5.3.2 Image Restoration: Filter Approaches

Chapter Contents (Back)
Restoration. Filters. See also Non-Local Means for Denoising.

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Bandlimited Image Restoration by Linear Mean-Square-Error Filter,
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Stuller, J.A.,
An Algebraic Approach to Image Restoration Filter Design,
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Kondo, K., Ichioka, Y., and Suzuki, T.,
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Rajala, S.A., de Figueiredo, R.J.P.,
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Ahmed, M.S., Tahboub, K.K.,
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Restrepo, A., Bovik, A.C.,
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Liu, Z.Q., Caelli, T.M.[Terry M.],
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CVGIP(44), No. 3, December 1988, pp. 332-349.
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Mallikarjuna, H.S., and Chaparro, L.F.,
Iterative Composite Filtering for Image Restoration,
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IEEE DOI BibRef 9206

Katsaggelos, A.K., Kang, M.G.[Moon Gi],
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Earlier: A2, A1:
A general formulation of the weighted smoothing functional for regularized image restoration,
ICIP94(II: 695-699).
IEEE DOI 9411
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Kang, M.G.[Moon Gi], Johnson, T.C.,
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Molina, R.[Rafael], Katsaggelos, A.K.[Aggelos K.], Mateos, J.[Javier], Hermoso, A.[Aurora], Segall, C.A.[C. Andrew],
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Molina, R.[Rafael], Katsaggelos, A.K., Mateos, J., Abad, J.,
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ICIP96(II: 469-472).
IEEE DOI BibRef 9600

Peters, II, R.A.,
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IP(4), No. 5, May 1995, pp. 554-568.
IEEE DOI 0402
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Koivunen, V.,
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IP(4), No. 5, May 1995, pp. 569-578.
IEEE DOI 0402
BibRef

Joo, K.S., Bose, T., Xu, G.F.,
Image Restoration Using a Conjugate Gradient-Based Adaptive Filtering Algorithm,
CSSP(16), No. 2, 1997, pp. 197-206. 9703
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Joo, K.S.[Kyung Sub], Bose, T.,
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ICIP95(II: 117-120).
IEEE DOI 9510
BibRef

Wang, T., Wang, C.L.,
A New 2-Dimensional Block Adaptive Fir Filtering Algorithm and Its Application to Image-Restoration,
IP(7), No. 2, February 1998, pp. 238-246.
IEEE DOI 9802
BibRef

Natarajan, B.[Balas], Konstantinides, K., Herley, C.,
Occam Filters for Stochastic Sources with Application to Digital Images,
TSP(46), 1998, pp. 1434-xx. BibRef 9800
And: Correction: TSP(46), No. 6, June 1998, pp. 1777. BibRef
Earlier: ICIP96(I: 399-402).
IEEE DOI BibRef

Herley, C.,
A post-processing algorithm for compressed digital camera images,
ICIP98(I: 396-400).
IEEE DOI 9810
BibRef

Wei, G.W.,
Generalized Perona-Malik Equation for Image Restoration,
SPLetters(7), No. 7, July 1999, pp. 165.
IEEE Top Reference. See also Scale Space and Edge Detection using Anisotropic Diffusion. BibRef 9907

Hardie, R.C., Barner, K.E.,
Extended Permutation Filters and Their Application to Edge Enhancement,
IP(5), No. 6, June 1996, pp. 855-867.
IEEE DOI 9607
BibRef
Earlier: A2, A1:
Extended permutation filters and their application to image edge enhancement,
ICIP95(I: 366-369).
IEEE DOI 9510
BibRef

Hardie, R.C., Barner, K.E.,
Rank Conditioned Rank Selection Filters for Signal Restoration,
IP(3), No. 2, March 1994, pp. 192-206.
IEEE DOI BibRef 9403

Barner, K.E., Sarhan, A.M., Hardie, R.C.,
Partition-Based Weighted Sum Filters for Image Restoration,
IP(8), No. 5, May 1999, pp. 740-745.
IEEE DOI BibRef 9905

Shao, M., Barner, K.E.,
Optimization of Partition-Based Weighted Sum Filters and Their Application to Image Denoising,
IP(15), No. 7, July 2006, pp. 1900-1915.
IEEE DOI 0606
BibRef

Lin, Y., Hardie, R.C., Barner, K.E.,
Subspace Partition Weighted Sum Filters for Image Restoration,
SPLetters(12), No. 9, September 2005, pp. 613-616.
IEEE DOI 0508
BibRef

Wang, J.H.,
Prescanned minmax centre-weighted filters for image restoration,
VISP(146), No. 2, April 1999, pp. 101. BibRef 9904

