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9909
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Regularisation Functions and Estimators,
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IEEE DOI
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0106
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ICIP01(I: 233-236).
IEEE DOI
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0409
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0512
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Springer DOI
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Semi-explicit Solution and Fast Minimization Scheme for an Energy with
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See also Regularization of Ill-Posed Problems, The.
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Nikolova, M.[Mila],
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DOI Link
1307
BibRef
Earlier:
Should We Search for a Global Minimizer of Least Squares Regularized
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SSVM11(508-519).
Springer DOI
1201
BibRef
Earlier:
Bounds on the Minimizers of (nonconvex) Regularized Least-Squares,
SSVM07(496-507).
Springer DOI
0705
BibRef
Nikolova, M.[Mila],
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Springer DOI
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Durand, S.,
Nikolova, M.,
Stability of image restoration by minimizing regularized objective
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LevelSet01(xx-yy).
0106
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SIIMS(1), No. 1, 2008, pp. 2-25.
image restoration; regularization; nonsmooth and nonconvex
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segmentation; inverse problems; deblurring; constrained optimization;
graduated nonconvexity (GNC)
DOI Link
BibRef
0800
Nikolova, M.[Mila],
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Tam, C.P.,
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IEEE DOI
1011
BibRef
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PR(32), No. 12, December 1999, pp. 2067-2068.
Elsevier DOI
BibRef
9912
Earlier: A2, A1, A3, A4:
CAIP99(33-40).
Springer DOI
9909
BibRef
Baumbach, T.,
Ortmann, W.,
Shift detection by restoration:
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CIAP99(310-315).
IEEE DOI
9909
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0002
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IEEE DOI
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Li, S.Z.[Stan Z.],
Toward global solution to MAP image restoration and segmentation:
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Elsevier DOI
0002
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Storvik, G.,
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0003
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Sigelle, M.[Marc],
A Cumulant Expansion Technique for Simultaneous Markov Random Field
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DOI Link
0008
BibRef
Choy, S.O.,
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Image restoration by regularisation in uncorrelated transform domain,
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Oscillating Patterns in Image Processing and
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Images decompose into geometry and texture.
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0600
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Markham, J.[Joanne],
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Fast maximum-likelihood image-restoration algorithms for
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Piccolomini, E.L.[E. Loli],
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Convex half-quadratic criteria and interacting auxiliary variables for
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0108
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Chouzenoux, E.,
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IEEE DOI
1106
accelerated subspace optimization.
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0110
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Pham, T.D.[Tuan D.],
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Elsevier DOI
1101
Information fusion; Permanence of ratios; Probabilistic measures;
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See also Fuzzy declustering-based vector quantization.
BibRef
Pham, T.D.[Tuan D.],
Image Classification with Indicator Kriging Error Comparison,
ICISP14(433-440).
Springer DOI
1406
BibRef
Pham, T.D.,
Image Restoration by Ordinary Kriging with Convexity,
ICPR00(Vol III: 330-333).
IEEE DOI
0009
BibRef
Pham, T.D.[Tuan D.],
Double Adaptive Filtering of Gaussian Noise Degraded Images,
SCIA07(848-857).
Springer DOI
0706
BibRef
Pham, T.D.,
Wagner, M.,
Image Restoration by Fuzzy Convex Ordinary Kriging,
ICIP00(Vol I: 113-116).
IEEE DOI
0008
BibRef
Pham, T.D.[Tuan D.],
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A New Spatial Approach to Image Restoration,
IPTA08(1-8).
IEEE DOI
0811
BibRef
Unal, G.B.,
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Restoration of error-diffused images using projection onto convex sets,
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0201
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Sotthivirat, S.,
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Image Recovery Using Partitioned-Separable Paraboloidal Surrogate
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IEEE DOI
0203
BibRef
Earlier:
Partitioned Separable Paraboloidal Surrogate Coordinate Ascent
Algorithm for Image Restoration,
ICIP00(Vol I: 109-112).
IEEE DOI
0008
BibRef
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CirSysVideo(12), No. 5, May 2002, pp. 331-341.
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Sequeira, R.E.,
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0402
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0304
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Zoubir, A.M.,
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Robust Estimation Approach for Blind Denoising,
IP(14), No. 11, November 2005, pp. 1755-1765.
IEEE DOI
0510
BibRef
Liao, Y.,
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Blind Image Restoration With Eigen-Face Subspace,
IP(14), No. 11, November 2005, pp. 1766-1772.
IEEE DOI
0510
BibRef
Nadadur, D.,
Haralick, R.M.,
Gustafson, D.E.,
A Bayesian Framework for Noise Covariance Estimation Using the Facet
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IP(14), No. 11, November 2005, pp. 1902-1917.
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0510
BibRef
Memon, N.,
Pal, A.,
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0602
Pose as a graph problem, find the best ordering.
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Zhu, D.[Daan],
Razaz, M.[Moe],
Fisher, M.[Mark],
An adaptive algorithm for image restoration using combined penalty
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PRL(27), No. 12, September 2006, pp. 1336-1341.
Elsevier DOI
0606
Gradient descent; Penalized likelihood; Combined penalty function;
Regularization
BibRef
Zhu, D.[Daan],
Razaz, M.,
Lee, R.,
A robust regularised restoration algorithm based on Topkis-Veinott
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ICPR04(IV: 705-708).
IEEE DOI
0409
BibRef
And:
A Landweber Algorithm for 3D Confocal Microscopy Restoration,
ICPR04(I: 552-555).
IEEE DOI
0409
BibRef
Esmer, G.B.[G. Bora],
Uzunov, V.[Vladislav],
Onural, L.[Levent],
Ozaktas, H.M.[Haldun M.],
Gotchev, A.[Atanas],
Diffraction field computation from arbitrarily distributed data points
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SP:IC(22), No. 2, February 2007, pp. 178-187.
Elsevier DOI
0704
Scalar optical diffraction; Plane wave decomposition;
Pseudo-matrix inversion; Projection onto convex sets
BibRef
Esmer, G.B.[G. Bora],
Onural, L.[Levent],
Ozaktas, H.M.[Haldun M.],
Uzunov, V.[Vladislav],
Gotchev, A.[Atanas],
Performance Assessment of A Diffraction Field Computation Method Based
on Source Model,
3DTV08(257-260).
IEEE DOI
0805
BibRef
Esmer, G.B.[G. Bora],
Uzunov, V.[Vladislav],
Onural, L.[Levent],
Gotchev, A.[Atanas],
Ozaktas, H.M.[Haldun M.],
Reconstruction of Scalar Diffraction Field from Distributed Data Points
Over 3D Space,
3DTV07(1-4).
IEEE DOI
0705
BibRef
Uzunov, V.[Vladislav],
Esmer, G.B.[G. Bora],
Gotchev, A.[Atanas],
Onural, L.[Levent],
Ozaktas, H.M.[Haldun M.],
Bessel Functions-Based Reconstruction of Non-Uniformly Sampled
Diffraction Fields,
3DTV07(1-4).
IEEE DOI
0705
BibRef
Oommen, B.J.[B. John],
Kim, S.W.[Sang-Woon],
Horn, G.[Geir],
On the estimation of independent binomial random variables using
occurrence and sequential information,
PR(40), No. 11, November 2007, pp. 3263-3276.
Elsevier DOI
0707
BibRef
Earlier:
On the Theory and Applications of Sequence Based Estimation of
Independent Binomial Random Variables,
SSPR06(8-21).
Springer DOI
0608
Estimation using sequential information; Estimation of binomials;
Fused estimation methods; Sequential information
BibRef
Oommen, B.J.[B. John],
Kim, S.W.[Sang-Woon],
Multinomial Sequence Based Estimation Using Contiguous Subsequences of
Length Three,
ICIAR16(243-253).
Springer DOI
1608
BibRef
Pan, P.,
Schonfeld, D.,
Image Reconstruction and Multidimensional Field Estimation From
Randomly Scattered Sensors,
IP(17), No. 1, January 2008, pp. 94-99.
IEEE DOI
0712
Image reconstruction from photon-limited images and field
estimation from scattered sensors.
BibRef
Sha, L.,
Schonfeld, D.,
Wang, J.,
Graph Laplacian Regularization With Sparse Coding for Image
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CirSysVideo(30), No. 7, July 2020, pp. 2000-2014.
IEEE DOI
2007
Image restoration, Image coding, Laplace equations,
Clustering algorithms, Image edge detection, Encoding,
image decomposition
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Chaudhry, A.[Asmatullah],
Khan, A.[Asifullah],
Ali, A.[Asad],
Mirza, A.M.[Anwar M.],
A hybrid image restoration approach:
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IJIST(17), No. 4, 2007, pp. 224-231.
DOI Link
0712
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Jaffar, M.A.[M. Arfan],
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Nazir, M.[Muhammad],
Mirza, A.M.[Anwar M.],
Modified Histogram Based Fuzzy Filter,
MIRAGE09(277-284).
Springer DOI
0905
BibRef
Gan, T.,
He, Y.,
Zhu, W.,
Fast M-Term Pursuit for Sparse Image Representation,
SPLetters(15), No. 1, January 2008, pp. 116-119.
IEEE DOI
0801
Extension of matching pursuit, but much faster.
BibRef
Bao, P.[Paul],
Hong, S.W.[Sung-Wai],
Image Restoration Based on Generalized Finite Automata Encoded Edge
Preserving Regularization,
IJIG(2), No. 3, July 2002, pp. 425-439.
0207
BibRef
Goldfarb, D.[Donald],
Wen, Z.W.[Zai-Wen],
Yin, W.T.[Wo-Tao],
A Curvilinear Search Method For P-Harmonic Flows On Spheres,
SIIMS(2), No. 1, 2009, pp. 84-109.
DOI Link energy minimization; p-harmonic maps; p-harmonic flows; finite
difference; curvilinear search; global convergence; chromaticity
denoising
BibRef
0900
Guidara, R.,
Hosseini, S.,
Deville, Y.,
Maximum Likelihood Blind Image Separation Using Nonsymmetrical
Half-Plane Markov Random Fields,
IP(18), No. 11, November 2009, pp. 2435-2450.
IEEE DOI
0911
Separating mixtures of images.
BibRef
Barbu, A.[Adrian],
Training an Active Random Field for Real-Time Image Denoising,
IP(18), No. 11, November 2009, pp. 2451-2462.
IEEE DOI
0911
BibRef
And:
Learning real-time MRF inference for image denoising,
CVPR09(1574-1581).
IEEE DOI
0906
Train MRF to perform well with suboptimal inference (i.e. not
full maximum a posteriori estimation).
BibRef
Luo, J.,
Li, W.,
Zhu, Y.,
Reconstruction From Limited-Angle Projections Based on delta-u
Spectrum Analysis,
IP(19), No. 1, January 2010, pp. 131-140.
