5.3.9 Noise Removal, Denoising

Kubba, M.H.,
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Lev, A., Zucker, S.W., and Rosenfeld, A.,
Iterative Enhancement of Noisy Images,
SMC(7), 1977, pp. 435-442. Relaxation. BibRef 7700

Davis, L.S., Rosenfeld, A.,
Noise Cleaning by Iterated Local Averaging,
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Ali, F., Pavlidis, T.,
Noise Filtering in Binary Pictures by Combinatorial Techniques,
PR(15), No. 3, 1982, pp. 131-135.
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Arai, Y.[Yoshio], Kataoka, H.[Hiroyuki], Suzuki, I.[Isao], Yokota, S.[Shozo],
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Abdelmalek, N.N.,
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Chin, R.T., Yeh, C.L.,
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Dave, J.V., Gazdag, J.,
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Harouche, E., Peleg, S., Shvaytser, H., Davis, L.S.,
Noisy Image Restoration by Cost Function Minimization,
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Reed, I.S., Yu, X.,
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ASSP(38), No. 10, 1990, pp. 1760-1770.
IEEE DOI BibRef 9000

Boie, R.A., and Cox, I.J.,
An Analysis of Camera Noise,
PAMI(14), No. 6, June 1992, pp. 671-674.
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Wu, W.Y.[Wen-Yen], Wang, M.J.J.[Mao-Jiun J.], Liu, C.M.[Chih-Ming],
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Dougherty, E.R., Haralick, R.M.,
Hole-Spectrum Representation and Model-Based Optimal Morphological Restoration of Binary Images Degraded by Subtractive Noise,
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Olsen, S.I.[Søren I.],
Estimation of Noise in Images: An Evaluation,
GMIP(55), No. 4, July 1993, pp. 319-323.
DOI Link Survey, Noise Estimation. BibRef 9307

Wong, Y.F.[Yiu-Fai],
Clustering filter method for noise filtering, scale-space filtering and image processing,
US_Patent5,424,783, Jun 13, 1995
WWW Link. BibRef 9506

Suthaharan, S., Ray, S.,
Generation of Signal-Uncorrelated Noise for Control Experiments in Image Restoration,
PRL(17), No. 3, March 6 1996, pp. 219-230. BibRef 9603

Itoh, Y.,
Detail Preserving Noise Filtering for Compressed Image,
IEICE(E79-B), No. 10, October 1996, pp. 1459-1466. 9611
BibRef

Mowforth, P.H., Jin, Z.P.,
Implementation for Noise Suppression in Images,
IVC(4), No. 1, February 1986, pp. 29-37.
Elsevier DOI BibRef 8602

Yung, N.H.C., Lai, A.H.S.,
Performance Evaluation of a Feature-Preserving Filtering Algorithm for Removing Additive Random Noise in Digital Images,
OptEng(35), No. 7, July 1996, pp. 1871-1885. 9608
BibRef

Konstantinides, K., Natarajan, B., Yovanof, G.S.,
Noise Estimation and Filtering Using Block-Based Singular-Value Decomposition,
IP(6), No. 3, March 1997, pp. 479-483.
IEEE DOI 9703
SVD. BibRef

Beghdadi, A., Khellaf, A.,
A Noise-Filtering Method Using a Local Information Measure,
IP(6), No. 6, June 1997, pp. 879-882.
IEEE DOI 9705
BibRef

Singh, B., Siddiqi, M.U.,
MAP Estimation of Finite Gray-Scale Digital Images Corrupted by Supremum/Infimum Noise,
IP(6), No. 8, August 1997, pp. 1077-1088.
IEEE DOI 9708
BibRef

Feng, O.Y., Dwyer, G.,
A Real-Time Image Noise Reduction System for FLIR Applications,
RealTimeImg(4), No. 3, June 1998, pp. 211-216. 9807
BibRef

Oja, E., Hyvärinen, A., Hoyer, P.O.[Patrik O.],
Image Feature Extraction and Denoising by Sparse Coding,
PAA(2), No. 2, 1999, pp. 104-110. BibRef 9900

Hyvarinen, A.[Aapo], Hurri, J.[Jarmo], Hoyer, P.O.[Patrik O.], Oja, E.[Erkki],
Image Feature Extraction by Sparse Coding and Independent Component Analysis,
ICPR98(Vol II: 1268-1273).
IEEE DOI 9808
BibRef

Park, J.W., Lee, S.U.,
Recovery of Corrupted Image Data Based on the NURBS Interpolation,
CirSysVideo(9), No. 7, October 1999, pp. 1003.
IEEE Top Reference. BibRef 9910

Bernardini, R., Cortelazzo, G.M.,
A Post-Processing Technique for Noise Removal of Range Data,
CirSysVideo(10), No. 2, March 2000, pp. 201.
IEEE Top Reference. 0003
BibRef

You, Y.L., Kaveh, M.,
Fourth-Order Partial Differential Equations for Noise Removal,
IP(9), No. 10, October 2000, pp. 1723-1730.
IEEE DOI 0010
BibRef

Chen, T., Wu, H.R.,
Recursive LMS L Filters for Noise Removal in Images,
SPLetters(8), No. 2, February 2001, pp. 36-38.
IEEE Top Reference. 0101
BibRef

