5.3.9.1 Noise Removal, Impulse Noise, Salt and Pepper

Chapter Contents (Back)
Noise Removal. Impulse Noise. Salt and Pepper Noise. Denoising.
See also Median Filtering.

Yasuoka, Y., Haralick, R.M.,
Peak Noise Removal by a Facet Model,
PR(16), No. 1, 1983, pp. 23-29.
Elsevier DOI BibRef 8300

Rushby, R.J.[Robert J.], Parmar, Y.S.[Yashvant S.],
Method and apparatus for removing erroneous elements from digital images,
US_Patent4,389,677, Jun 21, 1983
WWW Link. BibRef 8306

Nomura, Y., and Haruse, H.,
Reduction of Obscuration Noise Using Multiple Images,
PAMI(10), No. 2, March 1988, pp. 267-270.
IEEE DOI Noise that replaces rather than modifies. Multiple images of a stationary scene. Test case: scene behind air bubbles in a water tank. BibRef 8803

Combettes, P.L., Trussell, H.J.,
Methods of Digital Restoration of Signals Degraded by a Stochastic Impulse Response,
ASSP(37), No. 3, March 1989, pp. 383-401. BibRef 8903

Patel, C.B.[Chandrakant B.], Weckenbrock, H.J.[Hermann J.], Wedam, W.F.[Werner F.], Altman, T.N.[Ted N.],
Estimation of noise using burst gate response to video signal,
US_Patent5,294,979, Mar 15, 1994
WWW Link. BibRef 9403

Kong, H., Guan, L.,
A Neural Network Adaptive Filter for the Removal of Impulse Noise in Digital Images,
NeurNet(9), No. 3, April 1996, pp. 373-378. 9605
BibRef

Guan, L., Kong, H.S.,
Adaptive Impulsive Noise Removal in TV Picture Transmission,
RealTimeImg(4), No. 2, April 1998, pp. 113-123. 9806
BibRef

Abreu, E., Lightstone, M., Mitra, S.K., Arakawa, K.,
A New Efficient Approach for the Removal of Impulse Noise from Highly Corrupted Images,
IP(5), No. 6, June 1996, pp. 1012-1025.
IEEE DOI 9607
BibRef

Russo, F., Ramponi, G.,
A Fuzzy Filter for Images Corrupted by Impulse Noise,
SPLetters(3), No. 6, June 1996, pp. 168-170.
IEEE Top Reference. 9607
BibRef

Russo, F.,
Fuzzy Processing of Image Data Using Fire Filters,
JIFS(5), No. 4, 1997, pp. 361-366. 9809
BibRef
Earlier:
Removal of impulse noise using a FIRE filter,
ICIP96(II: 975-978).
IEEE DOI 9610
BibRef
Earlier:
An image enhancement technique based on the FIRE operator,
ICIP95(I: 155-158).
IEEE DOI 9510
BibRef

Russo, F.[Fabrizio],
Hybrid neuro-fuzzy filter for impulse noise removal,
PR(32), No. 11, November 1999, pp. 1843-1855.
Elsevier DOI BibRef 9911
Earlier:
Nonlinear Filtering of Noisy Images Using Neuro-Fuzzy Operators,
ICIP97(III: 412-415).
IEEE DOI BibRef

Kundu, A., Mitra, S.K., Vaidyanathan, P.P.,
Application of Two-Dimensional Generalized Mean Filtering for Removal of Impulse Noises from Images,
ASSP(32), 1984, pp. 600-609. BibRef 8400

Wang, Z.[Zhou], Zhang, D.,
Restoration of Impulse Noise-Corrupted Images Using Long-Range Correlation,
SPLetters(5), No. 1, January 1998, pp. 4-7.
IEEE Top Reference. 9802
BibRef

Kong, H.S., Guan, L.,
Self-Organizing Tree Map for Eliminating Impulse Noise with Random Intensity Distributions,
JEI(7), No. 1, January 1998, pp. 36-44. 9807
BibRef

Xu, Y., Lai, E.M.K.,
Restoration of Images Contaminated by Mixed Gaussian and Impulse Noise Using a Recursive Minimum-Maximum Method,
VISP(145), No. 4, August 1998, pp. 264-270. 9810
BibRef

Overall, G.S.[Gary Scott], Wright, P.B.[Phillip Byron],
Image improvement after facsimile reception,
US_Patent5,940,190, Aug 17, 1999
WWW Link. BibRef 9908

Windyga, P.S.,
Fast Impulsive Noise Removal,
IP(10), No. 1, January 2001, pp. 173-179.
IEEE DOI 0101
BibRef

Marshall, Jr., T.G.,
Image filtering with orthogonal projectors for burst error control,
CirSysVideo(1), No. 3, September 1991, pp. 269-278.
IEEE Top Reference. 0206
BibRef

Struyf, A.[Anja], Rousseeuw, P.J.[Peter J.],
High-dimensional computation of the deepest location,
CSDA(34), No. 4, 28 October 2000, pp. 415-426.
Elsevier DOI 1307
BibRef

Pok, G.[Gouchol], Liu, J.C.[Jyh-Charn], Nair, A.S.,
Selective removal of impulse noise based on homogeneity level information,
IP(12), No. 1, January 2003, pp. 85-92.
IEEE DOI 0301
BibRef

Koivisto, P.[Pertti], Astola, J.T.[Jaakko T.], Lukin, V.V.[Vladimir V.], Melnik, V.P.[Vladimir P.], Tsymbal, O.[Oleg],
Removing Impulse Bursts from Images by Training-Based Filtering,
JASP(2003), No. 3, March 2003, pp. 223.
WWW Link. 0304
BibRef

Jiang, X.D.,
Image detail-preserving filter for impulsive noise attenuation,
VISP(150), No. 3, June 2003, pp. 179-185.
IEEE Abstract. 0308
BibRef

Nikolova, M.[Mila],
A Variational Approach to Remove Outliers and Impulse Noise,
JMIV(20), No. 1-2, January-March 2004, pp. 99-120.
DOI Link 0403
BibRef
Earlier:
Efficient Removing of Impulsive Noise Based on an L1-L2 Cost-Function,
ICIP03(I: 121-124).
IEEE DOI 0312
BibRef

Chan, R.H., Hu, C.[Chen], Nikolova, M.,
An iterative procedure for removing random-valued impulse noise,
SPLetters(11), No. 12, December 2004, pp. 921-924.
IEEE Abstract. 0412
BibRef

Chan, R.H., Ho, C.W.[Chung-Wa], Nikolova, M.,
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization,
IP(14), No. 10, October 2005, pp. 1479-1485.
IEEE DOI 0510
BibRef

Aizenberg, I., Butakoff, C.,
Effective impulse detector based on rank-order criteria,
SPLetters(11), No. 3, March 2004, pp. 363-366.
IEEE Abstract. 0404
BibRef

Aizenberg, I., Astola, J.T., Butakoff, C., Egiazarian, K.O., Paliy, D.,
Effective detection and elimination of impulsive noise with a minimal image smoothing,
ICIP03(III: 357-360).
IEEE DOI 0312
BibRef

Aizenberg, I., Butakoff, C., Paliy, D.,
Impulsive noise removal using threshold Boolean filtering based on the impulse detecting functions,
SPLetters(12), No. 1, January 2005, pp. 63-66.
IEEE Abstract. 0501
BibRef

Aizenberg, I.[Igor], Butakoff, C.[Constantine],
A windowed Gaussian notch filter for quasi-periodic noise removal,
IVC(26), No. 10, 1 October 2008, pp. 1347-1353.
Elsevier DOI 0804
Nonlinear filtering; Spectrum filtering; Fourier transform; Periodic noise BibRef

Crnojevic, V.S., Senk, V., Trpovski, Z.,
Advanced Impulse Detection Based on Pixel-Wise MAD,
SPLetters(11), No. 7, July 2004, pp. 589-592.
IEEE Abstract. 0407
MAD: median of the absolute deviations from the median. BibRef

Xu, H.X.[Hai-Xiang], Zhu, G.X.[Guang-Xi], Peng, H.Y.[Hao-Yu], Wang, D.S.[De-Sheng],
Adaptive fuzzy switching filter for images corrupted by impulse noise,
PRL(25), No. 15, November 2004, pp. 1657-1663.
Elsevier DOI 0411
BibRef

Alajlan, N.[Naif], Kamel, M.S.[Mohamed S.], Jernigan, E.[Ed],
Detail preserving impulsive noise removal,
SP:IC(19), No. 10, December 2004, pp. 993-1003.
Elsevier DOI 0501
BibRef

Lukac, R.[Rastislav], Fischer, V.[Viktor], Motyl, G.[Guy], Drutarovsky, M.[Milos],
Adaptive video filtering framework,
IJIST(14), No. 6, 2004, pp. 223-237.
DOI Link 0412
BibRef

Chuah, T.C.,
Turbo equalisation in non-Gaussian impulsive noise,
VISP(152), No. 1, February 2005, pp. 52-60.
IEEE Abstract. 0501
BibRef

Liu, Z.J.[Zheng-Jun], Wang, C.Y.[Chang-Yao], Liu, A.X.[Ai-Xia], Xiao, X.M.[Xiang-Ming],
Statistical Ratio Rank Ordered Differences Filter for SeaWiFS Impulse Noise Removal,
PhEngRS(71), No. 1, January 2005, pp. 89-96. The SRROD Filter for SeaWiFS Impulse Noise Removal is described.
WWW Link. 0509
BibRef