IEEE DOI
1001
Product of Delta function and step function for representation.
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Wang, Z.,
Arce, G.R.[Gonzalo R.],
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IP(19), No. 1, January 2010, pp. 264-270.
IEEE DOI
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Reconstruction from limited number of samples at sub-Nyquist sampling rates.
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Xiong, Z.X.[Zi-Xiang],
Arce, G.R.[Gonzalo R.],
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Zhu, W.[Wenwu],
Yan, Z.S.[Zhi-Sheng],
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ICIP12(909-912).
IEEE DOI
1302
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IEICE(E93-D), No. 2, February 2010, pp. 403-406.
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Dong, W.S.[Wei-Sheng],
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Shi, G.M.[Guang-Ming],
Spatial-Temporal Color Video Reconstruction From Noisy CFA Sequence,
CirSysVideo(20), No. 6, June 2010, pp. 838-847.
IEEE DOI
1007
Single sensor color, CFA for video, demosaicing for color.
Reduce sensor noise.
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Fonseca, L.M.G.[Leila M.G.],
de Carvalho, L.A.S.[Lino A.S.],
Projections Onto Convex Sets through Particle Swarm Optimization and
its application for remote sensing image restoration,
PRL(31), No. 13, 1 October 2010, pp. 1876-1886.
Elsevier DOI
1003
Image restoration; Projections Onto Convex Sets; Particle Swarm
Optimization; CBERS-2B
BibRef
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Gonsalves Pires, R.[Rafael],
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Papa, J.P.[João Paulo],
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WVC17(138-143)
IEEE DOI
1804
Boltzmann machines, face recognition, feature extraction,
learning (artificial intelligence), optimisation,
Restricted Boltzmann Machines
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Gonsalves Pires, R.[Rafael],
da Silva Santos, D.F.[Daniel Felipe],
de Souza, G.B.[Gustavo Botelho],
Marana, A.N.[Aparecido N.],
Levada, A.L.M.[Alexandre L. M.],
Papa, J.P.[João Paulo],
A Deep Boltzmann Machine-Based Approach for Robust Image Denoising,
CIARP17(525-533).
Springer DOI
1802
BibRef
Karci, M.H.,
Demirekler, M.,
Minimization of Monotonically Levelable Higher Order MRF Energies via
Graph Cuts,
IP(19), No. 11, November 2010, pp. 2849-2860.
IEEE DOI
1011
BibRef
Li, Q.[Qi],
Ding, S.H.[Sheng-Hui],
Yao, R.[Rui],
Wang, Q.[Qi],
Real-time terahertz scanning imaging by use of a pyroelectric array
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JOSA-A(27), No. 11, November 2010, pp. 2381-2386.
DOI Link
1011
BibRef
Pan, M.C.[Min-Cheng],
Image restoration through regularization based on error energy
minimization,
IJIST(20), No. 4, December 2010, pp. 308-315.
DOI Link
1011
BibRef
Cao, Y.[Yang],
Luo, Y.P.[Yu-Pin],
Yang, S.Y.[Shi-Yuan],
Image Denoising Based on Hierarchical Markov Random Field,
PRL(32), No. 2, 15 January 2011, pp. 368-374.
Elsevier DOI
1101
Image denoising; Markov random field; Bayesian estimation
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Giannoula, A.,
Classification-Based Adaptive Filtering for Multiframe Blind Image
Restoration,
IP(20), No. 2, February 2011, pp. 382-390.
IEEE DOI
1102
BibRef
Li, X.,
Fine-Granularity and Spatially-Adaptive Regularization for
Projection-Based Image Deblurring,
IP(20), No. 4, April 2011, pp. 971-983.
IEEE DOI
1103
BibRef
Su, L.Y.[Li-Yun],
Liu, R.H.[Rui-Hua],
Blind Image Restoration With Modified CMA,
IJIG(11), No. 1, January 2011, pp. 403-413.
DOI Link
1108
BibRef
Shen, Z.W.[Zuo-Wei],
Toh, K.C.[Kim-Chuan],
Yun, S.W.[Sang-Woon],
An Accelerated Proximal Gradient Algorithm for Frame-Based Image
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SIIMS(4), No. 2, 2011, pp. 573-596.
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1110
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A Generalized Accelerated Proximal Gradient Approach for
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IP(20), No. 10, October 2011, pp. 2748-2759.
IEEE DOI
1110
BibRef
Chen, Q.[Qi],
Wang, Y.F.[Yi-Fei],
Geng, Z.Y.[Zheng-Yang],
Wang, Y.[Yisen],
Yang, J.S.[Jian-Sheng],
Lin, Z.C.[Zhou-Chen],
Equilibrium Image Denoising With Implicit Differentiation,
IP(32), 2023, pp. 1868-1881.
IEEE DOI
2303
Iterative methods, Image denoising, Computational modeling,
Training, Noise reduction, Mathematical models, Neural networks,
deep equilibrium models
BibRef
Geng, Y.L.[Yan-Lin],
Lin, T.[Tong],
Lin, Z.C.[Zhou-Chen],
Hao, P.W.[Peng-Wei],
Refined Exponential Filter with Applications to Image Restoration and
Interpolation,
ACCV09(III: 33-42).
Springer DOI
0909
BibRef
Lopez-Martinez, J.L.[Jose L.],
Kober, V.[Vitaly],
Blind Adaptive Method for Image Restoration Using Microscanning,
IEICE(E95-D), No. 1, January 2012, pp. 280-284.
WWW Link.
1201
Multiple images. each a sample of the scene.
BibRef
Zoubir, A.M.,
Koivunen, V.,
Chakhchoukh, Y.,
Muma, M.,
Robust Estimation in Signal Processing:
A Tutorial-Style Treatment of Fundamental Concepts,
SPMag(29), No. 4, 2012, pp. 61-80.
IEEE DOI
1206
BibRef
Yousefi, S.,
Kehtarnavaz, N.,
Cao, Y.,
Razlighi, Q.R.,
Bilateral Markov mesh random field and its application to image
restoration,
JVCIR(23), No. 7, October 2012, pp. 1051-1059.
Elsevier DOI
1209
Markov random fields; Bilateral Markov mesh random field; Image
modeling; Image restoration; Image processing; Texture analysis; Causal
Markov random field; Stochastic image analysis
BibRef
Lu, C.W.,
Image restoration and decomposition using nonconvex non-smooth
regularisation and negative Hilbert-Sobolev norm,
IET-IPR(6), No. 6, 2012, pp. 706-716.
DOI Link
1210
BibRef
Chen, X.J.[Xiao-Jun],
Ng, M.K.,
Zhang, C.[Chao],
Non-Lipschitz L_p-Regularization and Box Constrained Model for Image
Restoration,
IP(21), No. 12, December 2012, pp. 4709-4721.
IEEE DOI
1212
BibRef
Bian, W.[Wei],
Chen, X.J.[Xiao-Jun],
Linearly Constrained Non-Lipschitz Optimization for Image Restoration,
SIIMS(8), No. 4, 2015, pp. 2294-2322.
DOI Link
1601
BibRef
Zhou, J.T.[Jian-Tao],
Wu, X.L.[Xiao-Lin],
Zhang, L.[Lei],
L_2 Restoration of L_inf -Decoded Images Via Soft-Decision Estimation,
IP(21), No. 12, December 2012, pp. 4797-4807.
IEEE DOI
1212
BibRef
Zachariah, D.,
Skog, I.,
Jansson, M.,
Handel, P.,
Bayesian Estimation With Distance Bounds,
SPLetters(19), No. 12, December 2012, pp. 880-883.
IEEE DOI
1212
BibRef
Zachariah, D.,
Stoica, P.,
Cramer-Rao Bound Analog of Bayes' Rule,
SPMag(32), No. 2, March 2015, pp. 164-168.
IEEE DOI
1503
Lecture Notes.
Gaussian processes
BibRef
Sun, J.[Jian],
Tappen, M.F.[Marshall F.],
Separable Markov Random Field Model and Its Applications in Low Level
Vision,
IP(22), No. 1, January 2013, pp. 402-407.
IEEE DOI
1301
BibRef
Earlier:
Learning non-local range Markov Random field for image restoration,
CVPR11(2745-2752).
IEEE DOI
1106
BibRef
Deng, L.J.[Liang-Jian],
Huang, T.Z.[Ting-Zhu],
Zhao, X.L.[Xi-Le],
Zhao, L.[Liang],
Wang, S.[Si],
Signal restoration combining Tikhonov regularization and multilevel
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JOSA-A(30), No. 5, May 2013, pp. 948-955.
DOI Link
1305
See also Regularization of Ill-Posed Problems, The.
BibRef
Yousefi, S.,
Kehtarnavaz, N.,
Cao, Y.[Yan],
Computationally Tractable Stochastic Image Modeling Based on
Symmetric Markov Mesh Random Fields,
IP(22), No. 6, 2013, pp. 2192-2206.
IEEE DOI Markov processes; image restoration; Markov random fields
1307
BibRef
Wang, Y.Q.[Yi-Qing],
Morel, J.M.[Jean-Michel],
SURE Guided Gaussian Mixture Image Denoising,
SIIMS(6), No. 2, 2013, pp. 999-1034.
DOI Link
1307
Implementation:
See also Implementation of SURE Guided Piecewise Linear Image Denoising, The.
BibRef
Wang, Y.Q.[Yi-Qing],
The Implementation of SURE Guided Piecewise Linear Image Denoising,
IPOL(2012), No. 2012, pp. 52.
DOI Link
1309
See also SURE Guided Gaussian Mixture Image Denoising.
BibRef
He, J.P.[Jin-Ping],
Gao, K.[Kun],
Ni, G.Q.[Guo-Qiang],
Su, G.D.[Guang-Da],
Chen, J.S.[Jian-Sheng],
Learning from Ideal Edge for Image Restoration,
IEICE(E96-D), No. 11, November 2013, pp. 2487-2491.
WWW Link.
1311
BibRef
Lanza, A.[Alessandro],
Morigi, S.[Serena],
Sgallari, F.[Fiorella],
Yezzi, A.J.[Anthony J.],
Variational Image Denoising Based on Autocorrelation Whiteness,
SIIMS(6), No. 4, 2013, pp. 1931-1955.
DOI Link
1402
BibRef
Lanza, A.[Alessandro],
Morigi, S.[Serena],
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Sgallari, F.[Fiorella],
Whiteness Constraints in a Unified Variational Framework for Image
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JMIV(60), No. 9, November 2018, pp. 1503-1526.
Springer DOI
1810
BibRef
Lanza, A.[Alessandro],
Morigi, S.[Serena],
Sgallari, F.[Fiorella],
Variational Image Restoration with Constraints on Noise Whiteness,
JMIV(53), No. 1, September 2015, pp. 61-77.