Chen, T.[Tao], Wu, H.R.[Hong Ren],
Application of partition-based median type filters for suppressing noise in images,
IP(10), No. 6, June 2001, pp. 829-836.
IEEE DOI 0106
BibRef

Lu, Q.[Qing], Jiang, T.Z.[Tian-Zi],
Pixon-Based Image Denoising with Markov Random Fields,
PR(34), No. 10, October 2001, pp. 2029-2039.
Elsevier DOI 0108
Preserve small features, but remove noise.
See also Pixon-based image segmentation with Markov random fields.
See also Novel Pixon-Representation for Image Segmentation Based on Markov Random Field, A. BibRef

Tonazzini, A., Bedini, L.,
Monte Carlo Markov chain techniques for unsupervised MRF-based image denoising,
PRL(24), No. 1-3, January 2003, pp. 55-64.
Elsevier DOI 0211
BibRef

Donoho, D.L.,
Denoising by Soft-Thresholding,
IT(41), No. 3, May 1995, pp. 613-627.
IEEE DOI BibRef 9505

Starck, J.L., Candes, E.J., Donoho, D.L.,
The Curvelet Transform for Image Denoising,
IP(11), No. 6, June 2002, pp. 670-684.
IEEE DOI 0207
BibRef
Earlier: A2 only: ICIP01(I: 7).
IEEE DOI 0108
BibRef

Starck, J.L., Elad, M., Donoho, D.L.,
Image decomposition via the combination of sparse representations and a variational approach,
IP(14), No. 10, October 2005, pp. 1570-1582.
IEEE DOI 0510
Morphological Component Analysis. Represent textured and smooth regions. Iterative thresholding. BibRef

Bobin, J.[Jérôme], Starck, J.L.[Jean-Luc], Fadili, J.M.[Jalal M.], Moudden, Y.[Yassir], Donoho, D.L.[David L.],
Morphological Component Analysis: An Adaptive Thresholding Strategy,
IP(16), No. 11, November 2007, pp. 2675-2681.
IEEE DOI 0709
Improve on Morphological Component Analysis to improve convergence of iteration. BibRef

Gluhovsky, I.[Ilya], Melnik, V.P.[Vladimir P.], Shmulevich, I.[Ilya],
Markov Random Field Modeling in Median Pyramidal Transform Domain for Denoising Applications,
JMIV(16), No. 3, May 2002, pp. 237-249.
DOI Link 0211
BibRef

Atae-Allah, Z.[Zakaria], Aroza, J.M.[José Martínez],
A Filter To Remove Gaussian Noise by Clustering the Gray Scale,
JMIV(17), No. 1, July 2002, pp. 15-25.
DOI Link 0211
BibRef

Ritter, G.X.[Gerhard X.], Urcid, G.[Gonzalo], Iancu, L.[Laurentiu],
Reconstruction of Patterns from Noisy Inputs Using Morphological Associative Memories,
JMIV(19), No. 2, September 2003, pp. 95-111.
DOI Link 0308
BibRef

Park, U.S.[Un-Sang], Udpa, L.[Lalita], Stockman, G.C.[George C.],
Motion-based filtering of magneto-optic imagers,
IVC(22), No. 3, 1 March 2004, pp. 243-249.
Elsevier DOI 0402
For aircraft inspection. Eliminate noise. BibRef

Lysaker, M.[Marius], Osher, S.J., Tai, X.C.[Xue-Cheng],
Noise Removal Using Smoothed Normals and Surface Fitting,
IP(13), No. 10, October 2004, pp. 1345-1357.
IEEE DOI 0410
LOT Model. Alleviate the staircase effect. BibRef

Hawksford, M.O.J.,
Parametrically controlled noise shaping in variable state-step-back pseudo-trellis SDM,
VISP(152), No. 1, February 2005, pp. 87-96.
IEEE Abstract. 0501
BibRef

Rabie, T.,
Robust Estimation Approach for Blind Denoising,
IP(14), No. 11, November 2005, pp. 1755-1765.
IEEE DOI 0510
BibRef

Coupier, D., Desolneux, A., Ycart, B.,
Image Denoising by Statistical Area Thresholding,
JMIV(22), No. 2-3, May 2005, pp. 183-197.
Springer DOI 0505
BibRef

Mahmoudi, M., Sapiro, G.,
Fast Image and Video Denoising via Nonlocal Means of Similar Neighborhoods,
SPLetters(12), No. 12, December 2005, pp. 839-842.
IEEE DOI 0512
BibRef

Balan, R.V.[Radu V.], Rosca, J.[Justinian], Rickard, S.T.[Scott T.],
Equivalence principle for optimization of sparse versus low-spread representations for signal estimation in noise,
IJIST(15), No. 1, 2005, pp. 10-17.
DOI Link 0507
BibRef

Sorzano, C.O.S., Ortiz, E., López, M., Rodrigo, J.,
Improved Bayesian image denoising based on wavelets with applications to electron microscopy,
PR(39), No. 6, June 2006, pp. 1205-1213.
Elsevier DOI Image denoising; Bayesian filtering; Wavelets 0604
BibRef