Garnett, R., Huegerich, T., Chui, C., He, W.,
A Universal Noise Removal Algorithm With an Impulse Detector,
IP(14), No. 11, November 2005, pp. 1747-1754.
IEEE DOI 0510
BibRef

Ma, Z.H.[Zhong-Hua], Feng, D.D.[David Dagan], Wu, H.R.[Hong Ren],
A neighborhood evaluated adaptive vector filter for suppression of impulse noise in color images,
RealTimeImg(11), No. 5-6, October-December 2005, pp. 403-416.
Elsevier DOI 0510
BibRef

Ma, Z.H.[Zhong-Hua], Wu, H.R.[Hong Ren], Feng, D.D.[David Dagan],
Fuzzy vector partition filtering technique for color image restoration,
CVIU(107), No. 1-2, July-August 2007, pp. 26-37.
Elsevier DOI 0706
Color image restoration; Adaptive vector filter; Vector partition filtering; Fuzzy ranking technique BibRef

Morillas, S.[Samuel], Gregori, V.[Valentín], Peris-Fajarnés, G.[Guillermo], Latorre, P.[Pedro],
A fast impulsive noise color image filter using fuzzy metrics,
RealTimeImg(11), No. 5-6, October-December 2005, pp. 417-428.
Elsevier DOI 0510
BibRef
Earlier:
A New Vector Median Filter Based on Fuzzy Metrics,
ICIAR05(81-90).
Springer DOI 0509
BibRef

Morillas, S.[Samuel], Gregori, V.[Valentin], Peris-Fajarnes, G.[Guillermo],
Isolating impulsive noise pixels in color images by peer group techniques,
CVIU(110), No. 1, April 2008, pp. 102-116.
Elsevier DOI 0804
Color image filter; Fuzzy metric; Peer group; Switching filtering; Vector median filter BibRef

Camarena, J.G.[Joan-Gerard], Gregori, V.[Valentin], Morillas, S.[Samuel], Sapena, A.[Almanzor],
Fast detection and removal of impulsive noise using peer groups and fuzzy metrics,
JVCIR(19), No. 1, January 2008, pp. 20-29.
Elsevier DOI 0711
BibRef
Earlier: A3, A2, A4, Only:
Fuzzy Bilateral Filtering for Color Images,
ICIAR06(I: 138-145).
Springer DOI 0610
Color image filter; Fuzzy metric; Non-linear vector filter; Peer group; Vector median filter BibRef

Camarena, J.G.[Joan-Gerard], Gregori, V.[Valentin], Morillas, S.[Samuel], Sapena, A.[Almanzor],
Some improvements for image filtering using peer group techniques,
IVC(28), No. 1, Januray 2010, pp. 188-201.
Elsevier DOI 1001
Adaptive filter; Color image denoising; Peer group filter; Switching filter; Vector filter BibRef

Camarena, J.G.[Joan-Gerard], Gregori, V.[Valentín], Morillas, S.[Samuel], Peris-Fajarnés, G.[Guillermo],
New Method for Fast Detection and Removal of Impulsive Noise Using Fuzzy Metrics,
ICIAR06(I: 359-369).
Springer DOI 0610
BibRef

Yuksel, M.E.,
A hybrid neuro-fuzzy filter for edge preserving restoration of images corrupted by impulse noise,
IP(15), No. 4, April 2006, pp. 928-936.
IEEE DOI 0604
BibRef

Schulte, S.[Stefan], Nachtegael, M.[Mike], de Witte, V.[Valérie], van der Weken, D.[Dietrich], Kerre, E.E.[Etienne E.],
A Fuzzy Impulse Noise Detection and Reduction Method,
IP(15), No. 5, May 2006, pp. 1153-1162.
IEEE DOI 0605
BibRef

Schulte, S.[Stefan], de Witte, V.[Valerie], Nachtegael, M.[Mike], van der Weken, D.[Dietrich], Kerre, E.E.[Etienne E.],
Histogram-based fuzzy colour filter for image restoration,
IVC(25), No. 9, 1 September 2007, pp. 1377-1390.
Elsevier DOI 0707
Fuzzy filter; Histogram; Colour filter; Impulse noise; Image restoration BibRef

Nachtegael, M., van der Weken, D., de Witte, V., Schulte, S., Melange, T., Kerre, E.E.,
Color Image Retrieval using Fuzzy Similarity Measures and Fuzzy Partitions,
ICIP07(VI: 13-16).
IEEE DOI 0709
BibRef

Schulte, S., Morillas, S., Gregori, V., Kerre, E.E.,
A New Fuzzy Color Correlated Impulse Noise Reduction Method,
IP(16), No. 10, October 2007, pp. 2565-2575.
IEEE DOI 0711
BibRef

Camarena, J.G.[Joan-Gerard], Gregori, V.[Valentin], Morillas, S.[Samuel], Sapena, A.[Almanzor],
Two-step fuzzy logic-based method for impulse noise detection in colour images,
PRL(31), No. 13, 1 October 2010, pp. 1842-1849.
Elsevier DOI 1003
Colour image filter; Fuzzy logic; Fuzzy metric; Impulse noise BibRef

Gregori, V.[Valentín], Morillas, S.[Samuel], Roig, B.[Bernardino], Sapena, A.[Almanzor],
Fuzzy averaging filter for impulse noise reduction in colour images with a correction step,
JVCIR(55), 2018, pp. 518-528.
Elsevier DOI 1809
Color image filter, Correction step, Fuzzy filter, Impulse noise BibRef

Morillas, S.[Samuel], Schulte, S.[Stefan], Kerre, E.E.[Etienne E.], Peris-Fajarnés, G.[Guillermo],
A New Fuzzy Impulse Noise Detection Method for Colour Images,
SCIA07(492-501).
Springer DOI 0706
BibRef

Schulte, S.[Stefan], de Witte, V.[Valérie], Nachtegael, M.[Mike], Mélange, T.[Tom], Kerre, E.E.[Etienne E.],
A New Fuzzy Additive Noise Reduction Method,
ICIAR07(12-23).
Springer DOI 0708
BibRef

Schulte, S., de Witte, V., Nachtegael, M., van der Weken, D., Kerre, E.E.,
Fuzzy Two-Step Filter for Impulse Noise Reduction From Color Images,
IP(15), No. 11, November 2006, pp. 3567-3578.
IEEE DOI 0610
BibRef
And:
A New Fuzzy Filter for the Reduction of Randomly Valued Impulse Noise,
ICIP06(1809-1812).
IEEE DOI 0610
BibRef
Earlier:
A New Fuzzy Multi-channel Filter for the Reduction of Impulse Noise,
IbPRIA05(I:368).
Springer DOI 0509
BibRef

Mélange, T.[Tom], Nachtegael, M.[Mike], Kerre, E.E.[Etienne E.],
Fuzzy Random Impulse Noise Removal From Color Image Sequences,
IP(20), No. 4, April 2011, pp. 959-970.
IEEE DOI 1103
BibRef
Earlier: A2, A1, A3:
The Possibilities of Fuzzy Logic in Image Processing,
PReMI07(198-208).
Springer DOI 0712
BibRef

Melange, T.[Tom], Nachtegael, M.[Mike], Schulte, S.[Stefan], Kerre, E.E.[Etienne E.],
A fuzzy filter for the removal of random impulse noise in image sequences,
IVC(29), No. 6, May 2011, pp. 407-419.
Elsevier DOI 1104
Video; Denoising; Impulse noise; Fuzzy sets BibRef

Nachtegael, M.[Mike], Schulte, S.[Stefan], de Witte, V.[Valerie], Mélange, T.[Tom], Kerre, E.E.[Etienne E.],
Image Similarity: From Fuzzy Sets to Color Image Applications,
Visual07(26-37).
Springer DOI 0706
BibRef

Schulte, S.[Stefan], de Witte, V.[Valrie], Kerre, E.E.[Etienne E.],
A Fuzzy Noise Reduction Method for Color Images,
IP(16), No. 5, May 2007, pp. 1425-1436.
IEEE DOI 0704
BibRef

González-Jaime, L.[Luis], Nachtegeal, M.[Mike], Kerre, E.E.[Etienne E.], Vegas-Sánchez-Ferrero, G.[Gonzalo],
Parametric Image Restoration Using Consensus: An Application to Nonstationary Noise Filtering,
IbPRIA13(358-365).
Springer DOI 1307
BibRef

Ze-Feng, D., Zhou-Ping, Y., You-Lun, X.,
High Probability Impulse Noise-Removing Algorithm Based on Mathematical Morphology,
SPLetters(14), No. 1, January 2007, pp. 31-34.
IEEE DOI 0701
BibRef

Srinivasan, K.S., Ebenezer, D.,
A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises,
SPLetters(14), No. 3, March 2007, pp. 189-192.
IEEE DOI 0703
BibRef

Civicioglu, P.,
Using Uncorrupted Neighborhoods of the Pixels for Impulsive Noise Suppression With ANFIS,
IP(16), No. 3, March 2007, pp. 759-773.
IEEE DOI 0703
BibRef

Zhao, W., Pope, A.,
Image Restoration Under Significant Additive Noise,
SPLetters(14), No. 6, June 2007, pp. 401-404.
IEEE DOI 0706
BibRef

Jin, L., Li, D.,
An Efficient Color-Impulse Detector and its Application to Color Images,
SPLetters(14), No. 6, June 2007, pp. 397-400.
IEEE DOI 0706
BibRef