Springer DOI
1505
BibRef
Lanza, A.[Alessandro],
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Sgallari, F.[Fiorella],
Convex Image Denoising via Non-convex Regularization with Parameter
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JMIV(56), No. 2, October 2016, pp. 195-220.
Springer DOI
1609
BibRef
Earlier:
Convex Image Denoising via Non-Convex Regularization,
SSVM15(666-677).
Springer DOI
1506
BibRef
Selesnick, I.[Ivan],
Lanza, A.[Alessandro],
Morigi, S.[Serena],
Sgallari, F.[Fiorella],
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JMIV(62), No. 6-7, July 2020, pp. 825-841.
Springer DOI
2007
BibRef
Lanza, A.[Alessandro],
Sciacchitano, F.[Federica],
Morigi, S.[Serena],
Sgallari, F.[Fiorella],
A Unified Framework for the Restoration of Images Corrupted by Additive
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SSVM17(498-510).
Springer DOI
1706
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Zhu, J.,
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Fidelity-Beltrami-Sparsity Model for Inverse Problems in Multichannel
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DOI Link
1402
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Liu, X.M.[Xian-Ming],
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Progressive Image Denoising Through Hybrid Graph Laplacian
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IEEE DOI
1404
Laplace transforms
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Moussallam, M.,
Gramfort, A.,
Daudet, L.,
Richard, G.,
Blind Denoising with Random Greedy Pursuits,
SPLetters(21), No. 11, November 2014, pp. 1341-1345.
IEEE DOI
1408
greedy algorithms
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Kim, K.,
Lee, J.,
Nonlinear Dynamic Projection for Noise Reduction of Dispersed
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PAMI(36), No. 11, November 2014, pp. 2303-2309.
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1410
Algorithm design and analysis
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Loizou, P.C.,
A Hybrid Coherence Model for Noise Reduction in Reverberant
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SPLetters(22), No. 3, March 2015, pp. 279-282.
IEEE DOI
1410
Coherence
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Imre, E.[Evren],
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Covariance estimation for minimal geometry solvers via scaled
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CVIU(130), No. 1, 2015, pp. 18-34.
Elsevier DOI
1411
Covariance estimation
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Zhao, S.,
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Fast Computation of Discrete Optimal FIR Estimates in White Gaussian
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SPLetters(22), No. 6, June 2015, pp. 718-722.
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1411
Iterative algorithm
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Sahoo, S.K.,
Makur, A.,
Enhancing Image Denoising by Controlling Noise Incursion in Learned
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SPLetters(22), No. 8, August 2015, pp. 1123-1126.
IEEE DOI
1502
image denoising
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McGaffin, M.G.,
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Edge-Preserving Image Denoising via Group Coordinate Descent on the
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IP(24), No. 4, April 2015, pp. 1273-1281.
IEEE DOI
1503
graphics processing units
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An optimized first-order method for image restoration,
ICIP15(3675-3679)
IEEE DOI
1512
First-order methods
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Yue, H.J.[Huan-Jing],
Sun, X.Y.[Xiao-Yan],
Yang, J.Y.[Jing-Yu],
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Image Denoising by Exploring External and Internal Correlations,
IP(24), No. 6, June 2015, pp. 1967-1982.
IEEE DOI
1504
BibRef
Earlier:
CID: Combined Image Denoising in Spatial and Frequency Domains Using
Web Images,
CVPR14(2933-2940)
IEEE DOI
1409
See also Landmark Image Super-Resolution by Retrieving Web Images. Accuracy
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Jalab, H.A.[Hamid A.],
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Fractional Conway Polynomials for Image Denoising with Regularized
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JMIV(51), No. 3, March 2015, pp. 442-450.
WWW Link.
1504
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Cohen, A.[Asaf],
When physics meets signal processing:
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SP:IC(34), No. 1, 2015, pp. 14-21.
Elsevier DOI
1505
Image denoising
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Jain, P.[Paras],
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VC(31), No. 5, May 2015, pp. 657-674.
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1505
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Moallem, P.[Payman],
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A novel adaptive Gaussian restoration filter for reducing periodic
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SIViP(9), No. 5, July 2015, pp. 1179-1191.
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1506
BibRef
Özkan, K.,
Seke, E.,
Image denoising using common vector approach,
IET-IPR(9), No. 8, 2015, pp. 709-715.
DOI Link
1506
estimation theory
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Pham, T.D.,
Estimating Parameters of Optimal Average and Adaptive Wiener Filters
for Image Restoration with Sequential Gaussian Simulation,
SPLetters(22), No. 11, November 2015, pp. 1950-1954.
IEEE DOI
1509
AWGN
BibRef
Zeng, X.,
Bian, W.,
Liu, W.,
Shen, J.,
Tao, D.,
Dictionary Pair Learning on Grassmann Manifolds for Image Denoising,
IP(24), No. 11, November 2015, pp. 4556-4569.
IEEE DOI
1509
Dictionaries
BibRef
Shen, X.Y.[Xiao-Yong],
Yan, Q.[Qiong],
Xu, L.[Li],
Ma, L.Z.[Li-Zhuang],
Jia, J.Y.[Jia-Ya],
Multispectral Joint Image Restoration via Optimizing a Scale Map,
PAMI(37), No. 12, December 2015, pp. 2518-2530.
IEEE DOI
1512
image colour analysis
BibRef
Shen, X.Y.[Xiao-Yong],
Zhou, C.[Chao],
Xu, L.[Li],
Jia, J.Y.[Jia-Ya],
Mutual-Structure for Joint Filtering,
IJCV(125), No. 1-3, December 2018, pp. 19-33.
Springer DOI
1711
BibRef
Earlier:
ICCV15(3406-3414)
IEEE DOI
1602
Filter a target image for structural information from a reference
image.
BibRef
Yan, Q.[Qiong],
Shen, X.Y.[Xiao-Yong],
Xu, L.[Li],
Zhuo, S.J.[Shao-Jie],
Zhang, X.P.[Xiao-Peng],
Shen, L.[Liang],
Jia, J.Y.[Jia-Ya],
Cross-Field Joint Image Restoration via Scale Map,
ICCV13(1537-1544)
IEEE DOI
1403
cross-field; denoise; image restoration; near-infrared
BibRef
Li, M.[Meng],
Ghosal, S.,
Fast Translation Invariant Multiscale Image Denoising,
IP(24), No. 12, December 2015, pp. 4876-4887.
IEEE DOI
1512
Gaussian noise
BibRef
Lu, X.[Xin],
Lin, Z.[Zhe],
Jin, H.L.[Hai-Lin],
Yang, J.C.[Jian-Chao],
Wang, J.Z.,
Image-Specific Prior Adaptation for Denoising,
IP(24), No. 12, December 2015, pp. 5469-5478.
IEEE DOI
1512
Gaussian processes
BibRef
Lu, X.[Xin],
Lin, Z.[Zhe],
Jin, H.L.[Hai-Lin],
Tree-Based Locally Linear Regression for Image Denoising,
WACV15(472-479)
IEEE DOI
1503
Databases;Noise level;Noise measurement;Noise reduction;PSNR;Training
BibRef
Portilla, J.,
Tristan-Vega, A.,
Selesnick, I.W.,
Efficient and Robust Image Restoration Using Multiple-Feature
L2-Relaxed Sparse Analysis Priors,
IP(24), No. 12, December 2015, pp. 5046-5059.
IEEE DOI
1512
Convergence
BibRef
Yu, L.[Lei],
Wei, C.[Chen],
Zheng, G.[Gang],
Adaptive Bayesian Estimation with Cluster Structured Sparsity,
SPLetters(22), No. 12, December 2015, pp. 2309-2313.
IEEE DOI
1512
adaptive estimation
BibRef
Azghani, M.,
Karimi, M.,
Marvasti, F.,
Multihypothesis Compressed Video Sensing Technique,
CirSysVideo(26), No. 4, April 2016, pp. 627-635.
IEEE DOI
1604
Cost function
See also Regularization of Ill-Posed Problems, The.
BibRef
Lei, Y.[Yang],
Song, Z.J.[Zhan-Jie],
Song, Q.W.[Qi-Wei],
Non-Convex Low-Rank Approximation for Image Denoising and Deblurring,
IEICE(E99-D), No. 5, May 2016, pp. 1364-1374.
WWW Link.
1605
BibRef
Al-Badrawi, M.H.,
Al-Jewad, B.Z.,
Smith, W.J.,
Kirsch, N.J.,
A De-noising Scheme Based on the Null Hypothesis of Intrinsic Mode
Functions,
SPLetters(23), No. 7, July 2016, pp. 924-928.
IEEE DOI
1608
signal denoising
BibRef
Smith, J.R.,
Al-Badrawi, M.H.,
Kirsch, N.J.,
An Optimized De-Noising Scheme Based on the Null Hypothesis of
Intrinsic Mode Functions,
SPLetters(26), No. 8, August 2019, pp. 1232-1236.
IEEE DOI
1908
computational complexity, filtering theory,
medical signal processing, Newton-Raphson method, noise,
signal de-noising
BibRef
Al-Badrawi, M.H.,
Kirsch, N.J.,
Al-Jewad, B.Z.,
Intrinsic Mode Function Based Noise Power Estimation With
Applications to Semiblind Spectrum Sensing Methods,
SPLetters(24), No. 7, July 2017, pp. 1088-1092.
IEEE DOI
1706
Detectors, Eigenvalues and eigenfunctions, Estimation,
Noise measurement, Signal to noise ratio,
Empirical mode decomposition (EMD),
intrinsic mode functions (IMFs), noise power estimation,
semiblind detectors, spectrum, sensing
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Dell'Acqua, P.[Pietro],
Nu-acceleration of statistical iterative methods for image restoration,
SIViP(10), No. 5, May 2016, pp. 927-934.
Springer DOI
1608
Landweber method.
BibRef
Luo, E.,
Chan, S.H.,
Nguyen, T.Q.,
Adaptive Image Denoising by Mixture Adaptation,
IP(25), No. 10, October 2016, pp. 4489-4503.
IEEE DOI
1610
Bayes methods
BibRef
Hong, H.Y.[Han-Yu],
Hua, X.[Xia],
Zhang, X.H.[Xiu-Hua],
Shi, Y.[Yu],
Multi-frame real image restoration based on double loops with
alternative maximum likelihood estimation,
SIViP(10), No. 8, November 2016, pp. 1489-1495.
WWW Link.
1610
BibRef
Ma, H.J.[Hong-Jin],
Nie, Y.F.[Yu-Feng],
An edge fusion scheme for image denoising based on anisotropic
diffusion models,
JVCIR(40, Part B), No. 1, 2016, pp. 406-417.
Elsevier DOI
1610
Image denoising
BibRef
Dong, J.L.[Jun-Liang],
Gao, J.B.[Jun-Bin],
Ju, F.[Fujiao],
Shen, J.H.[Jing-Hua],
Modulus Methods for Nonnegatively Constrained Image Restoration,
SIIMS(9), No. 3, 2016, pp. 1226-1246.