Chow, T.W.S., Li, X., Cho, S.Y.,
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VISP(147), No. 1, February 2000, pp. 23. 0005
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Phoong, S.M.[See-May], Lin, Y.P.[Yuan-Pei],
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IEEE Top Reference. 0206
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Lin, Y.P.[Yuan-Pei], Phoong, S.M.[See-May],
Statistical Bit Allocation and Statistical Precoding for Correlated MIMO Channels With Decision Feedback,
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IEEE DOI 1210
BibRef

Wang, J.H.[Jung-Hua], Liu, W.J.[Wen-Jeng], Lin, L.D.[Lian-Da],
Histogram-based fuzzy filter for image restoration,
SMC-B(32), No. 2, April 2002, pp. 230-238.
IEEE Top Reference. 0205
BibRef

Sugiyama, M.[Masashi], Ogawa, H.[Hidemitsu],
A unified method for optimizing linear image restoration filters,
SP(82), No. 11, November 2002, pp. 1773-1787.
HTML Version. 0210
BibRef

Arbel, D., Cohen, E., Citroen, M., Blumberg, D.G., Kopeika, N.S.,
Landsat TM Satellite Image Restoration Using Kalman Filters,
PhEngRS(70), No. 1, January 2004, pp. 91-100. The implementation of atmospheric filters based on atmospheric MTF for satellite image restoration is described.
WWW Link. 0403
BibRef

Lun, D.P.K., Chan, T.C.L., Hsung, T.C.[Tai-Chiu], Feng, D.D., Chan, Y.H.[Yuk-Hee],
Efficient blind image restoration using discrete periodic Radon transform,
IP(13), No. 2, February 2004, pp. 188-200.
IEEE DOI 0404
BibRef

Allende, H.[Héctor], Galbiati, J.[Jorge],
A non-parametric filter for digital image restoration, using cluster analysis,
PRL(25), No. 8, June 2004, pp. 841-847.
WWW Link. 0405
BibRef

Al-Naimi, K., Villette, S., Kondoz, A.M., Heikkinen, A.P.,
Improved line spectral frequency estimation through anti-aliasing filtering,
VISP(153), No. 5, October 2006, pp. 610-617.
DOI Link 0702
BibRef

Kazubek, M.,
Improving local wiener filtering using matched filter,
VISP(153), No. 4, August 2006, pp. 501-506.
WWW Link. 0705
BibRef

Takeuchi, Y.[Yoshinobu], Ooyagi, A.[Akira],
Blind Recover Conditions for Images with Side Information,
IEICE(E90-D), No. 9, September 2007, pp. 1469-1473.
DOI Link 0709
BibRef

Zhang, L.[Lei], Dong, W.S.[Wei-Sheng], Zhang, D.[David], Shi, G.M.[Guang-Ming],
Two-stage image denoising by principal component analysis with local pixel grouping,
PR(43), No. 4, April 2010, pp. 1531-1549.
Elsevier DOI 1002
Denoising; Principal component analysis (PCA); Edge preservation See also Sparsity-based image denoising via dictionary learning and structural clustering. BibRef

Bouboulis, P., Slavakis, K., Theodoridis, S.,
Adaptive Kernel-Based Image Denoising Employing Semi-Parametric Regularization,
IP(19), No. 6, June 2010, pp. 1465-1479.
IEEE DOI 1006
BibRef

Bouboulis, P.[Pantelis], Theodoridis, S.[Sergios], Slavakis, K.[Konstantinos],
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces,
ICPR10(2660-2663).
IEEE DOI 1008
BibRef

Guo, Z., Sun, J., Zhang, D., Wu, B.,
Adaptive Perona-Malik Model Based on the Variable Exponent for Image Denoising,
IP(21), No. 3, March 2012, pp. 958-967.
IEEE DOI 1203
See also Scale Space and Edge Detection using Anisotropic Diffusion. BibRef

Yang, S.M.[Shih-Ming], Tai, S.C.[Shen-Chuan],
A design framework for hybrid approaches of image noise estimation and its application to noise reduction,
JVCIR(23), No. 5, July 2012, pp. 812-826.
Elsevier DOI 1205
Noise estimation; Noise reduction; Image restoration; Image enhancement; Bilateral filter; Non-local mean filter; Laplacian operator; Sobel operator BibRef

Xue, F.[Feng], Luisier, F.[Florian], Blu, T.[Thierry],
Multi-Wiener SURE-LET Deconvolution,
IP(22), No. 5, May 2013, pp. 1954-1968.
IEEE DOI 1303
BibRef
Earlier:
SURE-LET image deconvolution using multiple Wiener filters,
ICIP12(3037-3040).
IEEE DOI 1302
BibRef

