5.3.9.5 Multiplicative Noise Removal

Chapter Contents (Back)
Noise Removal. Multiplicative Noise. Multiplicative Denoising.

Javidi, B., Wang, J.,
Optimum Filter for Detecting a Target in Multiplicative Noise and Additive Noise,
JOSA-A(14), No. 4, April 1997, pp. 836-844. 9704
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Farbiz, F.[Farzam], Menhaj, M.B.[Mohammad Bagher], Motamedi, S.A.[Seyed Ahmad], Hagan, M.T.,
A New Fuzzy Logic Filter for Image Enhancement,
SMC-B(30), No. 1, February 2000, pp. 110-120.
IEEE Top Reference. 0004
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Farbiz, F.[Farzam], Menhaj, M.B.[Mohammad Bagher], Motamedi, S.A.[Seyed Ahmad],
A Modified Iterative Fuzzy Control Based Filter for Image Enhancement with Multiplicative Noise Removal Property,
ICIP99(I:539-544).
IEEE DOI BibRef 9900
Earlier:
Fixed point filter design for image enhancement using fuzzy logic,
ICIP98(II: 838-842).
IEEE DOI 9810
BibRef

Rangayyan, R.M., Das, A.,
Filtering Multiplicative Noise in Images Using Adaptive Region Based Statistics,
JEI(7), No. 1, January 1998, pp. 222-230. 9807
BibRef

Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano], Borri, G.,
Pyramid-Based Multiresolution Adaptive Filters for Additive and Multiplicative Image Noise,
CirSysSignal(45), No. 8, August 1998, pp. 1092-1097. 9809
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Aiazzi, B.[Bruno], Alparone, L.[Luciano], Baronti, S.[Stefano],
Multiresolution Local-Statistics Speckle Filtering Based on a Ratio Laplacian Pyramid,
GeoRS(36), No. 5, September 1998, pp. 1466.
IEEE Top Reference. BibRef 9809
Earlier:
Multiresolution Adaptive Filtering of Signal-Dependent Noise Based on a Generalized Laplacian Pyramid,
ICIP97(I: 381-384).
IEEE DOI BibRef

Alparone, L.[Luciano], Baronti, S.[Stefano], Aiazzi, B.[Bruno], Garzelli, A.,
Spatial Methods for Multispectral Pansharpening: Multiresolution Analysis Demystified,
GeoRS(54), No. 5, May 2016, pp. 2563-2576.
IEEE DOI 1604
Laplace equations BibRef

Hawwar, Y., Reza, A.,
Spatially adaptive multiplicative noise image denoising technique,
IP(11), No. 12, December 2002, pp. 1397-1404.
IEEE DOI 0301
BibRef

Huang, L.L.[Li-Li], Xiao, L.[Liang], Wei, Z.H.[Zhi-Hui],
Multiplicative Noise Removal via a Novel Variational Model,
JIVP(2010), No. 2010, pp. xx-yy.
DOI Link 1003
BibRef

Zhang, J.[Jun], Wei, Z.H.[Zhi-Hui], Xiao, L.[Liang],
Adaptive Fractional-order Multi-scale Method for Image Denoising,
JMIV(43), No. 1, May 2012, pp. 39-49.
WWW Link. 1204
BibRef

Aja-Fernandez, S.[Santiago], Vegas-Sanchez-Ferrero, G.[Gonzalo], Martin-Fernandez, M.[Marcos], Alberola-Lopez, C.[Carlos],
Automatic noise estimation in images using local statistics. Additive and multiplicative cases,
IVC(27), No. 6, 4 May 2009, pp. 756-770.
Elsevier DOI 0904
Noise estimation; Mode; Restoration; Gaussian noise; Local statistics BibRef

Steidl, G., Teuber, T.,
Removing Multiplicative Noise by Douglas-Rachford Splitting Methods,
JMIV(36), No. 2, February 2010, pp. xx-yy.
Springer DOI 1002
BibRef