DOI Link
1610
BibRef
He, B.S.[Bing-Sheng],
Ma, F.[Feng],
Yuan, X.M.[Xiao-Ming],
Convergence Study on the Symmetric Version of ADMM with Larger Step
Sizes,
SIIMS(9), No. 3, 2016, pp. 1467-1501.
DOI Link
1610
ADMM: alternating direction method of multipliers.
Or: special split Bregman.
BibRef
Peker, E.[Eli],
Wiesel, A.[Ami],
Fitting Generalized Multivariate Huber Loss Functions,
SPLetters(23), No. 11, November 2016, pp. 1647-1651.
IEEE DOI
1609
least squares approximations
BibRef
Hu, R.,
Fu, Y.,
Chen, Z.,
Xiang, Y.,
Rong, R.,
Robust Sparse Signal Recovery in the Presence of the S alpha-S Noise,
SPLetters(23), No. 11, November 2016, pp. 1687-1691.
IEEE DOI
1609
function approximation
Symmetric alpha-stable noise.
BibRef
Jakhetiya, V.[Vinit],
Lin, W.S.[Wei-Si],
Jaiswal, S.I.P.[Sun-Il P.],
Guntuku, S.C.[Sharath Chandra],
Au, O.C.[Oscar C.],
Maximum a Posterior and Perceptually Motivated Reconstruction
Algorithm: A Generic Framework,
MultMed(19), No. 1, January 2017, pp. 93-106.
IEEE DOI
1612
Image edge detection
BibRef
Pang, J.H.[Jia-Hao],
Cheung, G.[Gene],
Graph Laplacian Regularization for Image Denoising:
Analysis in the Continuous Domain,
IP(26), No. 4, April 2017, pp. 1770-1785.
IEEE DOI
1704
diffusion
BibRef
Pierazzo, N.[Nicola],
Facciolo, G.[Gabriele],
Data Adaptive Dual Domain Denoising: a Method to Boost State of the
Art Denoising Algorithms,
IPOL(7), 2017, pp. 93-114.
DOI Link
1706
BibRef
Pierazzo, N.[Nicola],
Rais, M.E.,
Morel, J.M.[Jean-Michel],
Facciolo, G.[Gabriele],
DA3D: Fast and data adaptive dual domain denoising,
ICIP15(432-436)
IEEE DOI
1512
BibRef
Earlier: A1, A3, A4, Only:
Optimizing the Data Adaptive Dual Domain Denoising Algorithm,
CIARP15(358-365).
Springer DOI
1511
Data Adaptive
BibRef
Pierazzo, N.[Nicola],
Morel, J.M.[Jean-Michel],
Facciolo, G.[Gabriele],
Multi-Scale DCT Denoising,
IPOL(7), 2017, pp. 288-308.
DOI Link
1712
BibRef
Facciolo, G.[Gabriele],
Pierazzo, N.[Nicola],
Morel, J.M.[Jean-Michel],
Conservative Scale Recomposition for Multiscale Denoising (The Devil
is in the High Frequency Detail),
SIIMS(10), No. 3, 2017, pp. 1603-1626.
DOI Link
1710
BibRef
Arias, P.[Pablo],
Morel, J.M.[Jean-Michel],
Video Denoising via Empirical Bayesian Estimation of Space-Time Patches,
JMIV(60), No. 1, January 2018, pp. 70-93.
Springer DOI
1801
BibRef
Pierazzo, N.,
Lebrun, M.,
Rais, M.E.,
Morel, J.M.,
Facciolo, G.,
Non-local dual image denoising,
ICIP14(813-817)
IEEE DOI
1502
Frequency-domain analysis
BibRef
Wong, K.M.[Kin-Ming],
Wong, T.T.[Tien-Tsin],
Blue noise sampling using an N-body simulation-based method,
VC(33), No. 6-8, June 2017, pp. 823-832.
WWW Link.
1706
BibRef
Cornel, D.[Daniel],
Tobler, R.F.[Robert F.],
Sakai, H.[Hiroyuki],
Luksch, C.[Christian],
Wimmer, M.[Michael],
Forced Random Sampling:
Fast generation of importance-guided blue-noise samples,
VC(33), No. 6-8, June 2017, pp. 833-843.
Springer DOI
1706
BibRef
Yang, C.C.,
Guo, S.M.,
Tsai, J.S.H.,
Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising,
Cyber(47), No. 9, September 2017, pp. 2862-2871.
IEEE DOI
1708
Cameras, Encoding, Fuzzy logic, Fuzzy sets, Image denoising,
Noise measurement, Noise reduction, Camera raw image,
differential evolution, fuzzy logic system (FLS), image denoising
BibRef
Liu, J.[Jing],
Liu, R.J.[Rui-Jiao],
Wang, Y.H.[Ying-Hui],
Chen, J.L.[Jin-Lei],
Yang, Y.J.[Ya-Jie],
Ma, D.L.[Dou-Li],
Image denoising searching similar blocks along edge directions,
SP:IC(57), No. 1, 2017, pp. 33-45.
Elsevier DOI
1709
Similar block
BibRef
Xu, J.T.[Jiang-Tao],
Nie, H.F.[Hua-Feng],
Nie, K.[Kaiming],
Jin, W.M.[Wei-Min],
Fixed-pattern noise correction method based on improved moment
matching for a TDI CMOS image sensor,
JOSA-A(34), No. 9, September 2017, pp. 1500-1510.
DOI Link
1709
Image reconstruction-restoration, Noise in imaging systems,
Optical sensing and sensors
BibRef
Boccuto, A.[Antonio],
Gerace, I.[Ivan],
Martinelli, F.[Francesca],
Half-Quadratic Image Restoration with a Non-parallelism Constraint,
JMIV(59), No. 2, October 2017, pp. 270-295.
Springer DOI
1709
BibRef
Wang, Q.,
Zhang, X.,
Wu, Y.,
Tang, L.,
Zha, Z.,
Nonconvex Weighted L_p Minimization Based Group Sparse Representation
Framework for Image Denoising,
SPLetters(24), No. 11, November 2017, pp. 1686-1690.
IEEE DOI
1710
Dictionaries, Image denoising, Minimization, Noise measurement,
Noise reduction, Sparse matrices,
Adaptive patch search (APS),
generalized soft-thresholding (GST) algorithm, group sparsity,
image denoising, weighted, L_p, minimization
BibRef
Diop, E.S.[El_Hadji S.],
Alexandre, R.[Radjesvarane],
Boudraa, A.O.[Abdel O.],
Two-Dimensional Curvature-Based Analysis of Intrinsic Mode Functions,
SPLetters(25), No. 1, January 2018, pp. 20-24.
IEEE DOI
1801
empirical mode decomposition (EMD).
image processing, partial differential equations,
2D EMD algorithms, 2D curvature based analysis,
partial differential equations.
BibRef
Siadat, M.[Medya],
Aghazadeh, N.[Nasser],
Öktem, O.[Ozan],
Reordering for improving global Arnoldi-Tikhonov method in image
restoration problems,
SIViP(12), No. 3, March 2018, pp. 497-504.
WWW Link.
1804
BibRef
Milanfar, P.[Peyman],
Rendition: Reclaiming What a Black Box Takes Away,
SIIMS(11), No. 4, 2018, pp. 2722-2756.
DOI Link
1901
Recover the image which has been modified by some unknown process.
BibRef
Zeng, C.[Chao],
Jia, R.[Rui],
Wu, C.L.[Chun-Lin],
An Iterative Support Shrinking Algorithm for Non-Lipschitz Optimization
in Image Restoration,
JMIV(61), No. 1, January 2019, pp. 122-139.
Springer DOI
1901
BibRef
Liu, Z.W.[Zhan-Wen],
Gao, T.[Tao],
Kong, F.J.[Fan-Jie],
Jiao, Z.H.[Zi-Heng],
Yang, A.[Aodong],
Li, S.Y.[Shu-Ying],
Liu, B.[Bo],
Restoration algorithm for noisy complex illumination,
IET-CV(13), No. 2, March 2019, pp. 224-232.
DOI Link
1902
BibRef
Baloch, G.[Gulsher],
Ahmed, J.[Junaid],
Enhancing proximity measure between residual and noise for image
denoising,
IJCVR(9), No. 1, 2019, pp. 56-69.
DOI Link
1903
BibRef
Ge, H.M.[Huan-Min],
Wang, L.[Libo],
Wen, J.M.[Jin-Ming],
Xian, J.[Jun],
An RIP Condition for Exact Support Recovery With Covariance-Assisted
Matching Pursuit,
SPLetters(26), No. 3, March 2019, pp. 520-524.
IEEE DOI
1903
covariance matrices, Gaussian noise, iterative methods,
signal reconstruction, sparse matrices, RIP condition,
sparse recovery
BibRef
Jaouen, V.,
Bert, J.,
Boussion, N.,
Fayad, H.,
Hatt, M.,
Visvikis, D.,
Image Enhancement With PDEs and Nonconservative Advection Flow Fields,
IP(28), No. 6, June 2019, pp. 3075-3088.
IEEE DOI
1905
Image edge detection, Electric shock, Measurement,
Image restoration, Image enhancement, AWGN, Smoothing methods,
anisotropic diffusion
BibRef
Li, S.,
Qin, B.,
Xiao, J.,
Liu, Q.,
Wang, Y.,
Liang, D.,
Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale
Image Restoration,
IP(29), No. 1, 2020, pp. 142-156.
IEEE DOI
1910
image colour analysis, image denoising, image restoration,
iterative methods, learning (artificial intelligence),
proximal gradient descent
BibRef
Zhao, Q.[Qiang],
Du, Q.Z.[Qi-Zhen],
Sun, W.H.[Wen-Han],
Chen, Y.K.[Yang-Kang],
Iterative Double Laplacian-Scaled Low-Rank Optimization for
Under-Sampled and Noisy Signal Recovery,
GeoRS(57), No. 11, November 2019, pp. 9177-9187.
IEEE DOI
1911
Estimation, Data models, Noise measurement, Minimization,
Analytical models, Optimization, Task analysis, Erratic noise,
reweighted L1 minimization
BibRef
Fan, S.[Sihui],
Han, W.[Wei],
Gao, Z.Q.[Zhi-Qiu],
Yin, R.Y.[Ruo-Ying],
Zheng, Y.[Yu],
Denoising Algorithm for the FY-4A GIIRS Based on Principal Component
Analysis,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Zha, Z.Y.[Zhi-Yuan],
Yuan, X.[Xin],
Wen, B.H.[Bi-Han],
Zhou, J.T.[Jian-Tao],
Zhang, J.C.[Jia-Chao],
Zhu, C.[Ce],
From Rank Estimation to Rank Approximation: Rank Residual Constraint
for Image Restoration,
IP(29), 2020, pp. 3254-3269.