Pizurica, A., Philips, W.,
Estimating the Probability of the Presence of a Signal of Interest in Multiresolution Single- and Multiband Image Denoising,
IP(15), No. 3, March 2006, pp. 654-665.
IEEE DOI 0604
BibRef

Goossens, B., Pizurica, A., Philips, W.,
Image Denoising Using Mixtures of Projected Gaussian Scale Mixtures,
IP(18), No. 8, August 2009, pp. 1689-1702.
IEEE DOI 0907

See also joint inter- and intrascale statistical model for bayesian wavelet based image denoising, A.
See also Removal of Correlated Noise by Modeling the Signal of Interest in the Wavelet Domain. BibRef

Goossens, B.[Bart], Aelterman, J.[Jan], Luong, H.[Hiep], Pizurica, A.[Aleksandra], Philips, W.[Wilfried],
Complex wavelet joint denoising and demosaicing using Gaussian scale mixtures,
ICIP13(445-448)
IEEE DOI 1402
Image edge detection BibRef

Yasotharan, A., Thayaparan, T.,
Optimum time~frequency distribution for detecting a discrete-time chirp signal in noise,
VISP(153), No. 2, April 2006, pp. 132-140. 0604
BibRef

Kim, S.,
PDE-Based Image Restoration: A Hybrid Model and Color Image Denoising,
IP(15), No. 5, May 2006, pp. 1163-1170.
IEEE DOI 0605
BibRef

Shen, L., Papadakis, M., Kakadiaris, I.A., Konstantinidis, I., Kouri, D., Hoffman, D.,
Image Denoising Using a Tight Frame,
IP(15), No. 5, May 2006, pp. 1254-1263.
IEEE DOI 0605
BibRef

Santamaria-Pang, A., Bildea, T.S., Tan, S., Kakadiaris, I.A.,
Denoising for 3-D Photon-Limited Imaging Data Using Nonseparable Filterbanks,
IP(17), No. 12, December 2008, pp. 2312-2323.
IEEE DOI 0811
BibRef

Wei, J.[Jie],
Lebesgue anisotropic image denoising,
IJIST(15), No. 1, 2005, pp. 64-73.
DOI Link 0507
BibRef

Faraji, H., Maclean, W.J.,
CCD Noise Removal in Digital Images,
IP(15), No. 9, August 2006, pp. 2676-2685.
IEEE DOI 0608
BibRef

Hirakawa, K., Parks, T.W.,
Image Denoising Using Total Least Squares,
IP(15), No. 9, August 2006, pp. 2730-2742.
IEEE DOI 0608
BibRef

Ortiz, F., Torres, F.,
Automatic detection and elimination of specular reflectance in color images by means of MS diagram and vector connected filters,
SMC-C(36), No. 5, September 2006, pp. 681-687.
IEEE DOI 0609
BibRef

Ortiz, F., Torres, F., Gil, P.,
Gaussian noise elimination in colour images by vector-connected filters,
ICPR04(IV: 807-810).
IEEE DOI 0409
BibRef

Elad, M.[Michael], Aharon, M.[Michal],
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries,
IP(15), No. 12, December 2006, pp. 3736-3745.
IEEE DOI 0611
BibRef
Earlier:
Image Denoising Via Learned Dictionaries and Sparse representation,
CVPR06(I: 895-900).
IEEE DOI 0606
BibRef

Sulam, J.[Jeremias], Elad, M.[Michael],
Expected Patch Log Likelihood with a Sparse Prior,
EMMCVPR15(99-111).
Springer DOI 1504

See also From learning models of natural image patches to whole image restoration. BibRef

Sulam, J.[Jeremias], Ophir, B.[Boaz], Elad, M.[Michael],
Image denoising through multi-scale learnt dictionaries,
ICIP14(808-812)
IEEE DOI 1502
Algorithm design and analysis BibRef

Protter, M., Elad, M.,
Image Sequence Denoising via Sparse and Redundant Representations,
IP(18), No. 1, January 2009, pp. 27-35.
IEEE DOI 0812

See also Generalizing the Nonlocal-Means to Super-Resolution Reconstruction. BibRef

Aharon, M.[Michal], Elad, M.[Michael], Bruckstein, A.M.,
K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation,
TSP(54), No. 11, November 2006, pp. 4311-4322.
IEEE DOI
See also implementation and detailed analysis of the K-SVD image denoising algorithm, An. BibRef 0611

Scetbon, M.[Meyer], Elad, M.[Michael], Milanfar, P.[Peyman],
Deep K-SVD Denoising,
IP(30), 2021, pp. 5944-5955.
IEEE DOI 2107
Noise reduction, Dictionaries, Image denoising, Task analysis, Noise measurement, Training, Bridges, K-SVD denoising algorithm, iterative shrinkage algorithms BibRef

Aharon, M.[Michal], Elad, M.[Michael],
Sparse And Redundant Modeling Of Image Content Using An Image-Signature-Dictionary,
SIIMS(1), No. 3, 2008, pp. 228-247. sparse representation; matching pursuit; denoising; image-signature; dictionary; learning; MOD
DOI Link BibRef 0800