Setzer, S.[Simon], Steidl, G., Teuber, T.,
Deblurring Poissonian images by split Bregman techniques,
JVCIR(21), No. 3, April 2010, pp. 193-199.
Elsevier DOI 1003
Deblurring; Poisson noise; I-divergence; Kullback-Leibler divergence; TV; Alternating split Bregman algorithm; Douglas-Rachford splitting BibRef

Bioucas-Dias, J.M., Figueiredo, M.A.T.,
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization,
IP(19), No. 7, July 2010, pp. 1720-1730.
IEEE DOI 1007
BibRef

Afonso, M.V., Bioucas-Dias, J.M., Figueiredo, M.A.T.,
Fast Image Recovery Using Variable Splitting and Constrained Optimization,
IP(19), No. 9, September 2010, pp. 2345-2356.
IEEE DOI 1008
BibRef

Teodoro, A.M., Bioucas-Dias, J.M., Figueiredo, M.A.T.,
A Convergent Image Fusion Algorithm Using Scene-Adapted Gaussian-Mixture-Based Denoising,
IP(28), No. 1, January 2019, pp. 451-463.
IEEE DOI 1810
BibRef
Earlier:
Image restoration and reconstruction using variable splitting and class-adapted image priors,
ICIP16(3518-3522)
IEEE DOI 1610
Convex functions, Noise reduction, Convergence, Noise measurement, Image fusion, Linear programming, Inverse problems, Plug-and-play. Gaussian mixture model BibRef

Afonso, M.V., Bioucas-Dias, J.M.[Jose M.], Figueiredo, M.A.T.[Mario A. T.],
An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems,
IP(20), No. 3, March 2011, pp. 681-695.
IEEE DOI 1103
BibRef

Figueiredo, M.A.T.[Mario A. T.], Bioucas-Dias, J.M.[Jose M.],
Restoration of Poissonian Images Using Alternating Direction Optimization,
IP(19), No. 12, December 2010, pp. 3133-3145.
IEEE DOI 1011
BibRef
And:
Frame-based deconvolution of Poissonian images using alternating direction optimization,
ICIP10(3549-3552).
IEEE DOI 1009
BibRef

Rodrigues, I.[Isabel], Sanches, J.M.[Joao M.],
Fluorescence microscopy imaging denoising with log-Euclidean priors and photobleaching compensation,
ICIP09(809-812).
IEEE DOI 0911
BibRef

Rodrigues, I.[Isabel], Sanches, J.M.[Joao M.], Bioucas-Dias, J.M.[Jose M.],
Denoising of medical images corrupted by Poisson noise,
ICIP08(1756-1759).
IEEE DOI 0810

See also Medical Image Noise Reduction Using the Sylvester-Lyapunov Equation. BibRef

Li, F.[Fang], Ng, M.K.[Michael K.], Shen, C.M.[Chao-Min],
Multiplicative Noise Removal With Spatially Varying Regularization Parameters,
SIIMS(3), No. 1, 2010, pp. 1-20.
DOI Link 1002
multiplicative noise; total variation; textures; spatially varying regularization parameters BibRef

Fang, F.M.[Fa-Ming], Li, F.[Fang], Yang, X.M.[Xiao-Mei], Shen, C.M.[Chao-Min], Zhang, G.X.[Gui-Xu],
Single image dehazing and denoising with variational method,
IASP10(219-222).
IEEE DOI 1004
BibRef

Shi, J.N.[Jia-Ning], Osher, S.J.[Stanley J.],
A Nonlinear Inverse Scale Space Method For A Convex Multiplicative Noise Model,
SIIMS(1), No. 3, 2008, pp. 294-321. inverse scale space; total variation; multiplicative noise; denoising; Bregman distance
DOI Link BibRef 0800

Durand, S.[Sylvain], Fadili, J.[Jalal], Nikolova, M.[Mila],
Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients,
JMIV(36), No. 3, March 2010, pp. xx-yy.
Springer DOI 1003
BibRef
Earlier:
Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients,
SSVM09(282-294).
Springer DOI 0906
BibRef