IEEE DOI
2002
Low-rank, rank residual constraint, nuclear norm minimization,
nonlocal self-similarity, group-based sparse representation, image restoration
BibRef
Zha, Z.Y.[Zhi-Yuan],
Yuan, X.[Xin],
Wen, B.H.[Bi-Han],
Zhou, J.T.[Jian-Tao],
Zhu, C.[Ce],
Group Sparsity Residual Constraint With Non-Local Priors for Image
Restoration,
IP(29), 2020, pp. 8960-8975.
IEEE DOI
2009
Image restoration, Estimation, Minimization, Dictionaries,
Task analysis, Adaptation models, Degradation, Image restoration,
nonlocal self-similarity
BibRef
Zha, Z.Y.[Zhi-Yuan],
Wen, B.H.[Bi-Han],
Yuan, X.[Xin],
Zhou, J.T.Y.[Joey Tian-Yi],
Zhou, J.T.[Jian-Tao],
Zhu, C.[Ce],
Triply Complementary Priors for Image Restoration,
IP(30), 2021, pp. 5819-5834.
IEEE DOI
2106
Image restoration, Training, Task analysis, Image reconstruction,
Degradation, Noise reduction, Inverse problems, Image restoration,
hybrid plug-and-play
BibRef
Zha, Z.Y.[Zhi-Yuan],
Wen, B.H.[Bi-Han],
Zhang, J.C.[Jia-Chao],
Zhou, J.T.[Jian-Tao],
Zhu, C.[Ce],
A Comparative Study for the Nuclear Norms Minimization Methods,
ICIP19(2050-2054)
IEEE DOI
1910
Low-rank matrix approximation, NNM, WNNM, GSR, image denoising
BibRef
Wang, H.,
Li, Y.,
Cen, Y.,
He, Z.,
Multi-Matrices Low-Rank Decomposition With Structural Smoothness for
Image Denoising,
CirSysVideo(30), No. 2, February 2020, pp. 349-361.
IEEE DOI
2002
Matrix decomposition, Sparse matrices, TV, Image reconstruction,
Image restoration, Noise measurement, Optimization,
matrices tri-factorization
BibRef
Barbeiro, S.[Sílvia],
Lobo, D.[Diogo],
Learning Stable Nonlinear Cross-Diffusion Models for Image Restoration,
JMIV(62), No. 2, February 2020, pp. 223-237.
Springer DOI
2002
BibRef
Fernández-Menduiña, S.[Samuel],
Pérez-González, F.[Fernando],
Temporal Localization of Non-Static Digital Videos Using the
Electrical Network Frequency,
SPLetters(27), 2020, pp. 745-749.
IEEE DOI
2006
underlying signal in video.
Videos, Estimation, Frequency estimation, Phase locked loops,
Frequency modulation, Demodulation, Time-frequency analysis, ENF,
non-static videos
BibRef
Wu, G.M.[Ge-Ming],
Luo, S.Q.[Shu-Qian],
Yang, Z.[Zhi],
Optimal weighted bilateral filter with dual-range kernel for Gaussian
noise removal,
IET-IPR(14), No. 9, 20 July 2020, pp. 1840-1850.
DOI Link
2007
BibRef
Liu, R.S.[Ri-Sheng],
Mu, P.[Pan],
Chen, J.[Jian],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Investigating Task-Driven Latent Feasibility for Nonconvex Image
Modeling,
IP(29), 2020, pp. 7629-7640.
IEEE DOI
2007
Low-level vision, nonconvex image modeling,
task-driven feasibility, maximum a posterior
BibRef
Valsesia, D.[Diego],
Fracastoro, G.[Giulia],
Magli, E.[Enrico],
Deep Graph-Convolutional Image Denoising,
IP(29), 2020, pp. 8226-8237.
IEEE DOI
2008
BibRef
Earlier:
Image Denoising with Graph-Convolutional Neural Networks,
ICIP19(2399-2403)
IEEE DOI
1910
Convolution, Noise reduction, Image denoising,
Biological neural networks,
graph convolution.
BibRef
Gong, X.[Xiao],
Chen, W.[Wei],
Chen, J.[Jie],
Ai, B.[Bo],
Tensor Denoising Using Low-Rank Tensor Train Decomposition,
SPLetters(27), 2020, pp. 1685-1689.
IEEE DOI
1806
Tensile stress, Noise reduction, Matrix decomposition, Indexes,
Signal processing, Machine learning,
tensor decomposition
BibRef
Tian, X.[Xin],
Chen, W.[Wei],
Zhao, F.[Fang],
Li, B.[Bo],
Wang, Z.Y.[Zhong-Yuan],
Robust CBCT Reconstruction Based On Low-Rank Tensor Decomposition And
Total Variation Regularization,
ICIP20(330-334)
IEEE DOI
2011
Image reconstruction, TV, Tensile stress,
Robustness,
total variation
BibRef
Ou, Y.[Yang],
Luo, J.Q.[Jian-Qiao],
Li, B.L.[Bai-Lin],
Swamy, M.N.S.,
Gray-level image denoising with an improved weighted sparse coding,
JVCIR(72), 2020, pp. 102895.
Elsevier DOI
2010
Image denoising, Nonlocal self-similarity, Weight matrix, Weighted sparse coding
BibRef
Wang, Y.Y.[Yi-Yang],
Ma, L.[Long],
Liu, R.S.[Ri-Sheng],
A convergent framework with learnable feasibility for Hadamard-based
image recovery,
CVIU(202), 2021, pp. 103095.
Elsevier DOI
2012
Image recovery, Hadamard product, Data-driven feasibility,
Learning paradigm, Coordinate update
BibRef
Xiao, J.[Jie],
Jin, Z.[Zhi],
Zhang, H.R.[Huan-Rong],
A general model compression method for image restoration network,
SP:IC(93), 2021, pp. 116134.
Elsevier DOI
2103
Model compression, Image restoration,
Deformable convolution kernel, Attention mechanism
BibRef
Gao, Q.X.[Quan-Xue],
Zhang, P.[Pu],
Xia, W.[Wei],
Xie, D.[Deyan],
Gao, X.B.[Xin-Bo],
Tao, D.C.[Da-Cheng],
Enhanced Tensor RPCA and its Application,
PAMI(43), No. 6, June 2021, pp. 2133-2140.
IEEE DOI
2106
Tensors, Minimization, Image color analysis,
Principal component analysis, Periodic structures,
multidimensional image denoising
BibRef
Zha, Z.Y.[Zhi-Yuan],
Wen, B.[Bihan],
Yuan, X.[Xin],
Zhou, J.T.[Jian-Tao],
Zhu, C.[Ce],
Image Restoration via Reconciliation of Group Sparsity and Low-Rank
Models,
IP(30), 2021, pp. 5223-5238.
IEEE DOI
2106
Image restoration, Image coding, Dictionaries, Adaptation models,
Minimization, Image denoising, Sparse matrices,
image restoration
BibRef
Pei, Y.T.[Yan-Ting],
Huang, Y.P.[Ya-Ping],
Zhang, X.Y.[Xing-Yuan],
Consistency Guided Network for Degraded Image Classification,
CirSysVideo(31), No. 6, June 2021, pp. 2231-2246.
IEEE DOI
2106
Visualization, Image resolution, Image restoration, Semantics,
Task analysis, Heating systems, Degradation, Image classification,
visual attention alignment loss
BibRef
Premnath, S.P.,
Renjit, J.A.[J. Arokia],
Image restoration model using Jaya-Bat optimization-enabled noise
prediction map,
IET-IPR(15), No. 9, 2021, pp. 1926-1939.
DOI Link
2106
BibRef
Malladi, S.R.S.P.[Sree Ramya S. P.],
Ram, S.[Sundaresh],
Rodríguez, J.J.[Jeffrey J.],
Image Denoising Using Superpixel-Based PCA,
MultMed(23), 2021, pp. 2297-2309.
IEEE DOI
2108
Principal component analysis, Noise reduction, Noise measurement,
Transforms, Image denoising, Decorrelation, Noise level,
patch-based method
BibRef
Zhou, R.[Rui],
Han, J.T.[Jiang-Tao],
Guo, Z.Y.[Zhen-Yu],
Li, T.L.[Tong-Lin],
De-Noising of Magnetotelluric Signals by Discrete Wavelet Transform
and SVD Decomposition,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ko, K.[Keunsoo],
Koh, Y.J.[Yeong Jun],
Kim, C.S.[Chang-Su],
Blind and Compact Denoising Network Based on Noise Order Learning,
IP(31), 2022, pp. 1657-1670.
IEEE DOI
2202
Noise reduction, Feature extraction, Noise measurement,
Image denoising, Complexity theory, Training, Noise level,
convolutional neural network
BibRef
Monma, Y.[Yuki],
Aro, K.[Kan],
Yasuda, M.[Muneki],
Hierarchical Gaussian Markov Random Field for Image Denoising,
IEICE(E105-D), No. 3, March 2022, pp. 689-699.
WWW Link.
2203
BibRef
Li, P.L.[Peng-Liang],
Liang, J.L.[Jun-Li],
Zhang, M.[Miaohua],
Fan, W.[Wen],
Yu, G.Y.[Guo-Yang],
Joint image denoising with gradient direction and edge-preserving
regularization,
PR(125), 2022, pp. 108506.
Elsevier DOI
2203
Joint image denoising, Gradient direction,
Majorization minimization, Nonlinear optimization, Nonconvex optimization
BibRef
Mou, C.[Chong],
Zhang, J.[Jian],
Fan, X.P.[Xiao-Peng],
Liu, H.F.[Hang-Fan],
Wang, R.G.[Rong-Gang],
COLA-Net: Collaborative Attention Network for Image Restoration,
MultMed(24), 2022, pp. 1366-1377.
IEEE DOI
2204
Image restoration, Task analysis, Collaboration, Image denoising,
Finite element analysis, Training,
image restoration
BibRef
Tomita, K.[Keigo],
Tsutake, C.[Chihiro],
Takahashi, K.[Keita],
Fujii, T.[Toshiaki],
Denoising multi-view images by soft thresholding:
A short-time DFT approach,
SP:IC(105), 2022, pp. 116710.
Elsevier DOI
2205
Multi-view images, Denoising, Short-time DFT, Soft thresholding, Model selection
BibRef
Abedini, M.[Maryam],
Haddad, H.[Horriyeh],
Masouleh, M.F.[Marzieh Faridi],
Shahbahrami, A.[Asadollah],
Image Denoising Using Sparse Representation and Principal Component
Analysis,
IJIG(22), No. 4, July 2022, pp. 2250033.
