5.3 Image Restoration, Image Denoising

Linfoot, E.H.,
Contrast Transmission Functions at Low Spatial Frequencies,
Optica Acta(6), No. 4, October 1959, pp. 387-404. BibRef 5910

Barnes, C.W.,
Object Restoration in a Diffraction Limited Imaging System,
JOSA(56), 1966, pp. 575-576. BibRef 6600

Müller, P.F., Reynolds, G.O.,
Image Restoration by Removal of Random-Media Degradations,
JOSA(57), No. 11, November 1967, pp. 1338-1345. BibRef 6711

Yu, F.T.S.,
Image Restoration, Uncertainty, and Information,
AppOpt(8), No. 1, January 1969, pp. 53. BibRef 6901

Boulter, J.F.,
Interactive Digital Image Restoration and Enhancement,
CGIP(11), No. 4, December 1979, pp. 301-312.
Elsevier DOI BibRef 7912

Frieden, B.R.,
Statistical Models for the Image Restoration Problem,
CGIP(12), No. 1, January 1980, pp. 40-59.
Elsevier DOI BibRef 8001

Jain, A.K., and Angel, E.,
Image Restoration, Modelling, and Reduction of Dimensionality,
TC(23), No. 5, May 1974, pp. 470-476. BibRef 7405

Sondhi, M.M.,
Image Restoration: The Removal of Spatially Invariant Degradations,
PIEEE(60), No. 7, July 1972, pp. 842-853. BibRef 7207

Anderson, C.L., and Netravali, A.N.,
Image Restoration Based on a Subjective Criterion,
SMC(6), December 1976, pp. 845-853. BibRef 7612

Ostrem, J.S., and Falconer, D.G.,
A Differential Operator Technique for Restoring Degraded Signals and Images,
PAMI(3), No. 3, May 1981, pp. 278-284. BibRef 8105

Stuller, J.A., McGillem, C.D.,
Correction of a Statement in Digital Picture Processing,
CVGIP(22), No. 3, June 1983, pp. 409.
Elsevier DOI BibRef 8306

Meinel, E.S.,
Origins of linear and nonlinear recursive restoration algorithms,
JOSA-A(3), 1986, pp. 787-799. BibRef 8600

Aravena, J.L., and Porter, W.A.,
One-Dimensional Scan Selection for Two-Dimensional Signal Restoration,
PAMI(8), No. 2, March 1986, pp. 282-284. BibRef 8603

Murray, D.W., Kashko, A., Buxton, H.,
A Parallel Approach to the Picture Restoration Algorithm of Geman and Geman on an SIMD Machine,
IVC(4), No. 3, August 1986, pp. 133-142.
Elsevier DOI
See also Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. BibRef 8608

Cai, Z.G.[Zu-Guang],
Restoration of Binary Images Using Contour Direction Chain Codes Description,
CVGIP(41), No. 1, January 1988, pp. 101-106.
Elsevier DOI BibRef 8801

Bumbaca, F.[Federico], Smith, K.C.[Kennety C.],
A Practical Approach to Image Restoration for Computer Vision,
CVGIP(42), No. 2, May 1988, pp. 220-233.
Elsevier DOI BibRef 8805

Gidas, B.,
A Renormalization Group Approach to Image Processing Problems,
PAMI(11), No. 2, February 1989, pp. 164-180.
IEEE DOI BibRef 8902

Wang, Y.M.[Yuan Mei], and Lu, W.X.[Wei Xue],
Multicriterion Image Reconstruction and Implementation,
CVGIP(46), No. 1, April 1989, pp. 131-135.
Elsevier DOI BibRef 8904

Cocozza-Thivent, C.[Christiane], Bekkhoucha, A.[Abdelkrim],
Estimation in Pickard Random Fields and Application to Image Processing,
PR(26), No. 5, May 1993, pp. 747-761.
Elsevier DOI 0401
BibRef

Nanda, P.K., Kumar, K. .S.I.[K. Sun-Il], Ghokale, S., Desai, U.B.,
A multiresolution approach to color image restoration and parameter estimation using homotopy continuation method,
ICIP95(II: 45-48).
IEEE DOI 9510
BibRef

Terebizh, V.Y.,
Occamian Approach in the Image Restoration and Other Inverse Problems,
IJIST(6), No. 4, Winter 1995, pp. 358-369. BibRef 9500

Azencott, R., Chalmond, B., Wang, J.P.,
Transfer-Function Estimation, Film Fusion and Image Restoration,
GMIP(58), No. 1, January 1996, pp. 65-74. BibRef 9601

Guan, L.,
An Optimal Neuron Evolution Algorithm for Constrained Quadratic-Programming in Image Restoration,
SMC-A(26), No. 4, July 1996, pp. 513-518.
IEEE Top Reference. 9607
BibRef

Sundaram, R., Ersoy, O.K.,
Partitioning of Hopfield Networks and Its Application to Image Restoration,
OptEng(35), No. 8, August 1996, pp. 2276-2285. 9609
BibRef

Snyder, D.L.[Donald L.],
Image Recovery from Correlations,
JOSA-A(9), No. 8, August 1992, pp. 1266-1272. 9702
BibRef

Snyder, D.L.[Donald L.], Hammoud, A., White, R.,
Image Recovery from Data Acquired with a Charge-Coupled Device Camera,
JOSA-A(10), No. 5, May 1993, pp. 1014-1023. BibRef 9305

Leahy, R.M., Goutis, C.E.,
An Optimal Technique for Constraint-Based Image Restoration and Reconstruction,
ASSP(34), 1986, pp. 1629-1642. BibRef 8600

Koufopavlou, O.G., Goutis, C.E.,
Image reconstruction on a special purpose array processor,
IVC(10), No. 7, September 1992, pp. 479-484.
Elsevier DOI 0401
BibRef

