.C.[Jean-Christophe],
Numerical evaluation of sampling bounds for near-optimal reconstruction in compressed sensing,
ICIP11(3073-3076).
IEEE DOI 1201
BibRef

Li, B.[Bin], Zhu, X.[Xuqi], Liu, Y.[Yu], Zhang, L.[Lin],
An unequally protected Distributed Compressed Video Sensing algorithm,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Zhang, Z.[Zhen], Shi, Y.H.[Yun-Hui], Ding, W.P.[Wen-Peng], Yin, B.C.[Bao-Cai],
MR images reconstruction based on TVWL2-L1 model,
JVCIR(24), No. 2, February 2013, pp. 187-195.
Elsevier DOI 1302
Compressive sensing; MR image reconstruction; Convex optimization; Wavelet transform; Total variation BibRef

Zhang, Z.[Zhen], Shi, Y.H.[Yun-Hui], Yin, B.C.[Bao-Cai],
Compressive sensing image recovery based on equalization quantization noise model,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Huang, H.L.[Hong-Lin], Makur, A., Venkatraman, D.,
Video object error coding method based on compressive sensing,
ICARCV08(1287-1291).
IEEE DOI 1109
BibRef

Xiao, L.[Liang], Shao, J.[Jun], Huang, L.[Lili], Wei, Z.H.[Zhi-Hui],
Compounded Regularization and Fast Algorithm for Compressive Sensing Deconvolution,
ICIG11(616-621).
IEEE DOI 1109
BibRef

Lin, X.F.[Xiao-Fen], Lu, G.[Gang], Yan, J.W.[Jing-Wen], Lin, W.[Wei],
Measurement Matrix of Compressive Sensing Based on Gram-Schmidt Orthogonalization,
ICIG11(205-210).
IEEE DOI 1109
BibRef

Ren, Y.M.[Yue-Mei], Zhang, Y.N.[Yang-Ning], Li, Y.[Ying], Huang, J.Y.[Jian-Yu], Hui, J.J.[Jian-Jiang],
A Space Target Recognition Method Based on Compressive Sensing,
ICIG11(582-586).
IEEE DOI 1109
BibRef

Borghi, A., Darbon, J., Peyronnet, S., Chan, T.F.[Tony F.], Osher, S.J.[Stanley J.],
A Compressive Sensing Algorithm for Many-Core Architectures,
ISVC10(II: 678-686).
Springer DOI 1011
BibRef

Trocan, M.[Maria], Maugey, T.[Thomas], Tramel, E.W.[Eric W.], Fowler, J.E.[James E.], Pesquet-Popescu, B.[Beatrice],
Compressed sensing of multiview images using disparity compensation,
ICIP10(3345-3348).
IEEE DOI 1009
BibRef

Zhang, X.[Xin], Lam, E.Y.[Edmund Y.],
Sectional image reconstruction in optical scanning holography using compressed sensing,
ICIP10(3349-3352).
IEEE DOI 1009
BibRef

He, Z.X.[Zai-Xing], Ogawa, T.[Takahiro], Haseyama, M.[Miki],
The simplest measurement matrix for compressed sensing of natural images,
ICIP10(4301-4304).
IEEE DOI 1009
BibRef

Majumdar, A.[Angshul], Ward, R.K.[Rabab K.],
Compressive color imaging with group-sparsity on analysis prior,
ICIP10(1337-1340).
IEEE DOI 1009
BibRef

Shang, F.[Fei], Du, H.[Huiqian], Jia, Y.D.[Yun-De],
Compressive Sampling Recovery for Natural Images,
ICPR10(2206-2209).
IEEE DOI 1008
BibRef

Yamamoto, S.[Satoshi], Itakura, Y.[Yasumasa], Sawabe, M.[Masashi],
Precomputed ROMP for light transport acquisition,
PROCAMS10(49-56).
IEEE DOI 1006
Compressive sensing. BibRef

Chang, H.S.[Hyun Sung], Weiss, Y.[Yair], Freeman, W.T.[William T.],
Informative sensing of natural images,
ICIP09(3025-3028).
IEEE DOI 0911
different random sampling. BibRef

Mun, S.K.[Sung-Kwang], Fowler, J.E.[James E.],
Block compressed sensing of images using directional transforms,
ICIP09(3021-3024).
IEEE DOI 0911
BibRef

Patel, V.M.[Vishal M.], Easley, G.R.[Glenn R.], Healy, D.M.[Dennis M.], Chellappa, R.[Rama],
Compressed sensing for Synthetic Aperture Radar imaging,
ICIP09(2141-2144).
IEEE DOI 0911
BibRef

Lu, W.[Wei], Vaswani, N.[Namrata],
Modified compressive sensing for real-time dynamic MR imaging,
ICIP09(3045-3048).
IEEE DOI 0911
BibRef

Wu, X.L.[Xiao-Lin], Zhang, X.J.[Xiang-Jun],
Compressive-uniform hybrid sensing for image acquisition and communication,
ICIP09(3041-3044).
IEEE DOI 0911
BibRef

Wang, T.[Tao], Zhu, Z.G.[Zhi-Gang], Rhody, H.[Harvey],
A smart sensor with hyperspectral/range fovea and panoramic peripheral view,
OTCBVS09(98-105).
IEEE DOI 0906
BibRef

Wan, T.[Tao], Canagarajah, N.[Nishan], Achim, A.[Alin],
Compressive image fusion,
ICIP08(1308-1311).
IEEE DOI 0810
Sampling pattern. BibRef

Patel, V.M.[Vishal M.], Easley, G.R.[Glenn R.], Chellappa, R.[Rama], Healy, D.M.[Dennis M.],
Enhancing sparsity using gradients for compressive sensing,
ICIP09(3033-3036).
IEEE DOI 0911
BibRef

Hyder, M.M.[M. Mashud], Mahata, K.[Kaushik],
A fast decoder for Compressed Sensing based multiple description image coding,
ICIP09(2125-2128).
IEEE DOI 0911
BibRef

Schulz, A.[Adriana], Velho, L.[Luiz], da Silva, E.A.B.[Eduardo A.B.],
On the empirical rate-distortion performance of Compressive Sensing,
ICIP09(3049-3052).
IEEE DOI 0911
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Matching Pursuits, Video Coding .


Last update:Sep 25, 2017 at 16:36:46