DOI Link
2208
BibRef
Yin, H.T.[Hai-Tao],
Ma, S.Y.[Si-Yuan],
CSformer: Cross-Scale Features Fusion Based Transformer for Image
Denoising,
SPLetters(29), 2022, pp. 1809-1813.
IEEE DOI
2209
Transformers, Feature extraction, Convolution, Noise measurement,
Image denoising, Noise reduction, Noise level, Cross-scale,
transformer
BibRef
Pan, X.G.[Xin-Gang],
Zhan, X.H.[Xiao-Hang],
Dai, B.[Bo],
Lin, D.[Dahua],
Loy, C.C.[Chen Change],
Luo, P.[Ping],
Exploiting Deep Generative Prior for Versatile Image Restoration and
Manipulation,
PAMI(44), No. 11, November 2022, pp. 7474-7489.
IEEE DOI
2210
BibRef
Earlier:
ECCV20(II:262-277).
Springer DOI
2011
Image reconstruction, Generative adversarial networks,
Image restoration, Generators, Task analysis, Image color analysis
BibRef
Yu, Z.[Zhi],
Luo, Y.H.[Yi-Hao],
Liu, Z.F.[Zhi-Fa],
Zhou, G.X.[Guo-Xu],
Contour information regularized tensor ring completion for realistic
image restoration,
IET-IPR(16), No. 13, 2022, pp. 3499-3506.
DOI Link
2210
BibRef
Wu, D.[Di],
Zhang, T.[Tao],
Corrected rank residual constraint model for image denoising,
IET-IPR(16), No. 13, 2022, pp. 3659-3668.
DOI Link
2210
BibRef
Xu, S.P.[Shao-Ping],
Chen, X.J.[Xiao-Jun],
Luo, J.[Jie],
Cheng, X.H.[Xiao-Hui],
Xiao, N.[Nan],
An unsupervised fusion network for boosting denoising performance,
JVCIR(88), 2022, pp. 103626.
Elsevier DOI
2210
Merge multiple denoising results.
Image denoising, Boosting denoising performance,
Deep fusion network, Unsupervised training strategy
BibRef
He, J.W.[Jing-Wen],
Dong, C.[Chao],
Liu, Y.H.[Yi-Hao],
Qiao, Y.[Yu],
Interactive Multi-Dimension Modulation for Image Restoration,
PAMI(44), No. 12, December 2022, pp. 9363-9379.
IEEE DOI
2212
Degradation, Modulation, Image restoration, Task analysis,
Noise reduction, Estimation, Adaptation models, Image restoration, deep learning
BibRef
Punnappurath, A.[Abhijith],
Brown, M.S.[Michael S.],
A Little Bit More: Bitplane-Wise Bit-Depth Recovery,
PAMI(44), No. 12, December 2022, pp. 9718-9724.
IEEE DOI
2212
Training, Quantization (signal), Deep learning, Image restoration,
Standards, Task analysis, Network architecture, Bit depth, bitplane,
image restoration
BibRef
Gajamannage, K.[Kelum],
Park, Y.G.[Yong-Gi],
Sadovski, A.[Alexey],
Geodesic Gramian denoising applied to the images contaminated with
noise sampled from diverse probability distributions,
IET-IPR(17), No. 1, 2023, pp. 144-156.
DOI Link
2301
BibRef
Zhang, Z.W.[Zhen-Wei],
Chen, K.[Ke],
Tang, K.[Ke],
Duan, Y.P.[Yu-Ping],
Fast Multi-Grid Methods for Minimizing Curvature Energies,
IP(32), 2023, pp. 1716-1731.
IEEE DOI
2303
Minimization, Computational modeling, Image restoration,
Image reconstruction, Convergence, Surface treatment
BibRef
Pan, Y.Z.[Yi-Zhong],
Ren, C.[Chao],
Wu, X.H.[Xiao-Hong],
Huang, J.[Jie],
He, X.H.[Xiao-Hai],
Real Image Denoising via Guided Residual Estimation and Noise
Correction,
CirSysVideo(33), No. 4, April 2023, pp. 1994-2000.
IEEE DOI
2304
Noise reduction, Noise level, Noise measurement, Image denoising,
Iterative methods, Image reconstruction, Estimation,
guided residual estimation
BibRef
Liu, J.[Jun],
Liu, R.W.[Ryan Wen],
Sun, J.N.[Jia-Ning],
Zeng, T.Y.[Tie-Yong],
Rank-One Prior: Real-Time Scene Recovery,
PAMI(45), No. 7, July 2023, pp. 8845-8860.
IEEE DOI
2306
BibRef
Earlier:
Rank-One Prior: Toward Real-Time Scene Recovery,
CVPR21(14797-14805)
IEEE DOI
2111
Image color analysis, Image enhancement, Imaging,
Image restoration, Scattering, Learning systems, Attenuation, Haze,
unified spectrum.
Learning systems, Visualization,
Estimation, Training data, Video surveillance
BibRef
Shen, L.[Lili],
Zhao, B.[Bo],
Li, Q.[Qunxia],
Zhang, C.[Chuhe],
Sun, X.[Xichun],
Peng, B.[Bo],
Local to non-local:
Multi-scale progressive attention network for image restoration,
CVIU(233), 2023, pp. 103725.
Elsevier DOI
2307
Image restoration, Convolutional neural networks,
Single-scale feature enhancement, Multi-scale feature fusion,
Window-dilation self-attention
BibRef
Liu, L.[Lin],
Xie, L.X.[Ling-Xi],
Zhang, X.P.[Xiao-Peng],
Yuan, S.X.[Shan-Xin],
Chen, X.Y.[Xiang-Yu],
Zhou, W.G.[Wen-Gang],
Li, H.Q.[Hou-Qiang],
Tian, Q.[Qi],
TAPE: Task-Agnostic Prior Embedding for Image Restoration,
ECCV22(XVIII:447-464).
Springer DOI
2211
BibRef
Jiang, Y.F.[Yi-Fan],
Wronski, B.[Bartlomiej],
Mildenhall, B.[Ben],
Barron, J.T.[Jonathan T.],
Wang, Z.Y.[Zhang-Yang],
Xue, T.F.[Tian-Fan],
Fast and High Quality Image Denoising via Malleable Convolution,
ECCV22(XVIII:429-446).
Springer DOI
2211
BibRef
Zhang, Z.X.[Zhong-Xing],
Liu, H.[Hui],
Guo, Q.[Qiang],
Image Restoration Using Probability-Inducing Nuclear Norm
Minimization,
ICIP22(2666-2670)
IEEE DOI
2211
Image quality, Codes, Superresolution, Noise reduction, Minimization,
Approximation algorithms, Image restoration, Image restoration,
nuclear norm minimization
BibRef
Li, B.[Boyun],
Liu, X.[Xiao],
Hu, P.[Peng],
Wu, Z.Q.[Zhong-Qin],
Lv, J.C.[Jian-Cheng],
Peng, X.[Xi],
All-In-One Image Restoration for Unknown Corruption,
CVPR22(17431-17441)
IEEE DOI
2210
Degradation, Photography, Codes, Image restoration,
Pattern recognition, Low-level vision, Computational photography
BibRef
Shin, W.[Wooksu],
Ahn, N.[Namhyuk],
Moon, J.H.[Jeong-Hyeon],
Sohn, K.A.[Kyung-Ah],
Exploiting Distortion Information for Multi-degraded Image
Restoration,
NTIRE22(536-545)
IEEE DOI
2210
Training, Knowledge engineering, Image recognition, Fuses,
Supervised learning, Distortion, Image restoration
BibRef
Choi, J.Y.[Joo-Young],
Lee, J.[Jungbeom],
Shin, C.[Chaehun],
Kim, S.[Sungwon],
Kim, H.W.[Hyun-Woo],
Yoon, S.[Sungroh],
Perception Prioritized Training of Diffusion Models,
CVPR22(11462-11471)
IEEE DOI
2210
Training, Visualization, Computational modeling, Noise reduction,
Data models, Image restoration, Pattern recognition,
Image and video synthesis and generation
BibRef
Lee, H.[Hunsang],
Choi, H.[Hyesong],
Sohn, K.H.[Kwang-Hoon],
Min, D.B.[Dong-Bo],
KNN Local Attention for Image Restoration,
CVPR22(2129-2139)
IEEE DOI
2210
Image color analysis, Focusing, Machine learning, Transformers,
Image restoration, Pattern recognition, Task analysis,
Machine learning
BibRef
Zhang, Y.[Yi],
Li, D.[Dasong],
Law, K.L.[Ka Lung],
Wang, X.G.[Xiao-Gang],
Qin, H.W.[Hong-Wei],
Li, H.S.[Hong-Sheng],
IDR: Self-Supervised Image Denoising via Iterative Data Refinement,
CVPR22(2088-2097)
IEEE DOI
2210
Training, Codes, Noise reduction, Benchmark testing,
Approximation algorithms, Pattern recognition, Low-level vision,
Datasets and evaluation
BibRef
Koh, J.[Jaihyun],
Lee, J.[Jangho],
Yoon, S.[Sungroh],
BNUDC: A Two-Branched Deep Neural Network for Restoring Images from
Under-Display Cameras,
CVPR22(1940-1949)
IEEE DOI
2210
Degradation, Deep learning, Training, Image color analysis,
Neural networks, Transforms, Cameras, Low-level vision,
Vision applications and systems
BibRef
Dutta, S.[Sayantan],
Basarab, A.[Adrian],
Georgeot, B.[Bertrand],
Kouamé, D.[Denis],
Image Denoising Inspired by Quantum Many-Body physics,
ICIP21(1619-1623)
IEEE DOI
2201
Wavelet transforms, Quantum computing, AWGN, Noise reduction,
Redundancy, Quantum mechanics, Filtering theory, quantum image processing.
BibRef
Kawar, B.[Bahjat],
Vaksman, G.[Gregory],
Elad, M.[Michael],
Stochastic Image Denoising by Sampling from the Posterior
Distribution,
AIM21(1866-1875)
IEEE DOI
2112
Uncertainty, Heuristic algorithms, Noise reduction,
Measurement uncertainty, Stochastic processes, Size measurement
BibRef
Ke, J.J.[Jun-Jie],
Wang, Q.F.[Qi-Fei],
Wang, Y.L.[Yi-Lin],
Milanfar, P.[Peyman],
Yang, F.[Feng],
MUSIQ: Multi-Scale Image Quality Transformer,
ICCV21(5128-5137)
IEEE DOI
2203
Image quality, Training, Degradation, Visualization, Shape,
Image representation, Transformers,
Vision applications and systems
BibRef
Ohayon, G.[Guy],
Adrai, T.[Theo],
Vaksman, G.[Gregory],
Elad, M.[Michael],
Milanfar, P.[Peyman],
High Perceptual Quality Image Denoising with a Posterior Sampling
CGAN,
AIM21(1805-1813)
IEEE DOI
2112
Deep learning, Noise reduction, Force,
Distortion, Generative adversarial networks, Generators
BibRef
Liu, Y.[Yang],
Qin, Z.[Zhenyue],
Anwar, S.[Saeed],
Ji, P.[Pan],
Kim, D.[Dongwoo],
Caldwell, S.[Sabrina],
Gedeon, T.[Tom],
Invertible Denoising Network: A Light Solution for Real Noise Removal,
CVPR21(13360-13369)
IEEE DOI
2111
Codes, Computational modeling, Noise reduction,
Transforms, Image restoration, Pattern recognition
BibRef
Mo, H.C.[Hong-Cheng],
Jiang, J.F.[Jian-Fei],
Wang, Q.[Qin],
Yin, D.[Dong],
Dong, P.Y.[Peng-Yu],
Tian, J.J.[Jing-Jun],
Frequency Attention Network: Blind Noise Removal for Real Images,
ACCV20(II:168-184).