Djurovic, I.[Igor], Lukin, V.V.[Vladimir V.],
Robust DFT-based filtering of pulse-like FM signals corrupted by impulsive noise,
SIViP(1), No. 1, April 2007, pp. 39-51.
Springer DOI 0706
BibRef

Lin, T.C.[Tzu-Chao],
Partition belief median filter based on Dempster-Shafer theory for image processing,
PR(41), No. 1, January 2008, pp. 139-151.
Elsevier DOI 0710
Impulsive noise; Evidence theory; Recursive filtering; Least mean square BibRef

Cai, J.F.[Jian-Feng], Chan, R.H.[Raymond H.], di Fiore, C.[Carmine],
Minimization of a Detail-Preserving Regularization Functional for Impulse Noise Removal,
JMIV(29), No. 1, Septmeber 2007, pp. 79-91.
Springer DOI 0709
BibRef

Petrovic, N.I.[Nemanja I.], Crnojevic, V.S.[Vladimir S.],
Universal Impulse Noise Filter Based on Genetic Programming,
IP(17), No. 7, July 2008, pp. 1109-1120.
IEEE DOI 0806
BibRef
Earlier:
Evolutionary Tree-Structured Filter for Impulse Noise Removal,
ACIVS06(103-113).
Springer DOI 0609
BibRef
Earlier: A2, Only:
Impulse Noise Filter with Adaptive Mad-Based Threshold,
ICIP05(III: 337-340).
IEEE DOI 0512
BibRef

Obradovic, R.[Radovan], Janev, M.[Marko], Antic, B.[Borislav], Crnojevica, V.S.[Vladimir S.], Petrovic, N.I.[Nemanja I.],
Robust sparse image denoising,
ICIP11(2569-2572).
IEEE DOI 1201
BibRef

Yu, H., Zhao, L., Wang, H.,
An Efficient Procedure for Removing Random-Valued Impulse Noise in Images,
SPLetters(15), No. 1, 2008, pp. 922-925.
IEEE DOI 0901
BibRef

Chen, S.S.[Shou-Shui], Yang, X.[Xin], Cao, G.,
Impulse noise suppression with an augmentation of ordered difference noise detector and an adaptive variational method,
PRL(30), No. 4, 1 March 2009, pp. 460-467.
Elsevier DOI 0903
BibRef
Earlier: A1, A2, Only:
A Variational Method with a Noise Detector for Impulse Noise Removal,
SSVM07(442-450).
Springer DOI 0705
Image denoising; Impulse noise reduction; Noise detection; Adaptive variational method BibRef

Zhang, X., Xiong, Y.,
Impulse Noise Removal Using Directional Difference Based Noise Detector and Adaptive Weighted Mean Filter,
SPLetters(16), No. 4, April 2009, pp. 295-298.
IEEE DOI 0903
BibRef

Wang, S.S.[Shuenn-Shyang], Wu, C.H.[Cheng-Hao],
A new impulse detection and filtering method for removal of wide range impulse noises,
PR(42), No. 9, September 2009, pp. 2194-2202.
Elsevier DOI 0905
Image processing; Impulse noise; Image filtering BibRef

Morillas, S., Gregori, V., Hervas, A.,
Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images,
IP(18), No. 7, July 2009, pp. 1452-1466.
IEEE DOI 0906
BibRef

Xu, Z., Wu, H.R., Qiu, B., Yu, X.,
Geometric Features-Based Filtering for Suppression of Impulse Noise in Color Images,
IP(18), No. 8, August 2009, pp. 1742-1759.
IEEE DOI 0907
BibRef

Ghanekar, U., Singh, A.K., Pandey, R.,
A Contrast Enhancement-Based Filter for Removal of Random Valued Impulse Noise,
SPLetters(17), No. 1, January 2010, pp. 47-50.
IEEE DOI 0911
BibRef

Kaliraj, G., Baskar, S.,
An efficient approach for the removal of impulse noise from the corrupted image using neural network based impulse detector,
IVC(28), No. 3, March 2010, pp. 458-466.
Elsevier DOI 1001
Neural network; Image filtering; Impulse detector; Impulse noise BibRef

Lopez-Rubio, E.[Ezequiel],
Restoration of images corrupted by Gaussian and uniform impulsive noise,
PR(43), No. 5, May 2010, pp. 1835-1846.
Elsevier DOI 1003
Image restoration; Gaussian noise; Uniform impulsive noise; Kernel regression; Probabilistic mixture models BibRef

Zibulevsky, M.[Michael], Elad, M.[Michael],
L1-L2 Optimization in Signal and Image Processing,
SPMag(27), No. 3, 2010, pp. 76-88.
IEEE DOI 1006
BibRef

Romano, Y.[Yaniv], Elad, M.[Michael],
Boosting of Image Denoising Algorithms,
SIIMS(8), No. 2, 2015, pp. 1187-1219.
DOI Link 1507
BibRef

Kannan, K., Kanna, B.R.[B. Rajesh], Aravindan, C.,
Root Mean Square filter for noisy images based on hyper graph model,
IVC(28), No. 9, September 2010, pp. 1329-1338.
Elsevier DOI 1007
Hypergraph; Image Neighborhood Hypergraph (INHG); Root Mean Square approximation; Impulse noise; Gaussian noise BibRef

Wu, C.C.[Chang-Cheng], Zhao, C.Y.[Chun-Yu], Chen, D.Y.[Da-Yue],
Improved Radiometric Based Method for Suppressing Impulse Noise from Corrupted Images,
IEICE(E93-D), No. 7, July 2010, pp. 1936-1943.
WWW Link. 1008
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Cai, J.F.[Jian-Feng], Chan, R.H.[Raymond H.], Nikolova, M.[Mila],
Fast Two-Phase Image Deblurring Under Impulse Noise,
JMIV(36), No. 1, January 2010, pp. xx-yy.
Springer DOI 1001
BibRef

Chan, R.H., Dong, Y.Q.[Yi-Qiu], Hintermuller, M.,
An Efficient Two-Phase L1-TV Method for Restoring Blurred Images with Impulse Noise,
IP(19), No. 7, July 2010, pp. 1731-1739.
IEEE DOI 1007
BibRef

Bhotto, M.Z.A., Antoniou, A.,
Robust Recursive Least-Squares Adaptive-Filtering Algorithm for Impulsive-Noise Environments,
SPLetters(18), No. 3, March 2011, pp. 185-188.
IEEE DOI 1102
BibRef

Esakkirajan, S., Veerakumar, T., Subramanyam, A.N., Prem-Chand, C.H.,
Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter,
SPLetters(18), No. 5, May 2011, pp. 287-290.
IEEE DOI 1103
BibRef

Xiao, Y.[Yu], Zeng, T.Y.[Tie-Yong], Yu, J.[Jian], Ng, M.K.[Michael K.],
Restoration of images corrupted by mixed Gaussian-impulse noise via l1-l0 minimization,
PR(44), No. 8, August 2011, pp. 1708-1720.
Elsevier DOI 1104
Image restoration; Gaussian noise; Impulse noise; Dictionary learning BibRef

Awad, A.S.,
Standard Deviation for Obtaining the Optimal Direction in the Removal of Impulse Noise,
SPLetters(18), No. 7, July 2011, pp. 407-410.
IEEE DOI 1101
BibRef

Wu, J.[Jian], Tang, C.[Chen],
PDE-Based Random-Valued Impulse Noise Removal Based on New Class of Controlling Functions,
IP(20), No. 9, September 2011, pp. 2428-2438.
IEEE DOI 1109
BibRef

Pham, D.S.[Duc-Son], Venkatesh, S.[Svetha],
Improved Image Recovery From Compressed Data Contaminated With Impulsive Noise,
IP(21), No. 1, January 2012, pp. 397-405.
IEEE DOI 1112
BibRef

Pham, D.S.,
Improved Impulse Noise Removal with Generalized Median Filter,
DICTA15(1-8)
IEEE DOI 1603
image denoising BibRef

Pham, D.S.[Duc-Son], Venkatesh, S.[Svetha],
Efficient Algorithms for Robust Recovery of Images From Compressed Data,
IP(22), No. 12, 2013, pp. 4724-4737.
IEEE DOI 1312
data compression BibRef

Arandjelovic, O., Pham, D.S.[Duc-Son], Venkatesh, S.[Svetha],
Two Maximum Entropy-Based Algorithms for Running Quantile Estimation in Nonstationary Data Streams,
CirSysVideo(25), No. 9, September 2015, pp. 1469-1479.
IEEE DOI 1509
Entropy BibRef

Pham, D.S.[Duc-Son], Budhaditya, S.[Saha], Phung, D.Q.[Dinh Q.], Venkatesh, S.[Svetha],
Improved subspace clustering via exploitation of spatial constraints,
CVPR12(550-557).
IEEE DOI 1208
BibRef

Jiang, X.,
Iterative Truncated Arithmetic Mean Filter and Its Properties,
IP(21), No. 4, April 2012, pp. 1537-1547.
IEEE DOI 1204
BibRef

Xiong, B., Yin, Z.,
A Universal Denoising Framework With a New Impulse Detector and Nonlocal Means,
IP(21), No. 4, April 2012, pp. 1663-1675.
IEEE DOI 1204
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Lu, C.T.[Ching-Ta], Chou, T.C.[Tzu-Chun],
Denoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filter,
PRL(33), No. 10, 15 July 2012, pp. 1287-1295.
Elsevier DOI 1205
Image denoising; Salt-and-pepper noise; Median filter; Motion direction; Iterative filtering BibRef