Sanz, J.L.C., Huang, T.S.,
Discrete and Continuous Band-Limited Signal Extrapolation,
ASSP(31), 1983, pp. 1276-1285. BibRef 8300

Hebert, T.J., Lu, K.M.[Ke-Ming],
Expectation-maximization algorithms, null spaces, and MAP image restoration,
IP(4), No. 8, August 1995, pp. 1084-1095.
IEEE DOI 0402
BibRef

Sayrol, E., Nikias, C.L., Gasull, A.,
Image restoration using the W-slice method,
IP(4), No. 8, August 1995, pp. 1174-1181.
IEEE DOI 0402
BibRef

Jones, P.F., Aitken, G.J.M.,
Restoration of Images of Partially Obscured Objects,
JOSA-A(14), No. 5, May 1997, pp. 1015-1023. 9705
BibRef

Verveer, P.J., Jovin, T.M.,
Image-Restoration Based on Goods Roughness Penalty with Application to Fluorescence Microscopy,
JOSA-A(15), No. 5, May 1998, pp. 1077-1083. 9805
BibRef

Morita, T., Tanaka, K.,
Cluster ZTP in the Recovery of an Image,
PRL(18), No. 14, December 1997, pp. 1479-1493. 9806
BibRef

Mollah, M.M., Yahagi, T.,
Estimation of 2-D Noncausal AR Parameters for Image-Restoration Using Genetic Algorithm,
IEICE(E81-A), No. 8, August 1998, pp. 1676-1682. 9809
BibRef

Nikolova, M.[Mila],
Markovian Reconstruction Using a GNC Approach,
IP(8), No. 9, September 1999, pp. 1204-1220.
IEEE DOI BibRef 9909
Earlier:
Regularisation Functions and Estimators,
ICIP96(II: 457-460).
IEEE DOI BibRef

Nikolova, M.,
Image restoration by minimizing objective functions with non-smooth data-fidelity terms,
LevelSet01(xx-yy). 0106
BibRef
And:
Smoothing of Outliers in Image Restoration by Minimizing Regularized Objective Functions with Nonsmooth Data-fidelity Terms,
ICIP01(I: 233-236).
IEEE DOI 0108
BibRef

Nikolova, M.[Mila],
Weakly Constrained Minimization: Application to the Estimation of Images and Signals Involving Constant Regions,
JMIV(21), No. 2, September 2004, pp. 155-175.
DOI Link 0409
BibRef

Chan, T.F., Esedoglu, S., Nikolova, M.[Mila],
Finding the Global Minimum for Binary Image Restoration,
ICIP05(I: 121-124).
IEEE DOI 0512
BibRef

Nikolova, M.[Mila],
Counter-Examples for Bayesian MAP Restoration,
SSVM07(140-152).
Springer DOI 0705
BibRef

Nikolova, M.[Mila],
Semi-explicit Solution and Fast Minimization Scheme for an Energy with L1-Fitting and Tikhonov-Like Regularization,
JMIV(34), No. 1, May 2009, pp. xx-yy.
Springer DOI 0905

See also Regularization of Ill-Posed Problems, The. BibRef

Nikolova, M.[Mila],
Description of the Minimizers of Least Squares Regularized with L_0-norm. Uniqueness of the Global Minimizer,
SIIMS(6), No. 2, 2013, pp. 904-937.
DOI Link 1307
BibRef
Earlier:
Should We Search for a Global Minimizer of Least Squares Regularized with an L_0 Penalty to Get the Exact Solution of an under Determined Linear System?,
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],
Either Fit to Data Entries or Locally to Prior: The Minimizers of Objectives with Nonsmooth Nonconvex Data Fidelity and Regularization,
SSVM11(110-121).
Springer DOI 1201
BibRef

Durand, S., Nikolova, M.,
Stability of image restoration by minimizing regularized objective functions,
LevelSet01(xx-yy). 0106
BibRef

Nikolova, M.[Mila], Ng, M.K.[Michael K.], Zhang, S.Q.[Shu-Qin], Ching, W.K.[Wai-Ki],
Efficient Reconstruction Of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization,
SIIMS(1), No. 1, 2008, pp. 2-25. image restoration; regularization; nonsmooth and nonconvex optimization; continuation; interior point method; unsupervised segmentation; inverse problems; deblurring; constrained optimization; graduated nonconvexity (GNC)
DOI Link BibRef 0800

Nikolova, M.[Mila], Ng, M.K.[Michael K.], Tam, C.P.,
Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction,
IP(19), No. 12, December 2010, pp. 3073-3088.
IEEE DOI 1011
BibRef

Voss, K.[Klaus], Suesse, H.[Herbert], Ortmann, W.[Wolfgang], Baumbach, T.[Torsten],
Shift Detection by Restoration,
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: Demonstrated by signal based point pattern matching,
CIAP99(310-315).
IEEE DOI 9909
BibRef

Hunt, B.R.[Bobby R.],
Prospects for image restoration,
Modern Physics C(5), 1994, pp. 151-178. BibRef 9400

Miller, C.[Casey], Hunt, B.R.[Bobby R.], Marcellin, M.W.[Michael W.], Neifeld, M.A.[Mark A.],
Image restoration with the Viterbi algorithm,
JOSA-A(17), No. 2, February 2000, pp. 265-275. 0002
BibRef

Miller, C., Hunt, B.R., Neifeld, M.A., and Marcellin, M.W.,
Binary Image Reconstruction via 2-D Viterbi Search,
ICIP97(I: 181-184).
IEEE DOI BibRef 9700