Chen, D.Q., Cheng, L.Z.,
Spatially Adapted Total Variation Model to Remove Multiplicative Noise,
IP(21), No. 4, April 2012, pp. 1650-1662.
IEEE DOI 1204
BibRef

Shi, B.[Baoli], Huang, L.H.[Li-Hong], Pang, Z.F.[Zhi-Feng],
Fast algorithm for multiplicative noise removal,
JVCIR(23), No. 1, January 2012, pp. 126-133.
Elsevier DOI 1112
Multiplicative noise; Anisotropic total variation; Maximum a posteriori; Convex function; Alternating minimization algorithm; Proximal operator; Gamma distribution; Newton method BibRef

Yun, S., Woo, H.,
A New Multiplicative Denoising Variational Model Based on m th Root Transformation,
IP(21), No. 5, May 2012, pp. 2523-2533.
IEEE DOI 1204
BibRef

Chan, R.H., Ma, J.,
A Multiplicative Iterative Algorithm for Box-Constrained Penalized Likelihood Image Restoration,
IP(21), No. 7, July 2012, pp. 3168-3181.
IEEE DOI 1206
BibRef

Huang, Y.M., Moisan, L., Ng, M.K., Zeng, T.,
Multiplicative Noise Removal via a Learned Dictionary,
IP(21), No. 11, November 2012, pp. 4534-4543.
IEEE DOI 1210
BibRef

Xiao, Y.[Yu], Zeng, T.Y.[Tie-Yong],
Poisson noise removal via learned dictionary,
ICIP10(1177-1180).
IEEE DOI 1009
BibRef

Liu, J.[Jun], Huang, T.Z.[Ting-Zhu], Xu, Z.B.[Zong-Ben], Lv, X.G.[Xiao-Guang],
High-order total variation-based multiplicative noise removal with spatially adapted parameter selection,
JOSA-A(30), No. 10, October 2013, pp. 1956-1966.
DOI Link 1310
BibRef

Kang, M.J.[Myung-Joo], Yun, S.W.[Sang-Woon], Woo, H.[Hyenkyun],
Two-Level Convex Relaxed Variational Model for Multiplicative Denoising,
SIIMS(6), No. 2, 2013, pp. 875-903.
DOI Link 1307
BibRef

Dong, Y.Q., Zeng, T.Y.,
A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise,
SIIMS(6), No. 3, 2013, pp. 1598-1625.
DOI Link 1310
BibRef

Sciacchitano, F.[Federica], Dong, Y.Q.[Yi-Qiu], Zeng, T.Y.[Tie-Yong],
Variational Approach for Restoring Blurred Images with Cauchy Noise,
SIIMS(8), No. 3, 2015, pp. 1894-1922.
DOI Link 1511
BibRef

Chen, L.Y.[Li-Yuan], Zeng, T.Y.[Tie-Yong],
A Convex Variational Model for Restoring Blurred Images with Large Rician Noise,
JMIV(53), No. 1, September 2015, pp. 92-111.
WWW Link. 1505
BibRef

Hao, Y.[Yan], Xu, J.L.[Jian-Lou],
An effective dual method for multiplicative noise removal,
JVCIR(25), No. 2, 2014, pp. 306-312.
Elsevier DOI 1402
Image denoising BibRef

Wang, F., Zhao, X.L., Ng, M.K.,
Multiplicative Noise and Blur Removal by Framelet Decomposition and l_1 -Based L-Curve Method,
IP(25), No. 9, September 2016, pp. 4222-4232.
IEEE DOI 1609
convex programming BibRef

Zhao, X.L., Wang, F., Ng, M.K.,
A New Convex Optimization Model for Multiplicative Noise and Blur Removal,
SIIMS(7), No. 1, 2014, pp. 456-475.
DOI Link 1404
BibRef

Chan, R., Yang, H., Zeng, T.,
A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise,
SIIMS(7), No. 1, 2014, pp. 98-127.
DOI Link 1404
BibRef