Liu, Q.G.[Qie-Gen], Wang, S.S.[Shan-Shan], Luo, J.H.[Jian-Hua], Zhu, Y.M.[Yue-Min], Ye, M.[Meng],
An augmented Lagrangian approach to general dictionary learning for image denoising,
JVCIR(23), No. 5, July 2012, pp. 753-766.
Elsevier DOI 1205
Sparse representation; Dictionary learning; Augmented Lagrangian; Bregman iterative method; Accelerated technique; Iteratively Reweighted Norm; Gaussian noise removal; Impulse noise removal BibRef

Wang, S.S.[Shan-Shan], Xia, Y.[Yong], Liu, Q.G.[Qie-Gen], Luo, J.H.[Jian-Hua], Zhu, Y.M.[Yue-Min], Feng, D.D.[David Dagan],
Gabor feature based nonlocal means filter for textured image denoising,
JVCIR(23), No. 7, October 2012, pp. 1008-1018.
Elsevier DOI 1209
Nonlocal means filter; Gabor filter; Image denoising; Textured image analysis; Feature extraction; Similarity detection; Signal restoration; Gaussian noise BibRef

Zhou, Z.,
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IEEE DOI 1206
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SIViP(6), No. 4, November 2012, pp. 579-595.
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Zhou, Y.Y., Ye, Z.F., Huang, J.J.,
Improved decision-based detail-preserving variational method for removal of random-valued impulse noise,
IET-IPR(6), No. 7, 2012, pp. 976-985.
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Elsevier DOI 1212
Speckle noise; Nonconvex; Sparse; Alternative iteration; Augmented Lagrange multiplier; Iteratively reweighted method BibRef

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SIViP(7), No. 1, January 2013, pp. 111-118.
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IP(22), No. 3, March 2013, pp. 1223-1232.
IEEE DOI 1301
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A restoration algorithm for images contaminated by mixed Gaussian plus random-valued impulse noise,
JVCIR(24), No. 3, April 2013, pp. 283-294.
Elsevier DOI 1303
Image restoration; Mixed noise; Sparse representation; Masked K-SVD; Overcomplete dictionary; Noise classification; Bayesian decision rule; Variational denoising model BibRef

Hosseini, H., Marvasti, F.,
Fast restoration of natural images corrupted by high-density impulse noise,
JIVP(2013), No. 1, 2013, pp. 15.
DOI Link 1304
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Hosseini, H., Hessar, F., Marvasti, F.,
Real-Time Impulse Noise Suppression from Images Using an Efficient Weighted-Average Filtering,
SPLetters(22), No. 8, August 2015, pp. 1050-1054.
IEEE DOI 1502
image denoising BibRef

Jin, L.H.[Liang-Hai], Liu, H.[Hong], Xu, X.Y.[Xiang-Yang], Song, E.[Enmin],
Quaternion-Based Impulse Noise Removal From Color Video Sequences,
CirSysVideo(23), No. 5, May 2013, pp. 741-755.
IEEE DOI 1305
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Jin, L.H.[Liang-Hai],
Complex impulse noise removal from color images based on super pixel segmentation,
JVCIR(48), No. 1, 2017, pp. 54-65.
Elsevier DOI 1708
Color, image BibRef

Baek, Y.M.[Yeul-Min], Kim, W.Y.[Whoi-Yul],
Noise Reduction Method for Image Signal Processor Based on Unified Image Sensor Noise Model,
IEICE(E96-D), No. 5, May 2013, pp. 1152-1161.
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shot noise, dark-current noise, and fixed-pattern noise (FPN) together BibRef

Baljozovic, D.[Djordje], Kovacevic, B.[Branko], Baljozovic, A.[Aleksandra],
Mixed noise removal filter for multi-channel images based on halfspace deepest location,
IET-IPR(7), No. 4, 2013, pp. 310-323.
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remove mixed, impulse and Gaussian, noise. based on
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Xu, Z.Y.[Zheng-Ya], Wu, H.R.[Hong Ren], Yu, X.H.[Xing-Huo], Qiu, B.[Bin],
Adaptive progressive filter to remove impulse noise in highly corrupted color images,
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Phu, M.Q.[Mieng Quoc], Tischer, P.E.[Peter Eric], Wu, H.R.[Hon Ren],
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IEEE DOI 0609
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Nair, M.S.[Madhu S.], Shankar, V.[Viju],
Predictive-based adaptive switching median filter for impulse noise removal using neural network-based noise detector,
SIViP(7), No. 6, November 2013, pp. 1041-1070.
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Yan, M.,
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Jayasree, P.S.[P. Syamala], Raj, P.[Paru], Kumar, P.[Pradeep], Siddavatam, R.[Rajesh], Ghrera, S.P.,
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Springer DOI 1310
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Chen, F.[Fenge], Jiao, Y.L.[Yu-Ling], Ma, G.R.[Guo-Rui], Qin, Q.Q.[Qian-Qing],
Hybrid regularization image deblurring in the presence of impulsive noise,
JVCIR(24), No. 8, 2013, pp. 1349-1359.
Elsevier DOI 1312
Total variation BibRef

Kalyoncu, C., Toygar, O., Demirel, H.,
Interpolation-based impulse noise removal,
IET-IPR(7), No. 8, November 2013, pp. 777-785.
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image denoising BibRef

Kayhan, S.K.[Sema Koç],
An effective 2-stage method for removing impulse noise in images,
JVCIR(25), No. 2, 2014, pp. 478-486.
Elsevier DOI 1402
Impulse noise removal BibRef

Bhadouria, V.S.[Vivek Singh], Ghoshal, D.[Dibyendu], Siddiqi, A.H.[Abul Hasan],
A new approach for high density saturated impulse noise removal using decision-based coupled window median filter,
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Bhadouria, V.S.[Vivek Singh], Ghoshal, D.[Dibyendu],
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Teoh, S.H.[Sin Hoong], Ibrahim, H.[Haidi],
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Mendiola-Santibañez, J.D., Terol-Villalobos, I.R.,
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filtering theory BibRef

Pyatykh, S.[Stanislav], Hesser, J.[Jürgen],
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Pyatykh, S.[Stanislav], Hesser, J.[Jürgen],
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error statistics BibRef

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IEEE DOI 1302
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Varghese, J., Ghouse, M., Subash, S., Siddappa, M., Khan, M.S., Hussain, O.B.[O. Bin],
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Zhang, P., Li, F.,
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Dawood, H.[Hussain], Dawood, H.[Hassan], Guo, P.[Ping],
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Shang, J.D.[Jia-Dong], Wang, Z.[Zulin], Huang, Q.[Qin],
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Darsena, D., Gelli, G., Melito, F., Verde, F.,
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Bai, T.[Tian], Tan, J.Q.[Jie-Qing],
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Sulaiman, S.N.[Siti Noraini], Isa, N.A.M.[Nor Ashidi Mat], Yusoff, I.A.[Intan Aidha], Ahmad, F.[Fadzil],
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Springer DOI 1503
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Shi, K.[Kehan], Guo, Z.C.[Zhi-Chang], Dong, G.[Gang], Sun, J.[Jiebao], Zhang, D.Z.[Da-Zhi], Wu, B.Y.[Bo-Ying],
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Springer DOI 1504
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Pilevar, A.H.[Abdol Hamid], Saien, S.[Soudeh], Khandel, M.[Mina], Mansoori, B.[Bahman],
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Springer DOI 1504
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Ponomaryov, V.[Volodymyr], Montenegro, H.[Hector], Rosales, A.[Alberto], Duchen, G.[Gonzalo],
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Springer DOI 1506
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Chen, C.L.P., Liu, L.C.[Li-Cheng], Chen, L.[Long], Tang, Y.Y.[Yuan Yan], Zhou, Y.C.[Yi-Cong],
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IEEE DOI 1509
image denoising BibRef

Choi, Y.S.[Young-Seok],
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Joint parameter estimation and target localization for bistatic MIMO radar system in impulsive noise,
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Oudre, L.[Laurent],
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SIViP(9), No. 1 Supp, December 2015, pp. 41-48.
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Earlier:
Denoising using projections onto the epigraph set of convex cost functions,
ICIP14(2709-2713)
IEEE DOI 1502
Cost function BibRef

Smolka, B.[Bogdan], Kusnik, D.[Damian],
Robust local similarity filter for the reduction of mixed Gaussian and impulsive noise in color digital images,
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Turkmen, I.[Ilke],
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Image denoising BibRef

Qi, X.Y.[Xian-Ying], Liu, B.Q.[Bo-Qiang], Xu, J.W.[Jian-Wei],
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Elsevier DOI 1603
Image denoising BibRef

Lin, X., Li, C.T.,
Enhancing Sensor Pattern Noise via Filtering Distortion Removal,
SPLetters(23), No. 3, March 2016, pp. 381-385.
IEEE DOI 1603
image denoising BibRef

Wang, X., Shi, G., Zhang, P., Wu, J., Li, F., Wang, Y., Jiang, H.,
High quality impulse noise removal via non-uniform sampling and autoregressive modelling based super-resolution,
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image resolution BibRef

Wang, X.T.[Xiao-Tian], Shen, S.S.[Shan-Shan], Shi, G.M.[Guang-Ming], Xu, Y.N.[Yuan-Nan], Zhang, P.Y.[Pei-Yu],
Iterative non-local means filter for salt and pepper noise removal,
JVCIR(38), No. 1, 2016, pp. 440-450.
Elsevier DOI 1605
Salt and pepper noise removal BibRef