Mairal, J.[Julien], Elad, M.[Michael], Sapiro, G.[Guillermo],
Sparse Representation for Color Image Restoration,
IP(17), No. 1, January 2008, pp. 53-69.
IEEE DOI 0712
BibRef
Earlier: A1, A3, A2:
Multiscale Sparse Image Representation with Learned Dictionaries,
ICIP07(III: 105-108).
IEEE DOI 0709
BibRef

Bruckstein, A.M., Elad, M.,
On Sparse Signal Representations,
ICIP01(I: 3-6).
IEEE DOI 0108
BibRef

Elad, M.[Michael], Matalon, B.[Boaz], Zibulevsky, M.[Michael],
Image Denoising with Shrinkage and Redundant Representations,
CVPR06(II: 1924-1931).
IEEE DOI 0606
BibRef

Segev, D.[Dana], Schechner, Y.Y.[Yoav Y.], Elad, M.[Michael],
Example-based cross-modal denoising,
CVPR12(486-493).
IEEE DOI 1208
BibRef

Mairal, J.[Julien], Bach, F.[Francis], Ponce, J.[Jean],
Task-Driven Dictionary Learning,
PAMI(34), No. 4, April 2012, pp. 791-804.
IEEE DOI 1203
Model data with linear combinations of few elements. BibRef

Pan, R., Reeves, S.J.,
Efficient Huber-Markov Edge-Preserving Image Restoration,
IP(15), No. 12, December 2006, pp. 3728-3735.
IEEE DOI 0611
BibRef

Xiao, J.J., Luo, Z.Q., Giannakis, G.B.,
Performance Bounds for the Rate-Constrained Universal Decentralized Estimators,
SPLetters(14), No. 1, January 2007, pp. 47-50.
IEEE DOI 0701
BibRef

Lerallut, R.[Romain], Decenciere, E.[Etienne], Meyer, F.[Fernand],
Image filtering using morphological amoebas,
IVC(25), No. 4, April 2007, pp. 395-404.
Elsevier DOI 0702
Anisotropic filters; Noise reduction; Morphological filters; Color filters; 3D image processing BibRef

Lerallut, R., Boehm, M., Decenciere, E., Meyer, F.,
Noise Reduction in 3D Images Using Morphological Amoebas,
ICIP05(I: 109-112).
IEEE DOI 0512
BibRef

Mignotte, M.,
Image Denoising by Averaging of Piecewise Constant Simulations of Image Partitions,
IP(16), No. 2, February 2007, pp. 523-533.
IEEE DOI 0702
BibRef

Olhede, S.C.,
Hyperanalytic Denoising,
IP(16), No. 6, June 2007, pp. 1522-1537.
IEEE DOI 0706
BibRef

Cheng, T., Belzer, B.J., Sivakumar, K.,
Row-Column Soft-Decision Feedback Algorithm for Two-Dimensional Intersymbol Interference,
SPLetters(14), No. 7, July 2007, pp. 433-436.
IEEE DOI 0707
Corrupted binary images. BibRef

Shang, L.[Li],
Non-negative sparse coding shrinkage for image denoising using normal inverse Gaussian density model,
IVC(26), No. 8, 1 August 2008, pp. 1137-1147.
Elsevier DOI 0806
Normal inverse Gaussian density; Image denoising; Non-negative sparse coding; Shrinkage function; Maximum a posterior estimator BibRef

Shang, L.[Li], Huang, D.S.[De-Shuang],
Image Denoising Using Non-Negative Sparse Coding Shrinkage Algorithm,
CVPR05(I: 1017-1022).
IEEE DOI 0507
BibRef

Shi, Y.Y.[Yu-Ying],
Convergence of Fixed Point Iteration for Modified Restoration Problems,
JMIV(32), No. 1, September 2008, pp. xx-yy.
Springer DOI 0804
BibRef

Jia, T.T.[Tong-Tong], Shi, Y.Y.[Yu-Ying], Zhu, Y.G.[Yong-Gui], Wang, L.[Lei],
An image restoration model combining mixed L1/L2 fidelity terms,
JVCIR(38), No. 1, 2016, pp. 461-473.
Elsevier DOI 1605
Image restoration BibRef

Bi, D.L.[Dong-Liang], Guo, W.[Wei], Xu, A.D.[Ai-Dong],
A New Noise Removing Algorithm,
IJIG(6), No. 4, October 2006, pp. 677-687. 0610
BibRef

Singer, A.[Amit], Shkolnisky, Y.[Yoel], Nadler, B.[Boaz],
Diffusion Interpretation Of Nonlocal Neighborhood Filters For Signal Denoising,
SIIMS(2), No. 1, 2009, pp. 118-139. denoising; neighborhood filters; nonlocal means; FokkerPlanck equation; first passage time.
DOI Link BibRef 0900

Levin, A.[Anat], Nadler, B.[Boaz],
Natural image denoising: Optimality and inherent bounds,
CVPR11(2833-2840).
IEEE DOI 1106
BibRef