Li, S.Z.[Stan Z.],
Toward global solution to MAP image restoration and segmentation: Using Common Structure of Local Minima,
PR(33), No. 4, April 2000, pp. 715-723.
Elsevier DOI 0002
BibRef

van Kempen, G.M.P.[Geert M. P.], van Vliet, L.J.[Lucas J.],
Background estimation in nonlinear image restoration,
JOSA-A(17), No. 3, March 2000, pp. 425-433. 0003
BibRef

Choy, S.O., Chan, Y.H., Siu, W.C.,
Image restoration by regularisation in uncorrelated transform domain,
VISP(147), No. 6, December 2000, pp. 587-594. 0101
BibRef

Meyer, Y.,
Oscillating Patterns in Image Processing and Nonlinear Evolution Equations,
AMS2002. University Lecture Series, Vol. 22. Images decompose into geometry and texture. BibRef 0200

Meyer, Y.,
Oscillating Patterns in Some Nonlinear Evolution Equations,
SpringerLNM 1871, 2006, pp. 101-187.
Springer DOI BibRef 0600

Nagorni, M.[Matthias], Hell, S.W.[Stefan W.],
Coherent use of opposing lenses for axial resolution increase. II. Power and limitation of nonlinear image restoration,
JOSA-A(18), No. 1, January 2001, pp. 49-54. 0101
BibRef

Markham, J.[Joanne], Conchello, J.A.[Jose-Angel],
Fast maximum-likelihood image-restoration algorithms for three-dimensional fluorescence microscopy,
JOSA-A(18), No. 5, May 2001, pp. 1062-1071. 0105
BibRef

Piccolomini, E.L.[E. Loli], Zama, F.,
Parallel Image Restoration with Domain Decomposition,
RealTimeImg(7), No. 1, February 2001, pp. 47-57.
DOI Link 0106
BibRef

Idier, J.,
Convex half-quadratic criteria and interacting auxiliary variables for image restoration,
IP(10), No. 7, July 2001, pp. 1001-1009.
IEEE DOI 0108
BibRef

Chouzenoux, E., Idier, J., Moussaoui, S.,
A Majorize-Minimize Strategy for Subspace Optimization Applied to Image Restoration,
IP(20), No. 6, June 2011, pp. 1517-1528.
IEEE DOI 1106
accelerated subspace optimization. BibRef

Unal, G.B., Cetin, A.E.,
Restoration of error-diffused images using projection onto convex sets,
IP(10), No. 12, December 2001, pp. 1836-1841.
IEEE DOI 0201
BibRef

Sotthivirat, S., Fessler, J.A.,
Image Recovery Using Partitioned-Separable Paraboloidal Surrogate Coordinate Ascent Algorithms,
IP(11), No. 3, March 2002, pp. 306-317.
IEEE DOI 0203
BibRef
Earlier:
Partitioned Separable Paraboloidal Surrogate Coordinate Ascent Algorithm for Image Restoration,
ICIP00(Vol I: 109-112).
IEEE DOI 0008
BibRef

Zhang, D.D.[David D.], Wang, Z.[Zhou],
Image information restoration based on long-range correlation,
CirSysVideo(12), No. 5, May 2002, pp. 331-341.
IEEE Top Reference. 0206
BibRef

Sequeira, R.E., Gubner, J.A., Saleh, B.E.A.,
Image detection under low-level illumination,
IP(2), No. 1, January 1993, pp. 18-26.
IEEE DOI 0402
BibRef

Kim, J.B.[Jong Bae], Kim, H.J.[Hang Joon],
GA-Based Image Restoration by Isophote Constraint Optimization,
JASP(2003), No. 3, March 2003, pp. 238.
WWW Link. 0304
BibRef

Pham, D.S.[Due Son], Zoubir, A.M.,
A sequential algorithm for robust parameter estimation,
SPLetters(12), No. 1, January 2005, pp. 21-24.
IEEE Abstract. 0501
BibRef

Liao, Y., Lin, X.,
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 Model,
IP(14), No. 11, November 2005, pp. 1902-1917.
IEEE DOI 0510
BibRef

Memon, N., Pal, A.,
Automated Reassembly of File Fragmented Images Using Greedy Algorithms,
IP(15), No. 2, February 2006, pp. 385-393.
IEEE DOI 0602
Pose as a graph problem, find the best ordering. 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 in space,
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
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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
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Chaudhry, A.[Asmatullah], Khan, A.[Asifullah], Ali, A.[Asad], Mirza, A.M.[Anwar M.],
A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming,
IJIST(17), No. 4, 2007, pp. 224-231.
DOI Link 0712
BibRef

Hussain, A.[Ayyaz], Jaffar, M.A.[M. Arfan], Siddiqui, A.B.[Abdul Basit], 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

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

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. BibRef

Wang, Z.[Zhe], Luo, S.W.[Si-Wei], Wang, L.[Liang],
A Fast Algorithm for Learning the Overcomplete Image Prior,
IEICE(E93-D), No. 2, February 2010, pp. 403-406.
WWW Link. 1002
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Wang, Z.[Zhe], Huang, Y.P.[Ya-Ping], Luo, S.W.[Si-Wei], Wang, L.[Liang],
Complex Cell Descriptor Learning for Robust Object Recognition,
IEICE(E94-D), No. 7, July 2011, pp. 1502-1505.
WWW Link. 1107
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Papa, J.P.[Joao P.], 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

de Souza, G.B.[Gustavo Botelho], da Silva Santos, D.F.[Daniel Felipe], Gonsalves Pires, R.[Rafael], Marana, A.N.[Aparecido Nilceu], Papa, J.P.[João Paulo],
A Restricted Boltzmann Machine-Based Approach for Robust Dimensionality Reduction,
WVC17(138-143)
IEEE DOI 1804
Boltzmann machines, face recognition, feature extraction, learning (artificial intelligence), optimisation, Restricted Boltzmann Machines BibRef