Gellert, A., Brad, R.,
Context-based prediction filtering of impulse noise images,
IET-IPR(10), No. 6, 2016, pp. 429-437.
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image denoising BibRef

Deng, X.Y.[Xiang-Yu], Ma, Y.[Yide], Dong, M.[Min],
A new adaptive filtering method for removing salt and pepper noise based on multilayered PCNN,
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Elsevier DOI 1608
Salt and pepper noise BibRef

Lu, C.T.[Ching-Ta], Chen, Y.Y.[Yung-Yue], Wang, L.L.[Ling-Ling], Chang, C.F.[Chun-Fan],
Removal of salt-and-pepper noise in corrupted image using three-values-weighted approach with variable-size window,
PRL(80), No. 1, 2016, pp. 188-199.
Elsevier DOI 1609
Image denoising BibRef

Wang, Y., Wang, J., Song, X., Han, L.,
An Efficient Adaptive Fuzzy Switching Weighted Mean Filter for Salt-and-Pepper Noise Removal,
SPLetters(23), No. 11, November 2016, pp. 1582-1586.
IEEE DOI 1609
fuzzy set theory BibRef

Hasegawa, M.[Masaya], Sakashita, K.[Kazuki], Uchikoshi, K.[Kousei], Hirobayashi, S.[Shigeki], Misawa, T.[Tadanobu],
Removal of Salt-and-Pepper Noise Using a High-Precision Frequency Analysis Approach,
IEICE(E100-D), No. 5, May 2017, pp. 1097-1105.
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Roy, A.[Amarjit], Singha, J.[Joyeeta], Manam, L.[Lalit], Laskar, R.H.[Rabul Hussain],
Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images,
IET-IPR(11), No. 6, June 2017, pp. 352-361.
DOI Link 1706
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He, Z.Q., Li, H., Shi, Z.P., Fang, J., Huang, L.,
A Robust Iteratively Reweighted L_ Approach for Spectral Compressed Sensing in Impulsive Noise,
SPLetters(24), No. 7, July 2017, pp. 938-942.
IEEE DOI 1706
Compressed sensing, Dictionaries, Gaussian noise, Linear programming, Noise measurement, Robustness, Signal resolution, Compressed sensing (CS), grid mismatch, impulsive noise, line, spectra, estimation BibRef

Gao, W., Chen, J.,
Kernel Least Mean p-Power Algorithm,
SPLetters(24), No. 7, July 2017, pp. 996-1000.
IEEE DOI 1706
adaptive filters, error statistics, impulse noise, nonlinear systems, recursive estimation, statistical distributions, KLMP algorithm, additive nonGaussian impulsive noises, dynamic recursive weight coefficients, fractional lower order statistics error criterion, impulsive estimation error, kernel least mean p-power algorithm, nonlinear system identification, symmetric alpha-stable distribution, Coherence, Convergence, Cost function, Dictionaries, Heuristic algorithms, Kernel, Signal processing algorithms, Fractional lower order statistics (FLOS), kernel least mean p-power (KLMP) algorithm, symmetric, alpha-stable, (S, alpha, S), distribution BibRef

Shui, P.L., Wang, F.P.,
Anti-Impulse-Noise Edge Detection via Anisotropic Morphological Directional Derivatives,
IP(26), No. 10, October 2017, pp. 4962-4977.
IEEE DOI 1708
Detectors, Feature extraction, Gray-scale, Image edge detection, Image resolution, Robustness, Impulse noise, anisotropic morphological directional derivatives, biwindow configuration, differential-based edge detection, weighted, median, filter BibRef

Chen, Q.Q.A.[Qing-Qi-Ang], Hung, M.H.[Mao-Hsiung], Zou, F.M.[Fu-Min],
Effective and adaptive algorithm for pepper-and-salt noise removal,
IET-IPR(11), No. 9, September 2017, pp. 709-716.
DOI Link 1709
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Zhang, X.J.[Xiong-Jun], Bai, M.[Minru], Ng, M.K.[Michael K.],
Nonconvex-TV Based Image Restoration with Impulse Noise Removal,
SIIMS(10), No. 3, 2017, pp. 1627-1667.
DOI Link 1710
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Singh, N.[Neeti], Thilagavathy, T.[Thirusangu], Lakshmipriya, R.T.[Ramasubramanian T.], Umamaheswari, O.[Oorkavalan],
Some studies on detection and filtering algorithms for the removal of random valued impulse noise,
IET-IPR(11), No. 11, November 2017, pp. 953-963.
DOI Link 1711
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Taherkhani, F.[Fariborz], Jamzad, M.[Mansour],
Restoring highly corrupted images by impulse noise using radial basis functions interpolation,
IET-IPR(12), No. 1, January 2018, pp. 20-30.
DOI Link 1712
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Jin, K.H., Ye, J.C.,
Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal,
IP(27), No. 3, March 2018, pp. 1448-1461.
IEEE DOI 1801
BibRef
Earlier:
Random impulse noise removal using sparse and low rank decomposition of annihilating filter-based Hankel matrix,
ICIP16(3877-3881)
IEEE DOI 1610
Convex functions, Frequency-domain analysis, Image edge detection, Matrix decomposition, Noise reduction, sparse and low rank decomposition BibRef

Hussain, A.[Ayyaz], Habib, M.[Muhammad], Ramzan, M.[Muhammad],
RETRACTED ARTICLE: Cartesian vector-based directional nonparametric fuzzy filter for random-valued impulse noise removal,
SIViP(12), No. 1, January 2018, pp. 197.
Springer DOI 1801
see: A new cluster based adaptive fuzzy switching median filter for impulse noise removal Multimed Tools Appl DOI
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Ma, W.T.[Wen-Tao], Zheng, D.Q.[Dong-Qiao], Zhang, Z.Y.[Zhi-Yu], Duan, J.D.[Jian-Dong], Chen, B.D.[Ba-Dong],
Robust proportionate adaptive filter based on maximum correntropy criterion for sparse system identification in impulsive noise environments,
SIViP(12), No. 1, January 2018, pp. 117-124.
Springer DOI 1801
BibRef

Chen, Y., Zhang, Y., Shu, H., Yang, J., Luo, L., Coatrieux, J.L., Feng, Q.,
Structure-Adaptive Fuzzy Estimation for Random-Valued Impulse Noise Suppression,
CirSysVideo(28), No. 2, February 2018, pp. 414-427.
IEEE DOI 1802
Random-valued impulse noise, reliability metric, similarity metric, structure-adaptive fuzzy estimation (SAFE) BibRef

Sanaee, P.[Payam], Moallem, P.[Payman], Razzazi, F.[Farbod],
A structural post-processing method for enhancing intensity restoration of low-density impulse-noise for decision based filters,
JVCIR(51), 2018, pp. 40-55.
Elsevier DOI 1802
Impulse-noise, Image denoising, Image restoration, Decision based filters, Edge and detail preserving BibRef

Sanaee, P.[Payam], Moallem, P.[Payman], Razzazi, F.[Farbod],
Structure-based interpolation method for restoring the intensity of low-density impulse noise,
IET-IPR(12), No. 9, September 2018, pp. 1577-1585.
DOI Link 1809
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Sanaee, P.[Payam], Moallem, P.[Payman], Razzazi, F.[Farbod],
An interpolation filter based on natural neighbor Galerkin method for salt and pepper noise restoration with adaptive size local filtering window,
SIViP(13), No. 5, July 2019, pp. 895-903.
WWW Link. 1906
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Gellert, A.[Arpad], Brad, R.[Remus],
Studying the influence of search rule and context shape in filtering impulse noise images with Markov chains,
SIViP(12), No. 2, February 2018, pp. 315-322.
WWW Link. 1802
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Mújica-Vargas, D.[Dante], de Jesús Rubio, J.[José], Kinani, J.M.V.[Jean Marie Vianney], Gallegos-Funes, F.J.[Francisco J.],
An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images,
RealTimeIP(14), No. 3, March 2018, pp. 617-633.
Springer DOI 1804
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Harris, L., Llewellyn, G.M., Holma, H., Warren, M.A., Clewley, D.,
Characterization of Unstable Blinking Pixels in the AisaOWL Thermal Hyperspectral Imager,
GeoRS(56), No. 3, March 2018, pp. 1695-1703.
IEEE DOI 1804
II-VI semiconductors, data acquisition, geophysical image processing, hyperspectral imaging, thermal BibRef

Chen, J.[Jiayi], Zhan, Y.W.[Yin-Wei], Cao, H.Y.[Hui-Ying], Wu, X.[Xingda],
Adaptive probability filter for removing salt and pepper noises,
IET-IPR(12), No. 6, June 2018, pp. 863-871.
DOI Link 1805
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Zhao, Q., Du, Q., Gong, X., Chen, Y.,
Signal-Preserving Erratic Noise Attenuation via Iterative Robust Sparsity-Promoting Filter,
GeoRS(56), No. 6, June 2018, pp. 3547-3560.
IEEE DOI 1806
Attenuation, Gaussian distribution, Noise measurement, Noise reduction, Optimization, Robustness, Transforms, Erratic noise, signal preserving BibRef