Springer DOI
2103
BibRef
Zhu, M.Z.[Ming-Zhu],
Gao, Z.[Zhang],
Yu, J.Z.[Jun-Zhi],
He, B.W.[Bing-Wei],
Liu, J.T.[Jian-Tao],
ALRe: Outlier Detection for Guided Refinement,
ECCV20(VII:788-802).
Springer DOI
2011
BibRef
Li, X.[Xin],
Jin, X.[Xin],
Lin, J.X.[Jian-Xin],
Liu, S.[Sen],
Wu, Y.J.[Yao-Jun],
Yu, T.[Tao],
Zhou, W.[Wei],
Chen, Z.B.[Zhi-Bo],
Learning Disentangled Feature Representation for Hybrid-Distorted Image
Restoration,
ECCV20(XXIX: 313-329).
Springer DOI
2010
image that is degraded by multiple distortions.
BibRef
Wang, W.,
Guo, R.,
Tian, Y.,
Yang, W.,
CFSNet: Toward a Controllable Feature Space for Image Restoration,
ICCV19(4139-4148)
IEEE DOI
2004
Code, Image Restoration.
WWW Link. image reconstruction, image resolution, image restoration,
learning (artificial intelligence), Distortion
BibRef
Anwar, S.,
Barnes, N.,
Real Image Denoising With Feature Attention,
ICCV19(3155-3164)
IEEE DOI
2004
convolutional neural nets, image denoising, image denoising,
feature attention, convolutional neural networks,
Computational modeling
BibRef
Potts, C.,
Yang, L.,
Oyen, D.,
Wohlberg, B.,
A Topological Graph-Based Representation for Denoising Low Quality
Binary Images,
SGRL19(1788-1798)
IEEE DOI
2004
feature extraction, graph theory, image denoising,
image resolution, learning (artificial intelligence),
image representation
BibRef
Marinc, T.,
Srinivasan, V.,
Gül, S.,
Hellge, C.,
Samek, W.,
Multi-Kernel Prediction Networks for Denoising of Burst Images,
ICIP19(2404-2408)
IEEE DOI
1910
Burst Image Denoising, Kernel Fusion, Deep Learning, Kernel Prediction Network
BibRef
Kim, Y.,
Soh, J.W.,
Cho, N.I.,
Adaptively Tuning a Convolutional Neural Network by Gating Process
for Image Denoising,
ICIP19(1800-1804)
IEEE DOI
1910
Denoising, Convolutional Neural Network, Adaptive Denoising,
Gated Denoising, Noise Level Gated Denoising
BibRef
Lempitsky, V.,
Vedaldi, A.,
Ulyanov, D.,
Deep Image Prior,
CVPR18(9446-9454)
IEEE DOI
1812
Image restoration, Image resolution, Noise reduction,
Task analysis, Optimization, Generators, Image reconstruction
BibRef
Dorta, G.[Garoe],
Vicente, S.[Sara],
Agapito, L.[Lourdes],
Campbell, N.D.F.[Neill D. F.],
Simpson, I.[Ivor],
Structured Uncertainty Prediction Networks,
CVPR18(5477-5485)
IEEE DOI
1812
Image reconstruction, Uncertainty, Covariance matrices,
Predictive models, Data models, Sparse matrices, Estimation
BibRef
Chen, J.W.[Jing-Wen],
Chen, J.W.[Jia-Wei],
Chao, H.Y.[Hong-Yang],
Yang, M.[Ming],
Image Blind Denoising with Generative Adversarial Network Based Noise
Modeling,
CVPR18(3155-3164)
IEEE DOI
1812
Noise reduction,
Generative adversarial networks, Noise measurement, Training,
Adaptation models
BibRef
Choi, S.,
Isidoro, J.,
Getreuer, P.,
Milanfar, P.,
Fast, Trainable, Multiscale Denoising,
ICIP18(963-967)
IEEE DOI
1809
Noise reduction, Noise measurement, Kernel, Tensile stress,
Pipelines, Noise level, Blades, Image denoising, filter learning, multiscale
BibRef
Wang, H.M.[He-Ming],
Mann, R.[Richard],
Vrscay, E.R.[Edward R.],
A Diffusion-Based Two-Dimensional Empirical Mode Decomposition (EMD)
Algorithm for Image Analysis,
ICIAR18(295-305).
Springer DOI
1807
BibRef
Channoufi, I.[Ines],
Bourouis, S.[Sami],
Bouguila, N.[Nizar],
Hamrouni, K.[Kamel],
A Flexible Statistical Model for Image Denoising,
ICIAR18(30-38).
Springer DOI
1807
BibRef
Bergmann, R.,
MVIRT, a toolbox for manifold-valued image restoration,
ICIP17(201-205)
IEEE DOI
1803
Computational modeling, Image restoration, Manifolds, Minimization,
TV, Task analysis, Douglas-Rachford splitting, Riemannian manifold,
variational models
BibRef
Chen, P.[Peng],
Wu, S.Q.[Shi-Qian],
Fang, H.P.[Hong-Ping],
Chen, B.[Bin],
Wang, W.[Wei],
Gaussian Noise Detection and Adaptive Non-local Means Filter,
PSIVT17(396-405).
Springer DOI
1802
BibRef
Zhang, J.,
Pan, J.,
Lai, W.S.,
Lau, R.W.H.,
Yang, M.H.,
Learning Fully Convolutional Networks for Iterative Non-blind
Deconvolution,
CVPR17(6969-6977)
IEEE DOI
1711
Convolution, Deconvolution, Image denoising, Image restoration,
Kernel, Noise reduction, Training
BibRef
Foare, M.,
Lachaud, J.O.,
Talbot, H.,
Image restoration and segmentation using the Ambrosio-Tortorelli
functional and Discrete Calculus,
ICPR16(1418-1423)
IEEE DOI
1705
Calculus, Convergence, Image restoration, Image segmentation,
Minimization, Noise reduction, Standards, Mumford-Shah functional,
denoising, inverse problems, optimisation, segmentation,
simplification, variational, formulation
BibRef
Li, J.,
Tu, Q.A.[Qi-Ang],
Yan, Z.Y.[Zi-Ye],
Refining pre-image via error compensation for KPCA-based pattern
de-noising,
ICPR16(414-419)
IEEE DOI
1705
Error compensation, Image denoising, Kernel, Noise reduction,
Principal component analysis, Systematics, Training,
error compensation, kernel principal component analysis (KPCA),
pre-image, systematic, error
BibRef
Boudjenouia, F.,
Abed-Meraim, K.,
Chetouani, A.,
Jennane, R.,
On the use of image quality measures for image restoration,
IPTA16(1-6)
IEEE DOI
1703
gradient methods
BibRef
Li, J.W.[Jian-Wei],
Chen, X.W.[Xiao-Wu],
Zou, D.Q.[Dong-Qing],
Gao, B.[Bo],
Teng, W.[Wei],
Conformal and Low-Rank Sparse Representation for Image Restoration,
ICCV15(235-243)
IEEE DOI
1602
Dictionaries
BibRef
Guven, H.E.[H. Emre],
Gungor, A.[Alper],
Cetin, M.[Mujdat],
An Augmented Lagrangian Method for image reconstruction with multiple
features,
ICIP15(4175-4179)
IEEE DOI
1512
Alternating Direction Method of Multipliers
BibRef
Shah, T.,
Shikkenawis, G.[Gitam],
Mitra, S.K.[Suman K.],
Epitome based transform domain Image Denoising,
ICAPR15(1-6)
IEEE DOI
1511
image denoising
BibRef
Aouinti, F.,
Nasri, M.,
Moussaoui, M.,
Bouali, B.,
Image restoration by applying the genetic approach to the iterative
Wiener filter,
ISCV15(1-5)
IEEE DOI
1506
Wiener filters
BibRef
Kandaswamy, C.[Chetak],
Silva, L.M.[Luís M.],
Cardoso, J.S.[Jaime S.],
Source-Target-Source Classification Using Stacked Denoising
Autoencoders,
IbPRIA15(39-47).
Springer DOI
1506
BibRef
Liu, K.[Ke],
Xu, M.[Ming],
Yu, Z.Y.[Ze-Yun],
Feature-Preserving Image Restoration from Adaptive Triangular Meshes,
Restoration14(II: 31-46).
Springer DOI
1504
BibRef
Jiang, F.[Feng],
Zhang, S.P.[Sheng-Ping],
Zhao, D.B.[De-Bin],
Kung, S.Y.,
Image Restoration via Multi-prior Collaboration,
ACCV14(III: 191-204).
Springer DOI
1504
BibRef
Zang, X.H.[Xiu-Huan],
Shi, Y.H.[Yun-Hui],
Wang, J.[Jin],
Ding, W.P.[Wen-Peng],
Yin, B.C.[Bao-Cai],
Optimizing collaborative sparse dictionary for compressive light
field photography,
VCIP16(1-4)
IEEE DOI
1701
Algorithm design and analysis
BibRef
Wang, J.[Jin],
Cai, J.F.[Jian-Feng],
Shi, Y.H.[Yun-Hui],
Yin, B.C.[Bao-Cai],
Incoherent dictionary learning for sparse representation based image
denoising,
ICIP14(4582-4586)
IEEE DOI
1502
Coherence
BibRef
McCrackin, L.[Laura],
Shirani, S.[Shahram],
Strategic image denoising using a support vector machine with seam
energy and saliency features,
ICIP14(2684-2688)
IEEE DOI
1502
Image color analysis
BibRef
Zhang, X.[Xing],
Lyu, S.W.[Si-Wei],
Using Projection Kurtosis Concentration of Natural Images for Blind
Noise Covariance Matrix Estimation,
CVPR14(2870-2876)
IEEE DOI
1409
natural image statistics
BibRef
Anantrasirichai, N.,
Burn, J.,
Bull, D.R.[David R.],
Projective image restoration using sparsity regularization,
ICIP13(1080-1084)
IEEE DOI
1402
Accuracy
BibRef
Muramatsu, S.[Shogo],
Aizawa, N.[Natsuki],
Image restoration with 2-D non-separable oversampled lapped
transforms,
ICIP13(1051-1055)
IEEE DOI
1402
Dictionaries
BibRef
Feng, J.Z.[Jian-Zhou],
Song, L.[Li],
Huo, X.M.[Xiao-Ming],
Yang, X.K.[Xiao-Kang],
Zhang, W.J.[Wen-Jun],
Image restoration via efficient Gaussian mixture model learning,
ICIP13(1056-1060)
IEEE DOI
1402
Dictionaries
BibRef
Lee, C.[Chul],
Kim, C.S.[Chang-Su],
Lee, S.U.[Sang-Uk],
Probabilistic depth-guided multi-view image denoising,
ICIP13(905-908)
IEEE DOI
1402
Estimation
BibRef
Wang, H.Z.[Han-Zi],
Cai, J.L.[Jin-Long],
Tang, J.Y.[Jian-Yu],
AMSAC: An adaptive robust estimator for model fitting,
ICIP13(305-309)
IEEE DOI
1402
Adaptation models
robust scale estimator called AIKOSE.