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

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 camera and image denoising,
JOSA-A(27), No. 11, November 2010, pp. 2381-2386.
DOI Link 1011
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 Restoration via the Balanced Approach,
SIIMS(4), No. 2, 2011, pp. 573-596.
WWW Link. 1110
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Zuo, W.M.[Wang-Meng], Lin, Z.C.[Zhou-Chen],
A Generalized Accelerated Proximal Gradient Approach for Total-Variation-Based Image Restoration,
IP(20), No. 10, October 2011, pp. 2748-2759.
IEEE DOI 1110
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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

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

Wu, W.H.[Wei-Hao], Huang, T.Z.[Ting-Zhu], Zhang, H.[Hao], Wang, J.L.[Jian-Li], Zhao, X.L.[Xi-Le],
Untrained Low-Rank Neural Network Prior for Multi-Dimensional Image Recovery,
SPLetters(30), 2023, pp. 1647-1651.
IEEE DOI 2311
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], Sciacchitano, F.[Federica], Sgallari, F.[Fiorella],
Whiteness Constraints in a Unified Variational Framework for Image Restoration,
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

Wang, Z., Zhu, J., Yan, F., Xie, M.,
Fidelity-Beltrami-Sparsity Model for Inverse Problems in Multichannel Image Processing,
SIIMS(6), No. 4, 2013, pp. 2685-2713.
DOI Link 1402
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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 BibRef

Kim, K., Lee, J.,
Nonlinear Dynamic Projection for Noise Reduction of Dispersed Manifolds,
PAMI(36), No. 11, November 2014, pp. 2303-2309.
IEEE DOI 1410
Algorithm design and analysis BibRef

Yousefian, N., Hansen, J.H.L., Loizou, P.C.,
A Hybrid Coherence Model for Noise Reduction in Reverberant Environments,
SPLetters(22), No. 3, March 2015, pp. 279-282.
IEEE DOI 1410
Coherence BibRef

Imre, E.[Evren], Hilton, A.[Adrian],
Covariance estimation for minimal geometry solvers via scaled unscented transformation,
CVIU(130), No. 1, 2015, pp. 18-34.
Elsevier DOI 1411
Covariance estimation BibRef

Zhao, S., Shmaliy, Y.S., Liu, F.,
Fast Computation of Discrete Optimal FIR Estimates in White Gaussian Noise,
SPLetters(22), No. 6, June 2015, pp. 718-722.
IEEE DOI 1411
Iterative algorithm BibRef

Sahoo, S.K., Makur, A.,
Enhancing Image Denoising by Controlling Noise Incursion in Learned Dictionaries,
SPLetters(22), No. 8, August 2015, pp. 1123-1126.
IEEE DOI 1502
image denoising BibRef

McGaffin, M.G., Fessler, J.A.[Jeffrey A.],
Edge-Preserving Image Denoising via Group Coordinate Descent on the GPU,
IP(24), No. 4, April 2015, pp. 1273-1281.
IEEE DOI 1503
graphics processing units BibRef

Kim, D.[Donghwan], Fessler, J.A.[Jeffrey A.],
An optimized first-order method for image restoration,
ICIP15(3675-3679)
IEEE DOI 1512
First-order methods BibRef

Yue, H.J.[Huan-Jing], Sun, X.Y.[Xiao-Yan], Yang, J.Y.[Jing-Yu], Wu, F.[Feng],
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 BibRef

Jain, P.[Paras], Tyagi, V.[Vipin],
An adaptive edge-preserving image denoising technique using tetrolet transforms,
VC(31), No. 5, May 2015, pp. 657-674.
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Özkan, K., Seke, E.,
Image denoising using common vector approach,
IET-IPR(9), No. 8, 2015, pp. 709-715.
DOI Link 1506
estimation theory 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
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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

Shikkenawis, G.[Gitam], Mitra, S.K.[Suman K.],
2D Orthogonal Locality Preserving Projection for Image Denoising,
IP(25), No. 1, January 2016, pp. 262-273.
IEEE DOI 1601
Dictionaries BibRef

Shikkenawis, G.[Gitam], Mitra, S.K.[Suman K.],
Image denoising using 2D orthogonal locality preserving discriminant projection,
IET-IPR(14), No. 3, 28 February 2020, pp. 552-560.
DOI Link 2002
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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

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
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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 BibRef

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
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Hua, X.[Xia], Li, Z.Z.[Ze-Zheng], Hong, H.Y.[Han-Yu],
An Efficient Multiscale Spatial Rearrangement MLP Architecture for Image Restoration,
IP(33), 2024, pp. 423-438.
IEEE DOI 2401
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
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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

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
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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

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
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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

Pierazzo, N.[Nicola], Morel, J.M.[Jean-Michel], Facciolo, G.[Gabriele],
Multi-Scale DCT Denoising,
IPOL(7), 2017, pp. 288-308.
DOI Link 1712
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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
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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
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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
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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
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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
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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
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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
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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
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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

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
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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

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

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

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

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
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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

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

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

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

Shen, L.[Lili], Zhao, B.[Bo], Li, Q.X.[Qun-Xia], Zhang, C.H.[Chu-He], Sun, X.C.[Xi-Chun], 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

Mei, Y.Q.[Yi-Qun], Fan, Y.C.[Yu-Chen], Zhang, Y.L.[Yu-Lun], Yu, J.H.[Jia-Hui], Zhou, Y.Q.[Yu-Qian], Liu, D.[Ding], Fu, Y.[Yun], Huang, T.S.[Thomas S.], Shi, H.[Humphrey],
Pyramid Attention Network for Image Restoration,
IJCV(131), No. 12, December 2023, pp. 3207-3225.
Springer DOI 2311
BibRef