Samantaray, A.K.[Aswini Kumar], Kanungo, P.[Priyadarshi], Mohanty, B.[Bibhuprasad],
Neighbourhood decision based impulse noise filter,
IET-IPR(12), No. 7, July 2018, pp. 1222-1227.
DOI Link 1806
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Fareed, S.B.S.[Samsad Beagum Sheik], Khader, S.S.[Sheeja Shaik],
Fast adaptive and selective mean filter for the removal of high-density salt and pepper noise,
IET-IPR(12), No. 8, August 2018, pp. 1378-1387.
DOI Link 1808
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Javaheri, A., Zayyani, H., Figueiredo, M.A.T., Marvasti, F.,
Robust Sparse Recovery in Impulsive Noise via Continuous Mixed Norm,
SPLetters(25), No. 8, August 2018, pp. 1146-1150.
IEEE DOI 1808
approximation theory, Gaussian distribution, impulse noise, minimisation, probability, signal reconstruction, symmetric a-Stable (SaS) distribution BibRef

Pok, G., Ryu, K.H.,
Efficient Block Matching for Removing Impulse Noise,
SPLetters(25), No. 8, August 2018, pp. 1176-1180.
IEEE DOI 1808
Gaussian noise, image denoising, image matching, impulse noise, impulse noise, block-based image-denoising methods, impulse noise BibRef

Mafi, M., Rajaei, H., Cabrerizo, M., Adjouadi, M.,
A Robust Edge Detection Approach in the Presence of High Impulse Noise Intensity Through Switching Adaptive Median and Fixed Weighted Mean Filtering,
IP(27), No. 11, November 2018, pp. 5475-5490.
IEEE DOI 1809
adaptive filters, edge detection, image colour analysis, image denoising, image filtering, image sequences, image thinning, mean filtering BibRef

Dev, R., Verma, N.K.,
Generalized Fuzzy Peer Group for Removal of Mixed Noise from Color Image,
SPLetters(25), No. 9, September 2018, pp. 1330-1334.
IEEE DOI 1809
fuzzy set theory, Gaussian noise, image colour analysis, image denoising, image filtering, impulse noise, peer group BibRef

Dev, R., Verma, N.K.,
Robust Noisiness Measure Based Improved Generalized Fuzzy Peer Group for Removal of Mixed Noise From Color Image,
SPLetters(26), No. 2, February 2019, pp. 267-271.
IEEE DOI 1902
edge detection, fuzzy set theory, Gaussian noise, image colour analysis, image denoising, impulse noise, fuzzy peer group BibRef

Jin, L.H.[Liang-Hai], Liu, H.[Hong], Zhang, W.H.[Wen-Hua], Song, E.[Enmin],
Video oriented filter for impulse noise reduction,
JVCIR(55), 2018, pp. 1-11.
Elsevier DOI 1809
Video denoising, Window-adaptive filter, Orientation estimation, Impulse noise BibRef

Pritamdas, K., Manglem Singh, K., Lolitkumar Singh, L.,
Removal of impulse noise from color images based on the localized image characteristics and noise level,
SIViP(12), No. 7, October 2018, pp. 1377-1385.
WWW Link. 1809
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Gao, J.[Jing], Du, Z.Q.[Zeng-Quan], Shi, Z.F.[Zai-Feng], Xu, Z.H.[Ze-Hao], Cao, Q.J.[Qing-Jie], Tang, R.[Rui],
Switching impulse noise filter based on Laplacian convolution and pixels grouping for color images,
SIViP(12), No. 8, November 2018, pp. 1523-1529.
Springer DOI 1809
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Islam, M.T.[Mohammad Tariqul], Rahman, S.M.M.[S.M. Mahbubur], Ahmad, M.O.[M. Omair], Swamy, M.N.S.,
Mixed Gaussian-impulse noise reduction from images using convolutional neural network,
SP:IC(68), 2018, pp. 26-41.
Elsevier DOI 1810
Convolutional neural network, Deep learning, Image denoising, Reduction of mixed-noise BibRef

Song, G.[Gihun], Roy, K.[Kaushik], Ahn, K.[Kiok], Abdullah-Al-Wadud, M., Iqbal, M.T.B.[Md. Tauhid Bin], Chae, O.[Oksam],
Structural pattern-based approach for Betacam dropout detection in degraded archived media,
IET-IPR(13), No. 1, January 2019, pp. 224-232.
DOI Link 1812
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Qian, G.B.[Guo-Bing], Wang, S.Y.[Shi-Yuan], Wang, L.D.[Li-Dan], Duan, S.K.[Shu-Kai],
Convergence Analysis of a Fixed Point Algorithm Under Maximum Complex Correntropy Criterion,
SPLetters(25), No. 12, December 2018, pp. 1830-1834.
IEEE DOI 1812
adaptive filters, convergence of numerical methods, filtering theory, impulse noise, matrix inversion, EMSE BibRef

Zhang, T.[Tao], Wang, S.Y.[Shi-Yuan],
Nyström Kernel Algorithm Under Generalized Maximum Correntropy Criterion,
SPLetters(27), 2020, pp. 1535-1539.
IEEE DOI 2009
Kernel, Signal processing algorithms, Sampling methods, Approximation algorithms, Computational complexity, PRQ sampling BibRef

Yuan, G.Z.[Gan-Zhao], Ghanem, B.[Bernard],
L_0 TV: A Sparse Optimization Method for Impulse Noise Image Restoration,
PAMI(41), No. 2, February 2019, pp. 352-364.
IEEE DOI 1901
BibRef
Earlier:
L_0TV: A new method for image restoration in the presence of impulse noise,
CVPR15(5369-5377)
IEEE DOI 1510
TV, Image restoration, Data models, Optimization methods, Noise measurement, Image denoising, Total variation, impulse noise BibRef

Halder, A.[Amiya], Halder, S.[Sayan], Chakraborty, S.[Samrat], Sarkar, A.[Apurba],
A Statistical Salt-and-Pepper Noise Removal Algorithm,
IJIG(19), No. 1 2018, pp. 1950006.
DOI Link 1902
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Lyu, J., Bi, D., Li, X., Xie, Y.,
Robust Compressive Two-Dimensional Near-Field Millimeter-Wave Image Reconstruction in Impulsive Noise,
SPLetters(26), No. 4, April 2019, pp. 567-571.
IEEE DOI 1903
Image reconstruction, Image coding, Signal processing algorithms, TV, Noise measurement, parallel primal-dual algorithm BibRef

Zeng, C., Wu, C., Jia, R.,
Non-Lipschitz Models for Image Restoration with Impulse Noise Removal,
SIIMS(12), No. 1, 2019, pp. 420-458.
DOI Link 1904
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Delon, J.[Julie], Desolneux, A.[Agnès], Sutour, C.[Camille], Viano, A.[Agathe],
RNLp: Mixing Nonlocal and TV-Lp Methods to Remove Impulse Noise from Images,
JMIV(61), No. 4, May 2019, pp. 458-481.
Springer DOI 1904
BibRef

Chen, J.[Jiayi], Zhan, Y.W.[Yin-Wei], Cao, H.Y.[Hui-Ying], Xiong, G.Q.A.[Gang-Qi-Ang],
Iterative grouping median filter for removal of fixed value impulse noise,
IET-IPR(13), No. 6, 10 May 2019, pp. 946-953.
DOI Link 1906
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Liu, T., Qiu, T., Luan, S.,
Cyclic Frequency Estimation by Compressed Cyclic Correntropy Spectrum in Impulsive Noise,
SPLetters(26), No. 6, June 2019, pp. 888-892.
IEEE DOI 1906
compressed sensing, computational complexity, entropy, frequency estimation, impulse noise, numerical analysis, compressed sensing BibRef

Ehret, T.[Thibaud], Davy, A.[Axel], Morel, J.M.[Jean-Michel], Delbracio, M.[Mauricio],
Image Anomalies: A Review and Synthesis of Detection Methods,
JMIV(61), No. 5, June 2019, pp. 710-743.
Springer DOI 1906
BibRef
Earlier: A2, A1, A3, A4:
Reducing Anomaly Detection in Images to Detection in Noise,
ICIP18(1058-1062)
IEEE DOI 1809
Feature extraction, Computational modeling, Neural networks, Detectors, Anomaly detection, Colored noise, Image reconstruction, Self-similarity BibRef

Ehret, T.[Thibaud], Davy, A.[Axel], Delbracio, M.[Mauricio], Morel, J.M.[Jean-Michel],
How to Reduce Anomaly Detection in Images to Anomaly Detection in Noise,
IPOL(9), 2019, pp. 391-412.
DOI Link 1806
Code, Anomaly Detection. BibRef

Ehret, T.[Thibaud], Morel, J.M.[Jean-Michel], Arias, P.[Pablo],
Non-Local Kalman: A Recursive Video Denoising Algorithm,
ICIP18(3204-3208)
IEEE DOI 1809
Noise reduction, Trajectory, Covariance matrices, Kalman filters, Adaptive optics, Streaming media, Noise measurement, Patch-based methods BibRef

Soltanpur, C., Paravi, R., Ghamari, M., Adebisi, B.,
Nonlinear MMSE Equalizer for Impulsive Noise Mitigation in OFDM-Based Communications,
SPLetters(26), No. 7, July 2019, pp. 1016-1020.
IEEE DOI 1906
carrier transmission on power lines, equalisers, impulse noise, least mean squares methods, OFDM modulation, turbo codes, nonlinear filters BibRef