Chen, Y.J.[Yun-Jin], Feng, W.[Wensen], Ranftl, R., Qiao, H.[Hong], Pock, T.[Thomas],
A Higher-Order MRF Based Variational Model for Multiplicative Noise Reduction,
SPLetters(21), No. 11, November 2014, pp. 1370-1374.
IEEE DOI 1408
Markov processes BibRef

Feng, W.[Wensen], Qiao, H.[Hong], Chen, Y.J.[Yun-Jin],
Poisson Noise Reduction with Higher-Order Natural Image Prior Model,
SIIMS(9), No. 3, 2016, pp. 1502-1524.
DOI Link 1610
BibRef

Feng, W.[Wensen], Chen, Y.J.[Yun-Jin],
Speckle Reduction with Trained Nonlinear Diffusion Filtering,
JMIV(58), No. 1, May 2017, pp. 162-178.
WWW Link. 1704
BibRef

Kang, M.M.[Myeong-Min], Kang, M.J.[Myung-Joo], Jung, M.Y.[Mi-Youn],
Nonconvex higher-order regularization based Rician noise removal with spatially adaptive parameters,
JVCIR(32), No. 1, 2015, pp. 180-193.
Elsevier DOI 1511
Rician noise removal BibRef

Sharif, M.[Muhammad], Hussain, A.[Ayyaz], Jaffar, M.A.[Muhammad Arfan], Choi, T.S.[Tae-Sun],
Fuzzy-based hybrid filter for Rician noise removal,
SIViP(10), No. 1, February 2016, pp. 215-224.
Springer DOI 1601
BibRef

Chen, L.X.[Li-Xia], Liu, X.J.[Xu-Jiao], Wang, X.W.[Xue-Wen], Zhu, P.F.[Ping-Fang],
Multiplicative Noise Removal via Nonlocal Similarity-Based Sparse Representation,
JMIV(54), No. 2, February 2016, pp. 199-215.
Springer DOI 1602
BibRef

Liu, M.[Min], Fan, Q.B.[Qi-Bin],
A modified convex variational model for multiplicative noise removal,
JVCIR(36), No. 1, 2016, pp. 187-198.
Elsevier DOI 1603
Multiplicative noise BibRef

Ullah, A.[Asmat], Chen, W.[Wen], Sun, H.G.[Hong-Guang], Khan, M.A.[Mushtaq Ahmad],
A modified multi-grid algorithm for a novel variational model to remove multiplicative noise,
JVCIR(40, Part B), No. 1, 2016, pp. 485-501.
Elsevier DOI 1610
Maximum a posteriori (MAP) BibRef

Escande, P.[Paul], Weiss, P.[Pierre], Zhang, W.X.[Wen-Xing],
A Variational Model for Multiplicative Structured Noise Removal,
JMIV(57), No. 1, January 2017, pp. 43-55.
Springer DOI 1701
BibRef

de los Reyes, J.C., Schönlieb, C.B., Valkonen, T.,
Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models,
JMIV(57), No. 1, January 2017, pp. 1-25.
Springer DOI 1701
BibRef

Karami, A.[Azam], Tafakori, L.[Laleh],
Image denoising using generalised Cauchy filter,
IET-IPR(11), No. 9, September 2017, pp. 767-776.
DOI Link 1709
BibRef

Xu, X.L.[Xin-Li], Yu, T.[Teng], Xu, X.M.[Xin-Mei], Hou, G.J.[Guo-Jia], Liu, R.W.[Ryan Wen], Pan, H.Z.[Hui-Zhu],
Variational total curvature model for multiplicative noise removal,
IET-CV(12), No. 4, June 2018, pp. 542-552.
DOI Link 1805
BibRef

Chen, L.X.[Li-Xia], Zhu, P.F.[Ping-Fang], Wang, X.W.[Xue-Wen],
Low-rank constraint with sparse representation for image restoration under multiplicative noise,
SIViP(13), No. 1, February 2019, pp. 179-187.
WWW Link. 1901
BibRef