Cui, Y.N.[Yu-Ning], Ren, W.Q.[Wen-Qi], Cao, X.C.[Xiao-Chun], Knoll, A.[Alois],
Image Restoration via Frequency Selection,
PAMI(46), No. 2, February 2024, pp. 1093-1108.
IEEE DOI 2401
Variety of restoration tasks: single-image defocus deblurring, image dehazing, image motion deblurring, image desnowing, image deraining, and image denoising. BibRef

Yang, Z.Z.[Zi-Zheng], Huang, J.[Jie], Zhou, M.[Man], Zheng, N.[Naishan], Zhao, F.[Feng],
IRVR: A General Image Restoration Framework for Visual Recognition,
MultMed(26), 2024, pp. 7012-7026.
IEEE DOI 2405
Semantics, Image recognition, Image restoration, Task analysis, Visualization, Degradation, Calibration, Low-level vision, low for high BibRef

Zhu, H.Y.[Hang-Yan], Liu, S.H.[Shao-Hui], Liu, M.[Ming], Yan, Z.F.[Zi-Fei], Zuo, W.M.[Wang-Meng],
De2Net: Under-display camera image restoration with feature deconvolution and kernel decomposition,
CVIU(244), 2024, pp. 104028.
Elsevier DOI Code:
WWW Link. 2405
Under-display camera, Image restoration, Point spread function, Kernel prediction network BibRef

Wu, Z.M.[Zhong-Ming], Huang, C.Y.[Chao-Yan], Zeng, T.Y.[Tie-Yong],
Extrapolated Plug-and-Play Three-Operator Splitting Methods for Nonconvex Optimization with Applications to Image Restoration,
SIIMS(17), No. 2, 2024, pp. 1145-1181.
DOI Link 2407
BibRef

Wu, Z.J.[Zhi-Jian], Li, J.[Jun], Xu, C.[Chang], Huang, D.J.[Ding-Jiang], Hoi, S.C.H.[Steven C. H.],
RUN: Rethinking the UNet Architecture for Efficient Image Restoration,
MultMed(26), 2024, pp. 10381-10394.
IEEE DOI 2410
Image restoration, Convolution, Computer architecture, Task analysis, Computational modeling, Computational efficiency, UNet architecture BibRef

Tian, C.[Chunwei], Zheng, M.[Menghua], Lin, C.W.[Chia-Wen], Li, Z.W.[Zhi-Wu], Zhang, D.[David],
Heterogeneous Window Transformer for Image Denoising,
SMCS(54), No. 11, November 2024, pp. 6621-6632.
IEEE DOI Code:
WWW Link. 2410
Noise reduction, Image denoising, Transformers, Noise measurement, Data mining, Training, Tensors, Convolutional neural network (CNN), task decomposition BibRef

Cui, Y.N.[Yu-Ning], Ren, W.Q.[Wen-Qi], Cao, X.C.[Xiao-Chun], Knoll, A.[Alois],
Revitalizing Convolutional Network for Image Restoration,
PAMI(46), No. 12, December 2024, pp. 9423-9438.
IEEE DOI 2411
Image restoration, Transformers, Task analysis, Convolution, Computer architecture, Frequency modulation, representation learning BibRef

Zhang, K.[Kevin], Kulshrestha, S.[Sakshum], Metzler, C.A.[Christopher A.],
A Scalable Training Strategy for Blind Multi-Distribution Noise Removal,
IP(33), 2024, pp. 6216-6226.
IEEE DOI 2411
Noise, Training, Noise reduction, Speckle, Standards, Optimization, Polynomials, Noise level, Image reconstruction, Adaptation models, deep learning BibRef

Gao, H.[Hu], Yang, J.[Jing], Zhang, Y.[Ying], Wang, N.[Ning], Yang, J.F.[Jing-Fan], Dang, D.[Depeng],
Prompt-Based Ingredient-Oriented All-in-One Image Restoration,
CirSysVideo(34), No. 10, October 2024, pp. 9458-9471.
IEEE DOI Code:
WWW Link. 2411
Degradation, Image restoration, Task analysis, Transformers, Adaptation models, Decoding, Data models, Image restoration, prompt BibRef

Gao, H.[Hu], Ma, B.[Bowen], Zhang, Y.[Ying], Yang, J.F.[Jing-Fan], Yang, J.[Jing], Dang, D.[Depeng],
Frequency domain task-adaptive network for restoring images with combined degradations,
PR(158), 2025, pp. 111057.
Elsevier DOI Code:
WWW Link. 2411
Image restoration, Frequency domain-based gate, Task-adaptive, Combined degradations BibRef

Xu, J.Y.[Jing-Yi], Deng, X.[Xin], Zhang, C.X.[Chen-Xiao], Li, S.X.[Sheng-Xi], Xu, M.[Mai],
Laplacian Gradient Consistency Prior for Flash Guided Non-Flash Image Denoising,
IP(33), 2024, pp. 6380-6392.
IEEE DOI Code:
WWW Link. 2411
Image denoising, Laplace equations, Noise reduction, Noise, Image restoration, Gaussian distribution, Adaptation models, interpretable network BibRef

Xu, X.D.[Xu-Dong], Zhang, Z.H.[Zhi-Hua], Crabbe, M.J.C.[M. James C.],
Satellite Image Restoration via an Adaptive QWNNM Model,
RS(16), No. 22, 2024, pp. 4152.
DOI Link 2412
quaternion-based weighted nuclear norm minimization. BibRef