Xing, Y.[Yan], Xu, J.[Jian], Tan, J.Q.[Jie-Qing], Li, D.L.[Dao-Lun], Zha, W.S.[Wen-Shu],
Deep CNN for removal of salt and pepper noise,
IET-IPR(13), No. 9, 18 July 2019, pp. 1550-1560.
DOI Link 1907
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Jin, L.H.[Liang-Hai], Zhang, W.H.[Wen-Hua], Ma, G.Z.[Guang-Zhi], Song, E.[Enmin],
Learning deep CNNs for impulse noise removal in images,
JVCIR(62), 2019, pp. 193-205.
Elsevier DOI 1908
Image, Impulse noise, Convolution neural network, Denoising BibRef

Chen, J.[Jiuning], Li, F.[Fang],
Denoising convolutional neural network with mask for salt and pepper noise,
IET-IPR(13), No. 13, November 2019, pp. 2604-2613.
DOI Link 1911
BibRef

Jia, X.F.[Xiao-Fen], Guo, Y.[Yongcun], Zhao, B.[Baiting], Huang, Y.[Yourui],
Fractional-integral-operator-based improved SVM for filtering salt-and-pepper noise,
IET-IPR(13), No. 12, October 2019, pp. 2346-2357.
DOI Link 1911
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Devi, M.S.[M. Sindhana], Soranamageswari, M.,
Efficient impulse noise removal using hybrid neuro-fuzzy filter with optimized intelligent water drop technique,
IJIST(29), No. 4, 2019, pp. 465-475.
DOI Link 1911
first order Sugeno type fuzzy interference system, impulse noise, Mamdani fuzzy interference system BibRef

Abdurrazzaq, A.[Achmad], Mohd, I.[Ismail], Junoh, A.K.[Ahmad Kadri], Yahya, Z.[Zainab],
Modified tropical algebra based median filter for removing salt and pepper noise in digital image,
IET-IPR(13), No. 14, 12 December 2019, pp. 2790-2795.
DOI Link 1912
BibRef

Jelodari, P.T.[Parham Taghinia], Kordasiabi, M.P.[Mojtaba Parsa], Sheikhaei, S.[Samad], Forouzandeh, B.[Behjat],
FPGA implementation of an adaptive window size image impulse noise suppression system,
RealTimeIP(16), No. 6, December 2019, pp. 2015-2026.
Springer DOI 1912
BibRef

Alaoui, N.[Nail], Adamou-Mitiche, A.B.H.[Amel Baha Houda], Mitiche, L.[Lahcène],
Effective hybrid genetic algorithm for removing salt and pepper noise,
IET-IPR(14), No. 2, February 2020, pp. 289-296.
DOI Link 2001
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Wen, P.W.[Peng-Wei], Zhang, J.[Jiashu], Zhang, S.[Sheng],
Robust competitive diffusion LMS algorithm,
SIViP(14), No. 2, March 2020, pp. 343-349.
Springer DOI 2003
BibRef

Erkan, U.[Ugur], Enginoglu, S.[Serdar], Thanh, D.N.H.[Dang N.H.], Hieu, L.M.[Le Minh],
Adaptive frequency median filter for the salt and pepper denoising problem,
IET-IPR(14), No. 7, 29 May 2020, pp. 1291-1302.
DOI Link 2005
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Gökcen, A.[Alpaslan], Kalyoncu, C.[Cem],
Real-time impulse noise removal,
RealTimeIP(17), No. 3, June 2020, pp. 459-469.
Springer DOI 2006
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Zhu, H., Ng, M.K.,
Structured Dictionary Learning for Image Denoising Under Mixed Gaussian and Impulse Noise,
IP(29), 2020, pp. 6680-6693.
IEEE DOI 2007
Noise reduction, Dictionaries, Machine learning, Gaussian noise, Computational modeling, Image denoising, Image restoration, impulse noise BibRef

Zheng, S., Cagnazzo, M., Kieffer, M.,
Channel Impulsive Noise Mitigation for Linear Video Coding Schemes,
CirSysVideo(30), No. 9, September 2020, pp. 3196-3209.
IEEE DOI 2009
OFDM, Receivers, Video coding, Video recording, Quality assessment, Simulation, Precoding, Impulsive noise, linear video coding, video transmission BibRef

Satti, P., Sharma, N., Garg, B.,
Min-Max Average Pooling Based Filter for Impulse Noise Removal,
SPLetters(27), 2020, pp. 1475-1479.
IEEE DOI 2009
Noise measurement, Image restoration, Image edge detection, Benchmark testing, Correlation, PSNR, Noise reduction, Mean filters, image restoration and de-noising BibRef

Jeong, J.J.,
A Robust Affine Projection Algorithm Against Impulsive Noise,
SPLetters(27), 2020, pp. 1530-1534.
IEEE DOI 2009
Signal processing algorithms, Signal to noise ratio, Robustness, Linear matrix inequalities, Projection algorithms, time-varying system BibRef

Varghese, J.[Justin], Subash, S.[Saudia], Sridhar, K.P.[Kuttaiyur Palaniswamy], Balaji, N.V.[Narayanasamy Venkattaramanujam], Kumar, G.A.[Gopalakrishnan Ashok],
Adaptive switching interpolation filter for restoring impulse corrupted digital images,
IET-IPR(14), No. 12, October 2020, pp. 2869-2878.
DOI Link 2010
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Subash, S.[Saudia], Varghese, J.[Justin], Nallaperumal, K.[Krishnan], Mathew, S.P.[Santhosh P.], Allwin, S., Thakur, S.K.,
An Adaptive Clustering Based Non-linear Filter for the Restoration of Impulse Corrupted Digital Images,
ICCVGIP08(9-16).
IEEE DOI 0812
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Arora, S.[Shaveta], Hanmandlu, M.[Madasu], Gupta, G.[Gaurav],
Filtering impulse noise in medical images using information sets,
PRL(139), 2020, pp. 1-9.
Elsevier DOI 2011
Fuzzy sets, Information sets, Noise removal, Salt and pepper noise BibRef

Bania, R.K.[Rubul Kumar], Halder, A.[Anindya],
Adaptive Trimmed Median Filter for Impulse Noise Detection and Removal with an Application to Mammogram Images,
IJIG(20), No. 4, October 2020, pp. 2050032.
DOI Link 2011
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Pugalenthi, R., Oliver, A.S.[A. Sheryl], Anuradha, M.,
Impulse noise reduction using hybrid neuro-fuzzy filter with improved firefly algorithm from X-ray bio-images,
IJIST(30), No. 4, 2020, pp. 1119-1131.
DOI Link 2011
firefly algorithm, fuzzy interference system, impulse noise, Mamdani, particle swarm optimization BibRef

Sadrizadeh, S., Zarmehi, N., Kangarshahi, E.A., Abin, H., Marvasti, F.,
A Fast Iterative Method for Removing Impulsive Noise From Sparse Signals,
CirSysVideo(31), No. 1, January 2021, pp. 38-48.
IEEE DOI 2101
Image reconstruction, Cost function, Noise measurement, Iterative methods, Discrete cosine transforms, sparse signal BibRef

Mafi, M.[Mehdi], Izquierdo, W.[Walter], Martin, H.[Harold], Cabrerizo, M.[Mercedes], Adjouadi, M.[Malek],
Deep convolutional neural network for mixed random impulse and Gaussian noise reduction in digital images,
IET-IPR(14), No. 15, 15 December 2020, pp. 3791-3801.
DOI Link 2103
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Mafi, M.[Mehdi], Izquierdo, W.[Walter], Cabrerizo, M.[Mercedes], Barreto, A.[Armando], Andrian, J.[Jean], Rishe, N.D.[Naphtali David], Adjouadi, M.[Malek],
Survey on mixed impulse and Gaussian denoising filters,
IET-IPR(14), No. 16, 19 December 2020, pp. 4027-4038.
DOI Link 2103
Survey, Noise Filter. BibRef

Sen, A.P.[Amit Prakash], Rout, N.K.[Nirmal Kumar],
Improved probabilistic decision-based trimmed median filter for detection and removal of high-density impulsive noise,
IET-IPR(14), No. 17, 24 December 2020, pp. 4486-4498.
DOI Link 2104
BibRef

Meng, X.X.[Xiang-Xi], Lu, T.W.[Tong-Wei], Min, F.[Feng], Lu, T.[Tao],
An effective weighted vector median filter for impulse noise reduction based on minimizing the degree of aggregation,
IET-IPR(15), No. 1, 2021, pp. 228-238.
DOI Link 2106
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Xu, J.T.[Jiang-Tao], Xu, L.[Liang], Gao, Z.Y.[Zhi-Yuan], Lin, P.[Peng], Nie, K.M.[Kai-Ming],
A Denoising Method Based on Pulse Interval Compensation for High-Speed Spike-Based Image Sensor,
CirSysVideo(31), No. 8, August 2021, pp. 2966-2980.
IEEE DOI 2108
Image sensors, Noise reduction, Image reconstruction, Filtering algorithms, Transforms, Photodiodes, image correction BibRef

Zhang, Q.C.[Qian-Cheng], Ji, H.B.[Hong-Bing], Jin, Y.[Yan],
Cyclostationary Signals Analysis Methods Based on High-Dimensional Space Transformation Under Impulsive Noise,
SPLetters(28), 2021, pp. 1724-1728.
IEEE DOI 2109
Eigenvalues and eigenfunctions, Matrix decomposition, Kernel, Correlation, Frequency estimation, Binary phase shift keying, high-dimensional space transformation BibRef