Scale of noise.
BibRef
Mobasheri, M.R.,
Zendehbad, S.A.,
Diagnosis and Repair of Random Noise in The Sensor's Chris-Proba,
SMPR13(463-468).
HTML Version.
1311
CHRIS sensor on the PROBA-1 satellite.
BibRef
Matakos, A.[Antonios],
Ramani, S.[Sathish],
Fessler, J.A.[Jeffrey A.],
Image restoration using non-circulant shift-invariant system models,
ICIP12(3061-3064).
IEEE DOI
1302
BibRef
Pan, J.F.[Jing-Feng],
Cao, T.Y.[Tie-Yong],
Zhang, X.W.[Xiong-Wei],
Huang, H.[Hui],
A quantum-inspired noise reduction method based on noise feature
codebook,
CVRS12(158-163).
IEEE DOI
1302
BibRef
Sa, P.K.[Pankaj Kumar],
Majhi, B.[Banshidhar],
Adaptive edge preserving regularized image restoration,
ICIIP11(1-5).
IEEE DOI
1112
BibRef
Nguyen, T.A.[Tuan-Anh],
Hong, M.C.[Min-Cheol],
Filtering-Based Noise Estimation for Denoising the Image Degraded by
Gaussian Noise,
PSIVT11(II: 157-167).
Springer DOI
1111
BibRef
Lobry, S.,
Denis, L.,
Tupin, F.,
Sparse-smooth decomposition models for multi-temporal SAR images,
MultiTemp15(1-4)
IEEE DOI
1511
image denoising
BibRef
Denis, L.,
Tupin, F.,
Rondeau, X.,
Exact discrete minimization for TV+L0 image decomposition models,
ICIP10(2525-2528).
IEEE DOI
1009
Noise. Decompose and denoise each separately.
BibRef
Zhao, S.P.[Shuang-Ping],
A combined image denoising method,
IASP10(254-256).
IEEE DOI
1004
Wiener filter in wavelet and spatial domains.
BibRef
Chountasis, S.,
Pappas, D.,
Katsikis, V.N.,
Image Restoration Via Fast Computing of the Moore-Penrose Inverse
Matrix,
WSSIP09(1-4).
IEEE DOI
0906
BibRef
Huang, Y.L.[Yong-Lin],
Ye, Y.T.[Yu-Tang],
Qiao, N.S.[Nao-Sheng],
An Improved TV Model for Image Restoration,
CISP09(1-5).
IEEE DOI
0910
BibRef
Jiang, X.N.[Xue-Na],
Liu, Y.Y.[Yang-Yang],
Wang, S.J.[Shou-Jue],
A Novel Geometric Algorithm for Blind Image Restoration Based on
High-Dimensional Space,
CISP09(1-5).
IEEE DOI
0910
BibRef
Fang, S.L.[Sheng-Liang],
Zhang, X.W.[Xi-Wang],
A New Algorithm for Revising Noise Covariance Matrix Disturbance in the
Presence of Coherent Sources,
CISP09(1-6).
IEEE DOI
0910
BibRef
An, Z.J.[Zhi-Juan],
Fast subspace estimation with Rayleigh-Ritz approximation and
multi-stage Wiener filter,
IASP09(381-385).
IEEE DOI
0904
BibRef
Gao, Y.[Yan],
Chan, K.L.[Kap Luk],
Yau, W.Y.[Wei-Yun],
Manifold denoising with Gaussian Process Latent Variable Models,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Tanaka, M.[Masayuki],
Okutomi, M.[Masatoshi],
Locally adaptive learning for translation-variant MRF image priors,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Christiansen, O.,
Time-Frequency Analysis and its Applications in Denoising,
Ph.D.Thesis, 2002, Department of Informatics, University of Bergen, Norway.
BibRef
0200
Miao, L.[Lidan],
Qi, H.R.[Hai-Rong],
A Blind Source Separation Perspective on Image Restoration,
CVPR07(1-7).
IEEE DOI
0706
BibRef
Loog, M.[Marco],
Generic Blind Source Separation Using Second-Order Local Statistics,
SSPR06(844-852).
Springer DOI
0608
BibRef
Gerace, I.,
Solving the Sparse Data Image Restoration Problem by Local Minimization,
ICIP05(III: 321-324).
IEEE DOI
0512
BibRef
Wu, X.J.[Xian-Jin],
Wang, R.S.[Run-Sheng],
Wang, C.[Cheng],
Regularized image restoration based on adaptively selecting parameter
and operator,
ICPR04(III: 662-665).
IEEE DOI
0409
BibRef
Gutierrez, J.,
Malo, J.,
Ferri, F.J.,
Perceptual regularization functionals for natural image restoration,
ICIP03(II: 989-992).
IEEE DOI
0312
BibRef
Ben Hamza, A.,
Krim, H.[Hamid],
Towards a Unified View of Estimation: Variational vs Statistical,
ICIP01(II: 577-580).
IEEE DOI
0108
BibRef
Devcic, Z.,
Loncaric, S.,
Blind Restoration of Space-invariant Image Degradations in the Singular
Value Decomposition Domain,
ICIP01(II: 49-52).
IEEE DOI
0108
BibRef
Rao, K.D.[K. Deergha],
Swamy, M.N.S.,
Plotkin, E.I.,
Image Restoration Using an Hybrid Approach Based on DWT and SMKF,
ICIP01(I: 249-252).
IEEE DOI
0108
BibRef
Fan, L.X.[Li-Xin],
Sung, K.K.[Kah Kay],
Towards Statistical Image Restoration:
Perceptual Grouping as Regularizing Operators,
PercOrg01(xx-yy).
0106
BibRef
Ishwar, P.[Prakash],
Moulin, P.[Pierre],
Shift Invariant Restoration: An Overcomplete Maxent MAP Framework,
ICIP00(Vol III: 270-272).
IEEE DOI
0008
BibRef
Earlier:
Ishwar, P.[Prakash],
Moulin, P.[Pierre],
Multiple-Domain Image Modeling and Restoration,
ICIP99(I:362-366).
IEEE DOI
BibRef
Haseyama, M.,
Takezawa, M.,
Kitajima, H.,
An Image Restoration Method Using IFS,
ICIP00(Vol III: 774-777).
IEEE DOI
0008
BibRef
Fridrich, J.[Jiri],
Goljan, M.[Miroslav],
Images with Self-Correcting Capabilities,
ICIP99(III:792-796).
IEEE DOI
BibRef
9900
Inoue, J.I.,
Image restoration using quantum fluctuation,
CIAP99(130-135).
IEEE DOI
9909
BibRef
Murli, A.,
d'Amore, L.,
de Simone, V.,
The Wiener filter and regularization methods for image restoration
problems,
CIAP99(394-399).
IEEE DOI
9909
BibRef
Herzog, A.[Andreas],
Krell, G.[Gerald],
Michaelis, B.[Bernd],
Wang, J.Z.[Ji-Zhong],
Zuschratter, W.[Werner],
Braun, K.[Katharina],
Three-dimensional quasi-binary image restoration for confocal
microscopy and its application to dendritic trees,
CAIP97(114-121).
Springer DOI
9709
BibRef
Barakat, V.,
Guilpart, B.,
Goutte, R., and
Prost, R.,
Model-Based Tikhonov-Miller Image Restoration,
ICIP97(I: 310-313).
IEEE DOI
BibRef
9700
Suthaharan, S., and
Zhang, Z.W.[Zhong-Wei],
SNR Optimization Using Genetic Algorithm,
ICIP97(I: 295-297).
IEEE DOI
9710
BibRef
Chen, Y.W.[Yen-Wei],
Nakao, Z.,
Fang, X.[Xue],
Tamura, S.,
A Parallel Genetic Algorithm for Image Restoration and Its Performance,
ICPR96(IV: 694-698).
IEEE DOI
9608
(Univ. of the Ryukyus, J)
BibRef
Lasakul, A.,
Atsuta, K.,
Kondo, S.,
A Theory of Image Restoration for Linear Spatial Degradation
Using Multiresolution Analysis,
ICPR96(II: 422-426).
IEEE DOI
9608
(Tokai Univ., J)
BibRef
Ibrahim, H.M.[Hosny M.],
Gharieb, R.R.,
Two-dimensional cumulant-based adaptive enhancer,
ICIP96(I: 789-792).
IEEE DOI
BibRef
9600
Hirani, A.N.[Anil N.],
Totsuka, T.[Takashi],
Dual domain interactive image restoration: basic algorithm,
ICIP96(I: 797-800).
IEEE DOI
BibRef
9600
Cohen, H.A.[Harvey A.],
Image restoration via N-nearest neighbour classification,
ICIP96(I: 1005-1008).
IEEE DOI
BibRef
9600
Koivunen, V.[Visa],
Kassam, S.A.,
Covariance estimation in multivariate OS-filtering,
ICIP96(I: 981-984).
IEEE DOI
BibRef
9600
Lau, D.L.[Daniel L.],
Arce, G.R.[Gonzalo R.],
Gallagher, Jr., N.C.[Neal C.],
Robust Image Wavelet Shrinkage for Denoising,
ICIP96(I: 371-374).
IEEE DOI
BibRef
9600
Schonfeld, D.,
Qiao, Y.[Yi],
A new stochastic projection-based image recovery method,
ICIP95(I: 466-469).
IEEE DOI
9510
BibRef
Grigorian, A.[Artiom],
New models of image restoration,
CAIP95(509-514).
Springer DOI
9509
BibRef
Maitre, H.,
A General Scheme for Signal Restoration with Application to
Picture Processing,
PRIP81(430-432).
BibRef
8100
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Restoration -- General, Survey, Evaluations .