Cui, Y.N.[Yu-Ning], Ren, W.Q.[Wen-Qi], Knoll, A.[Alois],
Omni-Kernel Modulation for Universal Image Restoration,
CirSysVideo(34), No. 12, December 2024, pp. 12496-12509.
IEEE DOI 2501
Image restoration, Transformers, Kernel, Task analysis, Fast Fourier transforms, Degradation, Frequency modulation, all-in-one image restoration BibRef

Zhu, H.[Hong], Ng, M.K.[Michael K.],
An Inexact Majorized Proximal Alternating Direction Method of Multipliers for Diffusion Tensors,
SIIMS(17), No. 3, 2024, pp. 1795-1819.
DOI Link 2501
BibRef

Chen, J.R.[Jun-Ren], Liu, Z.Q.[Zhao-Qiang], Ding, M.[Meng], Ng, M.K.[Michael K.],
Uniform Recovery Guarantees for Quantized Corrupted Sensing Using Structured or Generative Priors,
SIIMS(17), No. 3, 2024, pp. 1909-1977.
DOI Link 2501
corrupted sensing then dithered quantizer. BibRef

Mao, J.F.[Jia-Feng], Wang, X.T.[Xue-Ting], Aizawa, K.[Kiyoharu],
The Lottery Ticket Hypothesis in Denoising: Towards Semantic-driven Initialization,
ECCV24(LXXIV: 93-109).
Springer DOI 2412
BibRef

Oh, Y.J.[Young-Jin], Lee, K.[Keuntek], Lee, J.Y.[Joo-Young], Lee, D.H.[Dae-Hyun], Cho, N.I.[Nam Ik],
Panel-specific Degradation Representation for Raw Under-display Camera Image Restoration,
ECCV24(XLVIII: 359-375).
Springer DOI 2412
BibRef

Jiang, X.Y.[Xing-Yu], Zhang, X.[Xiuhui], Gao, N.[Ning], Deng, Y.[Yue],
When Fast Fourier Transform Meets Transformer for Image Restoration,
ECCV24(XLV: 381-402).
Springer DOI 2412
BibRef

Qi, C.Y.[Chen-Yang], Tu, Z.Z.[Zheng-Zhong], Ye, K.[Keren], Delbracio, M.[Mauricio], Milanfar, P.[Peyman], Chen, Q.F.[Qi-Feng], Talebi, H.[Hossein],
Spire: Semantic Prompt-driven Image Restoration,
ECCV24(XL: 446-464).
Springer DOI 2412
BibRef

Zhou, S.H.[Shi-Hao], Pan, J.S.[Jin-Shan], Shi, J.L.[Jing-Lei], Chen, D.[Duosheng], Qu, L.[Lishen], Yang, J.F.[Ju-Feng],
Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration,
ECCV24(XVI: 246-264).
Springer DOI 2412
BibRef

Zhou, Y.C.[Yi-Chen], Zhou, P.[Pan], Ng, T.K.[Teck Khim],
Efficient Cascaded Multiscale Adaptive Network for Image Restoration,
ECCV24(XIX: 92-110).
Springer DOI 2412
BibRef

Park, D.[Dongwon], Kim, H.[Hayeon], Chun, S.Y.[Se Young],
Contribution-based Low-rank Adaptation with Pre-training Model for Real Image Restoration,
ECCV24(LXIV: 87-105).
Springer DOI 2412
BibRef

Guo, Y.[Yu], Gao, Y.[Yuan], Lu, Y.[Yuxu], Zhu, H.L.[Hui-Lin], Liu, R.W.[Ryan Wen], He, S.F.[Sheng-Feng],
Onerestore: A Universal Restoration Framework for Composite Degradation,
ECCV24(XIX: 255-272).
Springer DOI 2412
BibRef

Qin, C.J.[Chu-Jie], Wu, R.Q.[Rui-Qi], Liu, Z.[Zikun], Lin, X.[Xin], Guo, C.L.[Chun-Le], Park, H.H.[Hyun Hee], Li, C.Y.[Chong-Yi],
Restore Anything with Masks: Leveraging Mask Image Modeling for Blind All-in-one Image Restoration,
ECCV24(XLV: 364-380).
Springer DOI 2412
BibRef

Conde, M.V.[Marcos V.], Vasluianu, F.[Florin], Timofte, R.[Radu],
Toward Efficient Deep Blind Raw Image Restoration,
ICIP24(1725-1731)
IEEE DOI 2411
Degradation, Training, Pipelines, Noise, Superresolution, Noise reduction, Cameras BibRef

Ai, Y.[Yuang], Huang, H.B.[Huai-Bo], Zhou, X.Q.[Xiao-Qiang], Wang, J.X.[Jie-Xiang], He, R.[Ran],
Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration,
CVPR24(25432-25444)
IEEE DOI 2410
Degradation, Visualization, Image restoration BibRef

Nehete, H.[Hemkant], Monga, A.[Amit], Kaushik, P.[Partha], Kaushik, B.K.[Brajesh Kumar],
Fourier Prior-Based Two-Stage Architecture for Image Restoration,
NTIRE24(6014-6023)
IEEE DOI 2410
Degradation, Rain, Computational modeling, Frequency-domain analysis, Computer architecture, Transformers, Fourier Prior BibRef

Ryou, D.H.[Dong-Hun], Ha, I.[Inju], Yoo, H.[Hyewon], Kim, D.W.[Dong-Wan], Han, B.H.[Bo-Hyung],
Robust Image Denoising Through Adversarial Frequency Mixup,
CVPR24(2723-2732)
IEEE DOI Code:
WWW Link. 2410
Training, Frequency-domain analysis, Noise, Noise reduction, Pipelines, Training data, Robustness, Image Denoising, Robustness BibRef