Dong, F.F.[Fang-Fang], Liu, Z.[Zhen], Kong, D.X.[De-Xing], Liu, K.F.[Ke-Feng],
An Improved LOT Model for Image Restoration,
JMIV(34), No. 1, May 2009, pp. xx-yy.
Springer DOI 0905
Smooth angle rather than normal. Preserve fine structure.
See also Noise Removal Using Smoothed Normals and Surface Fitting. BibRef

Liu, Z.[Zhen], Dong, F.F.[Fang-Fang], Bai, Y.Q.[Yong-Qiang], Liu, K.F.[Ke-Feng],
Discrete Total Variation Model with Gradient Fidelity Term for Image Restoration,
CISP09(1-5).
IEEE DOI 0910
BibRef

Wu, Y.D., Sun, Y., Zhang, H.Y., Sun, S.X.,
Variational PDE based image restoration using neural network,
IET-IPR(1), No. 1, March 2007, pp. 85-93.
DOI Link 0905
BibRef

Gowda, R.[Rahul], Mehta, S.M.[Shalin M.], Yang, Y.[Yue], Li, B.X.[Bao-Xin],
Adaptive Nonlinear Image Enhancement of Gaussian Degraded Images,
IJIG(10), No. 3, July 2010, pp. 365-393.
DOI Link 1003
BibRef

Motta, G., Ordentlich, E., Ramirez, I., Seroussi, G., Weinberger, M.J.,
The iDUDE Framework for Grayscale Image Denoising,
IP(20), No. 1, January 2011, pp. 1-21.
IEEE DOI 1101
BibRef
Earlier:
The Dude Framework for Continuous Tone Image Denoising,
ICIP05(III: 345-348).
IEEE DOI 0512
BibRef

Ordentlich, E., Seroussi, G., Verdii, S., Weinberger, M.J., Weissman, T.,
A discrete universal denoiser and its application to binary images,
ICIP03(I: 117-120).
IEEE DOI 0312
BibRef

Grewenig, S.[Sven], Zimmer, S.[Sebastian], Weickert, J.[Joachim],
Rotationally invariant similarity measures for nonlocal image denoising,
JVCIR(22), No. 2, February 2011, pp. 117-130.
Elsevier DOI 1102
Block matching; Similarity measures; Moment invariants; Rotational invariance; Nonlocal means; Denoising; Rotation estimation; Structure tensor BibRef

Nielsen, A.A.,
Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations,
IP(20), No. 3, March 2011, pp. 612-624.
IEEE DOI 1103
BibRef

Nielsen, A.A.,
An extension to a filter implementation of a local quadratic surface for image noise estimation,
CIAP99(119-124).
IEEE DOI 9909
BibRef

Lei, T., Fan, Y.Y.,
Noise gradient reduction based on morphological dual operators,
IET-IPR(5), No. 1, February 2011, pp. 1-17.
DOI Link 1103
BibRef

Hajiaboli, M.R.[Mohammad Reza],
An Anisotropic Fourth-Order Diffusion Filter for Image Noise Removal,
IJCV(92), No. 2, April 2011, pp. 177-191.
WWW Link. 1103
BibRef
Earlier:
An Anisotropic Fourth-Order Partial Differential Equation for Noise Removal,
SSVM09(356-367).
Springer DOI 0906
BibRef
And:
A Self-governing Hybrid Model for Noise Removal,
PSIVT09(295-305).
Springer DOI 0901
BibRef

Hajiaboli, M.R.[Mohammad Reza], Ahmad, M.O., Wang, C.,
An Edge-Adapting Laplacian Kernel For Nonlinear Diffusion Filters,
IP(21), No. 4, April 2012, pp. 1561-1572.
IEEE DOI 1204
BibRef

Guidotti, P.[Patrick], Longo, K.[Kate],
Two Enhanced Fourth Order Diffusion Models for Image Denoising,
JMIV(40), No. 2, June 2011, pp. 188-198.
WWW Link. 1103
BibRef

Min, T.H.[Tae-Hong], Park, R.H.[Rae-Hong], Chang, S.K.[Soon-Keun],
Noise reduction in high dynamic range images,
SIViP(5), No. 3, September 2011, pp. 315-328.
WWW Link. 1109
BibRef

Peters, J.[Jonas], Janzing, D.[Dominik], Scholkopf, B.[Bernhard],
Causal Inference on Discrete Data Using Additive Noise Models,
PAMI(33), No. 12, December 2011, pp. 2436-2450.
IEEE DOI 1110
Inferring the structure of a set of random variables from a finite sample. BibRef

Gomez-Rodriguez, M., Kober, J., Scholkopf, B.[Bernhard],
Denoising photographs using dark frames optimized by quadratic programming,
ICCP09(1-9).
IEEE DOI 1208
Long exposure photos. Start with set of dark images, subtract these. BibRef

Qiu, Z.[Zhen], Yang, L.[Lei], Lu, W.P.[Wei-Ping],
A new feature-preserving nonlinear anisotropic diffusion for denoising images containing blobs and ridges,
PRL(33), No. 3, 1 February 2012, pp. 319-330.
Elsevier DOI 1201
BibRef
Earlier:
A New Feature-preserving Nonlinear Anisotropic Diffusion Method for Image Denoising,
BMVC11(xx-yy).
HTML Version. 1110
Image denoising; Nonlocal difference; Second-order derivative; Blob and ridge detection; Nonlinear diffusion BibRef