Chen, C.R.[Chang-Run], Xu, W.C.[Wei-Chao], Pan, Y.J.[Yi-Jin], Zhu, H.L.[Hui-Ling], Wang, J.Z.[Jiang-Zhou],
Rank Correlation Based Detection of Known Signals in Middleton's Class-A Noise,
SPLetters(28), 2021, pp. 1988-1992.
IEEE DOI 2110
Detect known signal in impulsive noise. Detectors, Atmospheric modeling, Gaussian noise, Correlation, Signal to noise ratio, Mathematical model, Data models, Spearman's rho (SR) BibRef

Cao, Y.Q.[Yi-Qin], Fu, Y.Y.[Yang-Yi], Zhu, Z.L.[Zhi-Liang], Rao, Z.C.[Zhe-Chu],
Color Random Valued Impulse Noise Removal Based on Quaternion Convolutional Attention Denoising Network,
SPLetters(29), 2022, pp. 369-373.
IEEE DOI 2202
Quaternions, Convolution, Image color analysis, Feature extraction, Noise reduction, Colored noise, Kernel, Color impulse noise, quaternion convolutional neural network BibRef

Yin, M.M.[Ming-Ming], Adam, T.[Tarmizi], Paramesran, R.[Raveendran], Hassan, M.F.[Mohd Fikree],
An L_0-overlapping group sparse total variation for impulse noise image restoration,
SP:IC(102), 2022, pp. 116620.
Elsevier DOI 2202
Non-convex, Image restoration, Total variation, ADMM, -norm fidelity BibRef

Chen, Y.P.[Ying-Pin], Huang, Y.M.[Yu-Ming], Wang, L.Z.[Ling-Zhi], Huang, H.Y.[Hui-Ying], Song, J.H.[Jian-Hua], Yu, C.Q.[Chao-Qun], Xu, Y.P.[Yan-Ping],
Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization,
IET-IPR(16), No. 7, 2022, pp. 1846-1865.
DOI Link 2205
BibRef
And: Corrigendum: IET-IPR(17), No. 7, 2023, pp. 2297-2298.
DOI Link 2305
BibRef

Yu, Y.[Yi], Lu, L.[Lu], Zakharov, Y.[Yuriy], de Lamare, R.C.[Rodrigo C.], Chen, B.D.[Ba-Dong],
Robust Sparsity-Aware RLS Algorithms With Jointly-Optimized Parameters Against Impulsive Noise,
SPLetters(29), 2022, pp. 1037-1041.
IEEE DOI 2205
Signal processing algorithms, Robustness, Optimized production technology, Gaussian noise, Steady-state, sparse systems BibRef

Lu, L.[Lu], Yu, Y.[Yi], de Lamare, R.C.[Rodrigo C.], Yang, X.M.[Xiao-Min],
Tukey's Biweight M-Estimate With Conjugate Gradient Adaptive Learning,
SPLetters(29), 2022, pp. 1117-1121.
IEEE DOI 2205
Signal processing algorithms, Convergence, Computational complexity, Computational efficiency, Standards, system identification BibRef

Li, D.S.[Da-Song], Zhang, Y.[Yi], Law, K.L.[Ka Lung], Wang, X.G.[Xiao-Gang], Qin, H.W.[Hong-Wei], Li, H.S.[Hong-Sheng],
Efficient Burst Raw Denoising with Variance Stabilization and Multi-frequency Denoising Network,
IJCV(130), No. 8, August 2022, pp. 2060-2080.
Springer DOI 2207
BibRef

Tian, X.[Xin], Xie, K.[Kun], Zhang, H.[Hanling],
A Low-Rank Tensor Decomposition Model With Factors Prior and Total Variation for Impulsive Noise Removal,
IP(31), 2022, pp. 4776-4789.
IEEE DOI 2208
Tensors, Computational modeling, Matrix decomposition, Convex functions, Image restoration, Color, Training, ADMM BibRef

Lin, J.Y.[Jian-Yu], Qin, J.X.[Jian-Xiao], Lu, S.Z.[Shi-Zhu],
Suppressing Shot Noise Using Quadratic Variable Step-Size Quantization for the Initial Acquisition of Camera-Raw Image Data,
IP(31), 2022, pp. 5242-5256.
IEEE DOI 2208
Image coding, Quantization (signal), Image sensors, Digital cameras, Photonics, Image color analysis, Voltage, shot noise BibRef

Zhu, J.G.[Jian-Guang], Wei, J.[Juan], Hao, B.B.[Bin-Bin],
Fast algorithm for box-constrained fractional-order total variation image restoration with impulse noise,
IET-IPR(16), No. 12, 2022, pp. 3359-3373.
DOI Link 2209
BibRef

Wang, W.Q.[Wei-Qi], Yang, J.[Jidong], Huang, J.P.[Jian-Ping], Li, Z.C.[Zhen-Chun], Sun, M.M.[Miao-Miao],
Outlier Denoising Using a Novel Statistics-Based Mask Strategy for Compressive Sensing,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Sanmartín-Vich, N.[Nofre], Calpe, J.[Javier], Pla, F.[Filiberto],
Shot Noise Analysis for Differential Sampling in Indirect Time of Flight Cameras,
SPLetters(30), 2023, pp. 46-49.
IEEE DOI 2302
Discrete Fourier transforms, Delays, Cameras, Reactive power, Clocks, Time-domain analysis, Photonics, 3D imaging, time-of-flight, shot noise BibRef

Zhang, J.[Jun], Li, Z.Y.[Zhao-Yang], Wang, L.Z.[Ling-Zhi], Chen, Y.P.[Ying-Pin],
Salt-and-pepper denoising method for colour images based on tensor low-rank prior and implicit regularization,
IET-IPR(17), No. 3, 2023, pp. 886-900.
DOI Link 2303
data-driven, FFDNet, model-driven, parallel matrix factorization, salt and pepper denoising BibRef

Jiang, J.L.[Jie-Lin], Yang, K.[Kang], Xu, X.L.[Xiao-Long], Cui, Y.[Yan],
A serial attention module-based deep convolutional neural network for mixed Gaussian-impulse removal,
IET-IPR(17), No. 6, 2023, pp. 1837-1851.
DOI Link 2305
batch normalization, convolutional neural network, serial attention module BibRef

Li, S.H.[Shuai-Hao], Bi, X.[Xiang], Zhao, Y.J.[Ya-Jun], Bi, H.L.[Hong-Liang],
Extended neighborhood-based road and median filter for impulse noise removal from depth map,
IVC(135), 2023, pp. 104709.
Elsevier DOI 2306
Depth map denoising, Impulse noise removal, Rank-ordered absolute differences, Median filter BibRef

Li, Z.[Zhen], Guo, J.[Junyuan], Wang, X.H.[Xiao-Han],
Joint Detection and Reconstruction of Weak Spectral Lines under Non-Gaussian Impulsive Noise with Deep Learning,
RS(15), No. 13, 2023, pp. 3268.
DOI Link 2307
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Montagu, T.[Thierry], Ferrari, A.[André],
Variance Stabilizing Transformations for Intensity Estimators of Shot Noise,
SPLetters(30), 2023, pp. 977-981.
IEEE DOI 2309
BibRef

Gantenapalli, S.R.[Srinivasa Rao], Choppala, P.B.[Praveen Babu], Meka, J.S.[James Stephen],
Selective Mean Filtering for Reducing Impulse Noise in Digital Color Images,
IJIG(23), No. 5 2023, pp. 2350049.
DOI Link 2310
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Chukka, D.N.[Demudu Naidu], Meka, J.S.[James Stephen], Setty, S.P.[S. Pallam], Choppala, P.B.[Praveen Babu],
Bayesian Selective Median Filtering for Reduction of Impulse Noise in Digital Color Images,
IJIG(24), No. 3, May 2024, pp. 2450026.
DOI Link 2406
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Tang, Y.C.[Yu-Chao], Deng, S.[Shirong], Peng, J.[Jigen], Zeng, T.Y.[Tie-Yong],
Proximal linearized alternating direction method of multipliers algorithm for nonconvex image restoration with impulse noise,
IET-IPR(17), No. 14, 2023, pp. 4044-4060.
DOI Link 2312
image denoising, impulse noise BibRef

Ebrahimnejad, J.[Javad], Naghsh, A.[Alireza], Pourghasem, H.[Hossein],
A robust watermarking approach against high-density salt and pepper noise (RWSPN) to enhance medical image security,
IET-IPR(18), No. 1, 2024, pp. 116-128.
DOI Link 2401
data restoration, image denoising, image processing, medical image security, robust watermarking BibRef

Zhang, B.[Benxin], Zhu, G.P.[Guo-Pu], Zhu, Z.B.[Zhi-Bin], Zhang, H.L.[Hong-Li], Zhou, Y.C.[Yi-Cong], Kwong, S.[Sam],
Impulse Noise Image Restoration Using Nonconvex Variational Model and Difference of Convex Functions Algorithm,
Cyber(54), No. 4, April 2024, pp. 2257-2270.
IEEE DOI 2403
TV, Image restoration, Data models, Image edge detection, Convex functions, Mathematical models, nonconvex optimization model BibRef

Buckel, P.[Peter], Oksanen, T.[Timo], Dietmueller, T.[Thomas],
RB-Dust - A Reference-based Dataset for Vision-based Dust Removal,
NTIRE23(1140-1149)
IEEE DOI 2309
BibRef

Pearl, N.[Naama], Treibitz, T.[Tali], Korman, S.[Simon],
NAN: Noise-Aware NeRFs for Burst-Denoising,
CVPR22(12662-12671)
IEEE DOI 2210
Photography, Sensitivity, Noise reduction, Rendering (computer graphics), Cameras, Mobile handsets, Low-level vision BibRef