Joshi, A.[Amogh], Akalwadi, N.[Nikhil], Mandi, C.[Chinmayee], Desai, C.[Chaitra], Tabib, R.A.[Ramesh Ashok], Patil, U.[Ujwala], Mudenagudi, U.[Uma],
HNN: Hierarchical Noise-Deinterlace Net Towards Image Denoising,
PBVS24(3007-3016)
IEEE DOI 2410
Attention mechanisms, Noise, Superresolution, Spatial coherence, Imaging, Object detection, Benchmark testing, Image Denoising, Multi-scale BibRef

Li, Y.L.[Ying-Long], Li, J.C.[Jia-Cheng], Xiong, Z.W.[Zhi-Wei],
Look-Up Table Compression for Efficient Image Restoration,
CVPR24(26016-26025)
IEEE DOI Code:
WWW Link. 2410
Image coding, Costs, Source coding, Image edge detection, Superresolution, Table lookup, Image restoration, deblocking BibRef

Gu, E.[Enxuan], Ge, H.W.[Hong-Wei], Guo, Y.[Yong],
CoDe: An Explicit Content Decoupling Framework for Image Restoration,
CVPR24(2920-2930)
IEEE DOI 2410
Codes, Superresolution, Pipelines, Transforms, Benchmark testing, Image restoration, Complexity theory, 13658, Enxuan Gu, CoDe: An Explicit Content Decoupling Framework for Image Restoration BibRef

Li, J.[Jikai], Muramatsu, S.[Shogo],
Inter-Scale Sure-Let Image Restoration with Deep Unrolled Image Prior,
ICIP23(3095-3099)
IEEE DOI 2312
BibRef

Salmon, B.[Benjamin], Krull, A.[Alexander],
Direct Unsupervised Denoising,
BioIm23(3840-3847)
IEEE DOI 2401
BibRef

Cheng, J.[Jun], Liu, T.[Tao], Tan, S.[Shan],
Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising,
ICCV23(12891-12902)
IEEE DOI 2401
BibRef

Lin, X.[Xin], Ren, C.[Chao], Liu, X.[Xiao], Huang, J.[Jie], Lei, Y.J.[Yig-Jie],
Unsupervised Image Denoising in Real-World Scenarios via Self-Collaboration Parallel Generative Adversarial Branches,
ICCV23(12608-12618)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, H.[Hao], Qu, C.Y.[Chen-Yuan], Zhang, Y.[Yu], Chen, C.[Chen], Jiao, J.B.[Jian-Bo],
Multi-view Self-supervised Disentanglement for General Image Denoising,
ICCV23(12247-12257)
IEEE DOI 2401
BibRef

Jang, Y.I.[Yeong Il], Lee, K.[Keuntek], Park, G.Y.[Gu Yong], Kim, S.[Seyun], Cho, N.I.[Nam Ik],
Self-supervised Image Denoising with Downsampled Invariance Loss and Conditional Blind-Spot Network,
ICCV23(12162-12171)
IEEE DOI 2401
BibRef

Liao, X.Y.[Xiang-Yu], Zheng, T.H.[Tian-Heng], Zhong, J.[Jiayu], Zhang, P.P.[Ping-Ping], Ren, C.[Chao],
Asymmetric Mask Scheme for Self-Supervised Real Image Denoising,
ECCV24(XXV: 199-215).
Springer DOI 2412
BibRef

Pan, Y.Z.[Yi-Zhong], Liu, X.[Xiao], Liao, X.Y.[Xiang-Yu], Cao, Y.Z.H.[Yuan-Zhou-Han], Ren, C.[Chao],
Random Sub-Samples Generation for Self-Supervised Real Image Denoising,
ICCV23(12116-12125)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zou, Y.H.[Yun-Hao], Yan, C.G.[Cheng-Gang], Fu, Y.[Ying],
Iterative Denoiser and Noise Estimator for Self-Supervised Image Denoising,
ICCV23(13219-13228)
IEEE DOI 2401
BibRef

Lai, Z.Q.[Ze-Qiang], Yan, C.G.[Cheng-Gang], Fu, Y.[Ying],
Hybrid Spectral Denoising Transformer with Guided Attention,
ICCV23(13019-13029)
IEEE DOI Code:
WWW Link. 2401
BibRef

Liu, K.[Kechun], Jiang, Y.T.[Yi-Tong], Choi, I.[Inchang], Gu, J.[Jinwei],
Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration,
ICCV23(5350-5360)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cui, Y.N.[Yu-Ning], Ren, W.Q.[Wen-Qi], Cao, X.C.[Xiao-Chun], Knoll, A.[Alois],
Focal Network for Image Restoration,
ICCV23(12955-12965)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, X.Y.[Xiang-Yu], Zhen, R.[Ruiwen], Li, S.[Shuai], Li, X.T.[Xiao-Tian], Wang, G.H.[Guang-Hui],
MOFA: A Model Simplification Roadmap for Image Restoration on Mobile Devices,
REDLCV23(1314-1324)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chobola, T.[Tomáš], Müller, G.[Gesine], Dausmann, V.[Veit], Theileis, A.[Anton], Taucher, J.[Jan], Huisken, J.[Jan], Peng, T.[Tingying],
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration,
BioIm23(3876-3885)
IEEE DOI 2401
BibRef

Agnihotri, S.[Shashank], Gandikota, K.V.[Kanchana Vaishnavi], Grabinski, J.[Julia], Chandramouli, P.[Paramanand], Keuper, M.[Margret],
On the unreasonable vulnerability of transformers for image restoration - and an easy fix,
AROW23(3709-3719)
IEEE DOI 2401
BibRef

Sasaki, T.[Takayuki], Bandoh, Y.[Yukihiro], Kitahara, M.[Masaki],
Complexity Reduction of Graph Signal Denoising Based on Fast Graph Fourier Transform,
ICIP23(1910-1914)
IEEE DOI 2312
BibRef