Wen, Y.W., Chan, R.H.,
Parameter Selection for Total-Variation-Based Image Restoration Using Discrepancy Principle,
IP(21), No. 4, April 2012, pp. 1770-1781.
IEEE DOI 1204
BibRef

Rajpoot, N.M.[Nasir M.], Butt, I.T.[Irfan T.],
A multiresolution framework for local similarity based image denoising,
PR(45), No. 8, August 2012, pp. 2938-2951.
Elsevier DOI 1204
BibRef
Earlier: A2, A1:
Multilateral filtering: A novel framework for generic similarity-based image denoising,
ICIP09(2981-2984).
IEEE DOI 0911
Image denoising; Bilateral filtering; Local image statistics BibRef

Yao, Z.[Zhen], Rajpoot, N.M.,
Image Denoising Using Multiscale Directional Cosine Bases,
ICIP05(III: 313-316).
IEEE DOI 0512
BibRef

Leclaire, A.[Arthur], Lebrun, M.[Marc],
An implementation and detailed analysis of the K-SVD image denoising algorithm,
IPOL(2012), No. 2012, pp. xx-yy.
DOI Link 1205
Code, Denoising.
See also K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation. BibRef

Chen, S.F.[Shi-Feng], Liu, M.[Ming], Zhang, W.[Wei], Liu, J.Z.[Jian-Zhuang],
Edge preserving image denoising with a closed form solution,
PR(46), No. 3, March 2013, pp. 976-988.
Elsevier DOI 1212
Image denoising; Markov random field; Label relaxation; Closed form solution BibRef

Liu, M.[Ming], Chen, S.F.[Shi-Feng], Liu, J.Z.[Jian-Zhuang],
Continuous MRF based image denoising with a closed form solution,
ICIP10(1137-1140).
IEEE DOI 1009
BibRef

Tsiotsios, C.[Chourmouzios], Petrou, M.[Maria],
On the choice of the parameters for anisotropic diffusion in image processing,
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Elsevier DOI 1302
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SIIMS(6), No. 3, 2013, pp. 1665-1688.
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Colom, M.[Miguel], Buades, A.[Antoni],
Analysis and Extension of the Ponomarenko et al. Method, Estimating a Noise Curve from a Single Image,
IPOL(2012), No. 2012, pp. xx-yy.
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Code, Noise Estimation.
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Colom, M.[Miguel], Buades, A.[Antoni],
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Colom, M.[Miguel], Buades, A.[Antoni],
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IPOL(6), 2016, pp. 365-390.
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PRL(34), No. 16, 2013, pp. 2110-2117.
Elsevier DOI 1310
Image denoising BibRef

Sun, Z.G.[Zhong-Gui], Chen, S.C.[Song-Can], Qiao, L.S.[Li-Shan],
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PR(47), No. 4, 2014, pp. 1751-1763.
Elsevier DOI 1402
Image denoising BibRef

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ICPR04(IV: 685-688).
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Acta Numerica(21), 2012, pp. 475-576.
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IP(24), No. 10, October 2015, pp. 3149-3161.
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IPOL(5), 2015, pp. 1-54.
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ICIP14(2674-2678)
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SPLetters(21), No. 3, March 2014, pp. 347-351.
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Gaussian noise BibRef

Jiang, J., Zhang, L., Yang, J.,
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Aboutanios, E., Ye, S.,
Efficient Iterative Estimation of the Parameters of a Damped Complex Exponential in Noise,
SPLetters(21), No. 8, August 2014, pp. 975-979.
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Ye, S., Sun, J., Aboutanios, E.,
On the Estimation of the Parameters of a Real Sinusoid in Noise,
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IEEE DOI 1704
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Algorithm design and analysis Estimation, Monte Carlo methods, Signal to noise ratio BibRef

Ding, W., Lin, E., Ribeiro, A., Sarunic, M.V., Tibbits, G.F., Beg, M.F.,
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Biomedical optical imaging BibRef

Lenzen, F.[Frank], Lellmann, J.[Jan], Becker, F.[Florian], Schnörr, C.[Christoph],
Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets,
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Variational Image Denoising with Adaptive Constraint Sets,
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Compressed Motion Sensing,
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Performance Bounds for Cosparse Multichannel Signal Recovery via Collaborative-TV,
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A New Augmented Lagrangian Approach for L^1-mean Curvature Image Denoising,
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PR(48), No. 10, 2015, pp. 3135-3144.
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Image processing BibRef

Xie, Y., Gu, S., Liu, Y., Zuo, W., Zhang, W., Zhang, L.,
Weighted Schatten-p Norm Minimization for Image Denoising and Background Subtraction,
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computer vision BibRef

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Image denoising via local and nonlocal circulant similarity,
JVCIR(30), No. 1, 2015, pp. 117-124.
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Yuan, J.J.[Jian-Jun], Liu, L.[Lipei],
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IEEE DOI 1605
Image denoising BibRef