Yao, W., Guo, Z., Sun, J., Wu, B., Gao, H.,
Multiplicative Noise Removal for Texture Images Based on Adaptive Anisotropic Fractional Diffusion Equations,
SIIMS(12), No. 2, 2019, pp. 839-873.
DOI Link 1907
BibRef

Ren, F.[Fuquan], Zhou, R.R.[Roberta Rui],
Optimization model for multiplicative noise and blur removal based on Gaussian curvature regularization,
JOSA-A(35), No. 5, May 2018, pp. 798-812.
DOI Link 1912
Image reconstruction-restoration, Inverse problems, Noise in imaging systems, Fourier transforms, Synthetic aperture radar BibRef

Liu, P.F.[Peng-Fei],
Hybrid higher-order total variation model for multiplicative noise removal,
IET-IPR(14), No. 5, 17 April 2020, pp. 862-873.
DOI Link 2004
BibRef

Liu, X.X.[Xiao-Xia], Lu, J.[Jian], Shen, L.X.[Li-Xin], Xu, C.[Chen], Xu, Y.[Yuesheng],
Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm,
SIIMS(13), No. 3, 2020, pp. 1595-1629.
DOI Link 2010
BibRef

Yang, H.[Huan], Li, H.W.[Hong-Wei], Duan, Y.P.[Yu-Ping],
Adaptive trainable non-linear reaction diffusion for Rician noise removal,
IET-IPR(14), No. 14, December 2020, pp. 3547-3561.
DOI Link 2012
BibRef

Liu, Z.F.[Zhi-Fang], Chang, H.[Huibin], Duan, Y.P.[Yu-Ping],
Variational Rician Noise Removal via Splitting on Spheres,
SIIMS(15), No. 2, 2022, pp. 521-549.
DOI Link 2205
BibRef

Wu, T.T.[Ting-Ting], Gu, X.Y.[Xiao-Yu], Li, Z.[Zeyu], Li, Z.[Zhi], Niu, J.W.[Jian-Wei], Zeng, T.Y.[Tie-Yong],
Efficient Boosted DC Algorithm for Nonconvex Image Restoration with Rician Noise,
SIIMS(15), No. 2, 2022, pp. 424-454.
DOI Link 2205
BibRef


Jetta, M.[Mahipal], Singh, U.[Utkarsh], Yinukula, P.[Padmaja],
On Trainable Multiplicative Noise Removal Models,
SSVM23(81-93).
Springer DOI 2307
BibRef

Seelamantula, C.S.[Chandra Sekhar], Blu, T.[Thierry],
Image denoising in multiplicative noise,
ICIP15(1528-1532)
IEEE DOI 1512
Gamma distribution BibRef

Kitchener, M.A.[Matthew Andrew], Bouzerdoum, A.[Abdesselam], Phung, S.L.[Son Lam],
Adaptive regularization for multiple image restoration using an extended Total Variations approach,
ICIP11(697-700).
IEEE DOI 1201
BibRef

Aubert, G.[Gilles], Aujol, J.F.[Jean-François],
A Nonconvex Model to Remove Multiplicative Noise,
SSVM07(68-79).
Springer DOI 0705
BibRef

Ponomarenko, N.N.[Nikolay N.], Lukin, V.V.[Vladimir V.], Astola, J.T.[Jaakko T.], Egiazarian, K.O.[Karen O.],
Non-local Sigma Filter,
CIAP15(II:483-493).
Springer DOI 1511

See also Automatic Design of Locally Adaptive Filters for Pre-processing of Images Subject to Further Interpretation. BibRef

Ponomarenko, N.N.[Nikolay N.], Lukin, V.V.[Vladimir V.], Egiazarian, K.O.[Karen O.], Astola, J.T.[Jaakko T.], Vozel, B.[Benoit], Chehdi, K.[Kacem],
Hybrid Sigma Filter for Processing Images Corrupted by Multiplicative Noise,
ACIVS06(46-54).
Springer DOI 0609
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Quality Evaluation, Visual Quality, Quality Assessment, and Imaging Models .


Last update:Mar 16, 2024 at 20:36:19