López-Tapia, S.[Santiago], Mateos, J.[Javier], Molina, R.[Rafael], Katsaggelos, A.K.[Aggelos K.],
Deep Robust Image Restoration Using the Moore-Penrose Blur Inverse,
ICIP23(775-779)
IEEE DOI 2312
BibRef

Wang, C.[Chao], Zheng, Z.D.[Zhe-Dong], Quan, R.J.[Rui-Jie], Sun, Y.F.[Yi-Fan], Yang, Y.[Yi],
Context-Aware Pretraining for Efficient Blind Image Decomposition,
CVPR23(18186-18195)
IEEE DOI 2309
Remove multiple types of degradation at once without the noise type. BibRef

Mehta, N.[Nancy], Dudhane, A.[Akshay], Murala, S.[Subrahmanyam], Zamir, S.W.[Syed Waqas], Khan, S.[Salman], Khan, F.S.[Fahad Shahbaz],
Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement,
CVPR23(22201-22210)
IEEE DOI 2309
BibRef

Dudhane, A.[Akshay], Zamir, S.W.[Syed Waqas], Khan, S.[Salman], Khan, F.S.[Fahad Shahbaz], Yang, M.H.[Ming-Hsuan],
Burstormer: Burst Image Restoration and Enhancement Transformer,
CVPR23(5703-5712)
IEEE DOI 2309
BibRef

Feng, R.C.[Rui-Cheng], Li, C.Y.[Chong-Yi], Chen, H.J.[Huai-Jin], Li, S.[Shuai], Gu, J.[Jinwei], Loy, C.C.[Chen Change],
Generating Aligned Pseudo-Supervision from Non-Aligned Data for Image Restoration in Under-Display Camera,
CVPR23(5013-5022)
IEEE DOI 2309
BibRef

Liu, W.Y.[Wen-Yang], Wang, Y.[Yi], Yap, K.H.[Kim-Hui], Chau, L.P.[Lap-Pui],
Bitstream-Corrupted JPEG Images are Restorable: Two-stage Compensation and Alignment Framework for Image Restoration,
CVPR23(9979-9988)
IEEE DOI 2309
BibRef

Li, X.[Xin], Li, B.C.[Bing-Chen], Jin, X.[Xin], Lan, C.L.[Cui-Ling], Chen, Z.B.[Zhi-Bo],
Learning Distortion Invariant Representation for Image Restoration from a Causality Perspective,
CVPR23(1714-1724)
IEEE DOI 2309
BibRef

Mansour, Y.[Youssef], Heckel, R.[Reinhard],
Zero-Shot Noise2Noise: Efficient Image Denoising without any Data,
CVPR23(14018-14027)
IEEE DOI 2309
BibRef

Wan, B.[Bowen], Shi, D.M.[Da-Ming], Liu, Y.K.[Yu-Kun],
STN: Stochastic Triplet Neighboring Approach to Self-supervised Denoising from Limited Noisy Images,
MMMod23(I: 109-120).
Springer DOI 2304
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, 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

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, 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, 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

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

Man, S.[Sean], Ohayon, G.[Guy], Adrai, T.[Theo], Elad, M.[Michael],
High-Perceptual Quality JPEG Decoding via Posterior Sampling,
NTIRE23(1272-1282)
IEEE DOI 2309
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 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

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
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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

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

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],
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Pan, J.F.[Jing-Feng], Cao, T.Y.[Tie-Yong], Zhang, X.W.[Xiong-Wei], Huang, H.[Hui],
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Lobry, S., Denis, L., Tupin, F.,
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Chountasis, S., Pappas, D., Katsikis, V.N.,
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A Blind Source Separation Perspective on Image Restoration,
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Loog, M.[Marco],
Generic Blind Source Separation Using Second-Order Local Statistics,
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Gerace, I.,
Solving the Sparse Data Image Restoration Problem by Local Minimization,
ICIP05(III: 321-324).
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Ben Hamza, A., Krim, H.[Hamid],
Towards a Unified View of Estimation: Variational vs Statistical,
ICIP01(II: 577-580).
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Devcic, Z., Loncaric, S.,
Blind Restoration of Space-invariant Image Degradations in the Singular Value Decomposition Domain,
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Ishwar, P.[Prakash], Moulin, P.[Pierre],
Shift Invariant Restoration: An Overcomplete Maxent MAP Framework,
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Multiple-Domain Image Modeling and Restoration,
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Haseyama, M., Takezawa, M., Kitajima, H.,
An Image Restoration Method Using IFS,
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Fridrich, J.[Jiri], Goljan, M.[Miroslav],
Images with Self-Correcting Capabilities,
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Image restoration using quantum fluctuation,
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Barakat, V., Guilpart, B., Goutte, R., and Prost, R.,
Model-Based Tikhonov-Miller Image Restoration,
ICIP97(I: 310-313).
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SNR Optimization Using Genetic Algorithm,
ICIP97(I: 295-297).
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A Parallel Genetic Algorithm for Image Restoration and Its Performance,
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Lasakul, A., Atsuta, K., Kondo, S.,
A Theory of Image Restoration for Linear Spatial Degradation Using Multiresolution Analysis,
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Two-dimensional cumulant-based adaptive enhancer,
ICIP96(I: 789-792).
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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

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Robust Image Wavelet Shrinkage for Denoising,
ICIP96(I: 371-374).
IEEE DOI BibRef 9600

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A new stochastic projection-based image recovery method,
ICIP95(I: 466-469).
IEEE DOI 9510
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Grigorian, A.[Artiom],
New models of image restoration,
CAIP95(509-514).
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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 .