Varghese, J., Subash, S., Tairan, N.,
Fourier transform-based windowed adaptive switching minimum filter for reducing periodic noise from digital images,
IET-IPR(10), No. 9, 2016, pp. 646-656.
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Fourier transforms BibRef

Li, W.[Wan], Liu, F.[Fang], Jiao, L.C.[Li-Cheng], Hao, H.X.[Hong-Xia], Yang, S.Y.[Shu-Yuan],
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SP:IC(49), No. 1, 2016, pp. 47-62.
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Compressive sensing BibRef

Liu, L.C.[Li-Cheng], Chen, L.[Long], Chen, C.L.P.[C.L. Philip], Tang, Y.Y.[Yuan Yan], Pun, C.M.[Chi Man],
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Image segmentation, Image restoration, Mumford-Shah model BibRef

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Sparse Overcomplete Denoising: Aggregation Versus Global Optimization,
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IEEE DOI 1710
approximation theory, image coding, image denoising, image representation, aggregation, convolutional sparse representation, global optimization, BibRef

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correlation methods, filtering theory, image denoising, learning (artificial intelligence), statistical analysis, sparse representation BibRef

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IEEE DOI 1809
Noise reduction, Noise measurement, Noise level, Image denoising, Machine learning algorithms, Prediction algorithms, region-aware BibRef

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filtering theory, image denoising, mean square error methods, neural nets, optimisation, image denoisers, convolutional neural networks BibRef

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JVCIR(62), 2019, pp. 286-294.
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Image denoising, Correlated noise, Convolutional neural networks, Deep learning BibRef

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Image denoising, Noise reduction, Gaussian noise, Optimization, Sparse matrices, Dictionaries, Integrated circuit modeling, low-rank recovery BibRef

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ICIP19(2399-2403)
IEEE DOI 1910
Convolution, Noise reduction, Image denoising, Biological neural networks, graph convolution. BibRef

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Tensile stress, Noise reduction, Matrix decomposition, Indexes, Signal processing, Machine learning, tensor decomposition BibRef

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ICIP20(330-334)
IEEE DOI 2011
Image reconstruction, TV, Tensile stress, Robustness, total variation BibRef

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Image denoising, Nonlocal self-similarity, Weight matrix, Weighted sparse coding BibRef

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IEEE DOI 2110
Convergence, Kernel, Noise reduction, Image restoration, Inverse problems, Task analysis, Symmetric matrices, Convergence, plug-and-play BibRef

Malladi, S.R.S.P.[Sree Ramya S. P.], Ram, S.[Sundaresh], Rodríguez, J.J.[Jeffrey J.],
Image Denoising Using Superpixel-Based PCA,
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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,
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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.
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Gao, Q.X.[Quan-Xue], Zhang, P.[Pu], Xia, W.[Wei], Xie, D.[Deyan], Gao, X.B.[Xin-Bo], Tao, D.C.[Da-Cheng],
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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

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

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.
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Yin, H.T.[Hai-Tao], Ma, S.Y.[Si-Yuan],
CSformer: Cross-Scale Features Fusion Based Transformer for Image Denoising,
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IEEE DOI 2209
Transformers, Feature extraction, Convolution, Noise measurement, Image denoising, Noise reduction, Noise level, Cross-scale, transformer BibRef

Wu, D.[Di], Zhang, T.[Tao],
Corrected rank residual constraint model for image denoising,
IET-IPR(16), No. 13, 2022, pp. 3659-3668.
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JVCIR(88), 2022, pp. 103626.
Elsevier DOI 2210
Merge multiple denoising results. Image denoising, Boosting denoising performance, Deep fusion network, Unsupervised training strategy 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.
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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

Yao, M.[Mingde], He, D.L.[Dong-Liang], Li, X.[Xin], Li, F.[Fu], Xiong, Z.W.[Zhi-Wei],
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CirSysVideo(33), No. 10, October 2023, pp. 5360-5374.
IEEE DOI 2310
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Frequency-Domain Deep Guided Image Denoising,
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IEEE DOI 2311
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Jiang, J.[Jielin], Hong, X.M.[Xiang-Ming], Zhao, Y.N.[Ying-Nan], Xu, X.L.[Xiaong-Long], Cui, Y.[Yan],
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IET-IPR(17), No. 13, 2023, pp. 3884-3896.
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convolution, image denoising, Gaussian noise BibRef

Liu, F.Y.[Feng-Yin], Zhou, Z.Q.[Zi-Qun], Men, C.Y.[Chang-You], Sun, Q.[Quan], Huang, K.J.[Ke-Jie],
IFGLT: Information fusion guided lightweight Transformer for image denoising,
JVCIR(97), 2023, pp. 103994.
Elsevier DOI 2312
Image denoising, Transformer, Lightweight network BibRef

Dutta, S.[Sayantan], Basarab, A.[Adrian], Kouamé, D.[Denis], Georgeot, B.[Bertrand],
Quantum Algorithm for Signal Denoising,
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IEEE DOI 2401
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Earlier: A1, A2, A4, A3:
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

Xie, X.H.[Xin-Heng], Wu, Y.[Yue], Ni, H.[Hao], He, C.[Cuiyu],
NODE-ImgNet: A PDE-informed effective and robust model for image denoising,
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Elsevier DOI 2402
Image denoising, NODE network, PDE learning BibRef

Zhang, S.P.[Sheng-Ping], Yu, W.[Wei], Jiang, F.[Feng], Nie, L.Q.[Li-Qiang], Yao, H.X.[Hong-Xun], Huang, Q.M.[Qing-Ming], Tao, D.C.[Da-Cheng],
Stereo Image Restoration via Attention-Guided Correspondence Learning,
PAMI(46), No. 7, July 2024, pp. 4850-4865.
IEEE DOI 2406
Image restoration, Task analysis, Superresolution, Correlation, Noise reduction, Transformers, Image coding, stereo matching BibRef

Wu, J.[Jing], Xie, R.[Ruilin], Wu, H.[Hao], Yuan, G.W.[Guo-Wu],
Improving the generalization of image denoising via structure-preserved MLP-based denoiser and generative diffusion prior,
IET-IPR(18), No. 10, 2024, pp. 2625-2644.
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convolutional neural nets, image denoising, image processing BibRef

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Hierarchical disentangled representation for image denoising and beyond,
IVC(149), 2024, pp. 105165.
Elsevier DOI 2408
Invertible image denoising, Bijective transformation, Disentangling learning, Hierarchical representation BibRef

Li, X.Y.[Xiao-Yu], Zhang, B.[Bo], Liao, J.[Jing], Sander, P.V.[Pedro V.],
Let's See Clearly: Contaminant Artifact Removal for Moving Cameras,
ICCV21(1991-2000)
IEEE DOI 2203
e.g. dust on lens. Codes, Fuses, Video sequences, Moisture, Lighting, Cameras, Computational photography, Low-level and physics-based vision BibRef

Jia, X.X.[Xi-Xi], Liu, S.Y.[San-Yang], Feng, X.C.[Xiang-Chu], Zhang, L.[Lei],
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CVPR19(6047-6056).
IEEE DOI 2002
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Probabilistic End-To-End Noise Correction for Learning With Noisy Labels,
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CVPR18(2433-2442)
IEEE DOI 1812
Noise reduction, Task analysis, Image restoration, Image resolution, Training, Convolution BibRef

Yair, N., Michaeli, T.,
Multi-scale Weighted Nuclear Norm Image Restoration,
CVPR18(3165-3174)
IEEE DOI 1812
Image restoration, Noise reduction, Degradation, Image denoising, Optimization, Task analysis, Minimization BibRef

Abdelhamed, A., Lin, S., Brown, M.S.,
A High-Quality Denoising Dataset for Smartphone Cameras,
CVPR18(1692-1700)
IEEE DOI 1812
Cameras, Noise measurement, Noise reduction, Estimation, Benchmark testing, Lighting, Image denoising BibRef

Arias, P.[Pablo], Nikolova, M.[Mila],
Below the Surface of the Non-local Bayesian Image Denoising Method,
SSVM17(208-220).
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Barbu, T.,
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WSSIP16(1-4)
IEEE DOI 1608
finite difference methods BibRef

Tang, Y., Chen, Y., Xu, N., Jiang, A., Gao, Y.,
Image denoising via sparse approximation using eigenvectors of graph Laplacian,
VCIP15(1-4)
IEEE DOI 1605
Approximation algorithms BibRef

Zhao, A., Durand, F., Guttag, J.,
Estimating a Small Signal in the Presence of Large Noise,
Extreme15(671-676)
IEEE DOI 1602
Blood BibRef

Navarro, L.[Laurent], Jourlin, M.[Michel], Courbebaisse, G.[Guy],
Logarithmic multiresolution analysis,
ICIP15(3827-3831)
IEEE DOI 1512
De-noising BibRef

Thanh, D.N.H., Dvoenko, S.D.,
A Denoising of Biomedical Images,
PTVSBB15(73-78).
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Pham, C.T., Kopylov, A.V.,
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PTVSBB15(101-106).
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Miyata, M., Kodama, K., Hamamoto, T.,
Fast multiple-view denoising based on image reconstruction by plane sweeping,
VCIP14(462-465)
IEEE DOI 1504
image denoising BibRef

Peng, G.J.[Guan-Ju], Hwang, W.L.[Wen-Liang],
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VCIP14(17-20)
IEEE DOI 1504
image denoising BibRef

Prasath, V.B.S., Moreno, J.C.,
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NCVPRIPG13(1-4)
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ICIP13(1095-1099)
IEEE DOI 1402
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ICIP12(1189-1192).
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Saghaian Nejad Esfahani, S.M.[Sayed M.], Luo, Y.[Ying], Cheung, S.C.S.[Sen-Ching S.],
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ICIP12(253-256).
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Wen, F.[Fang], Li, T.Z.[Tian-Ze],
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Huang, C.[Cheng], Zhu, Y.L.[You-Lian],
New Morphological Filtering Algorithm for Image Noise Reduction,
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ICIP23(101-105)
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ICIP04(II: 977-980).
IEEE DOI 0505
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Multiresolution image analysis using dual fresnel transform pairs and application to medical image denoising,
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Rosiles, J., Smith, M.,
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Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Noise Removal, Impulse Noise, Salt and Pepper .