Talebi, H.[Hossein], Zhu, X.[Xiang], Milanfar, P.[Peyman],
How to SAIF-ly Boost Denoising Performance,
IP(22), No. 4, April 2013, pp. 1470-1485.
IEEE DOI 1303
BibRef

Talebi, H.[Hossein], Milanfar, P.[Peyman],
Global Image Denoising,
IP(23), No. 2, February 2014, pp. 755-768.
IEEE DOI 1402
BibRef
And:
Global denoising is asymptotically optimal,
ICIP14(818-822)
IEEE DOI 1502
BibRef
Earlier:
Improving denoising filters by optimal diffusion,
ICIP12(1181-1184).
IEEE DOI 1302
Image denoising. approximation theory BibRef

Talebi, H.[Hossein], Milanfar, P.[Peyman],
Asymptotic Performance of Global Denoising,
SIIMS(9), No. 2, 2016, pp. 665-683.
DOI Link 1608
BibRef

Talebi, H.[Hossein], Milanfar, P.[Peyman],
Nonlocal Image Editing,
IP(23), No. 10, October 2014, pp. 4460-4473.
IEEE DOI 1410
edge detection BibRef

Milanfar, P.[Peyman], Talebi, H.[Hossein],
A new class of image filters without normalization,
ICIP16(3294-3298)
IEEE DOI 1610
Brightness BibRef

Hawe, S.[Simon], Kleinsteuber, M.[Martin], Diepold, K.[Klaus],
Analysis Operator Learning and its Application to Image Reconstruction,
IP(22), No. 6, 2013, pp. 2138-2150.
IEEE DOI 1307
conjugate gradient methods; image denoising BibRef

Conte, F., Germani, A., Iannello, G.,
A Kalman Filter Approach for Denoising and Deblurring 3-D Microscopy Images,
IP(22), No. 12, 2013, pp. 5306-5321.
IEEE DOI 1312
Kalman filters BibRef

Peng, H.H.[Hong-Hong], Rao, R.[Raghuveer], Dianat, S.A.[Sohail A.],
Multispectral Image Denoising With Optimized Vector Bilateral Filter,
IP(23), No. 1, January 2014, pp. 264-273.
IEEE DOI 1402
BibRef
Earlier:
Optimized vector bilateral filter for multispectral image denoising,
ICIP12(2141-2144).
IEEE DOI 1302
BibRef
Earlier: A1, A2, Only:
Hyperspectral image enhancement with vector bilateral filtering,
ICIP09(3713-3716).
IEEE DOI 0911
filtering theory BibRef

Liu, Z.[Zhi], Xu, S.Q.[Shu-Qiong], Chen, C.L.P., Zhang, Y.[Yun], Chen, X.[Xin], Wang, Y.N.[Yao-Nan],
A Three-Domain Fuzzy Support Vector Regression for Image Denoising and Experimental Studies,
Cyber(44), No. 4, April 2014, pp. 516-525.
IEEE DOI 1404
convex programming BibRef

Hansen, T.J.[Toke Jansen], Abrahamsen, T.J.[Trine Julie], Hansen, L.K.[Lars Kai],
Denoising by semi-supervised kernel PCA preimaging,
PRL(49), No. 1, 2014, pp. 114-120.
Elsevier DOI 1410
Semi-supervised denoising BibRef

Zhang, T., Gao, Q., Tan, G.,
Texture Preserving Image Restoration with Dyadic Bounded Mean Oscillating Constraints,
SPLetters(22), No. 3, March 2015, pp. 322-326.
IEEE DOI 1410
Adaptation models BibRef

Kheradmand, A., Milanfar, P.,
A General Framework for Regularized, Similarity-Based Image Restoration,
IP(23), No. 12, December 2014, pp. 5136-5151.
IEEE DOI 1412
conjugate gradient methods BibRef

Huang, C.[Chen], Ding, X.Q.[Xiao-Qing], Fang, C.[Chi], Wen, D.[Di],
Robust Image Restoration via Adaptive Low-Rank Approximation and Joint Kernel Regression,
IP(23), No. 12, December 2014, pp. 5284-5297.
IEEE DOI 1412
approximation theory BibRef

Yoo, J.C.[Jae-Chern], Ahn, C.W.[Chang Wook],
Image restoration by blind-Wiener filter,
IET-IPR(8), No. 12, 2014, pp. 815-823.
DOI Link 1412
Wiener filters BibRef

Gupta, V.[Vikas], Chaurasia, V.[Vijayshri], Shandilya, M.[Madhu],
Random-valued impulse noise removal using adaptive dual threshold median filter,
JVCIR(26), No. 1, 2015, pp. 296-304.
Elsevier DOI 1502
Image de-noising BibRef

Zhou, Z.Y.[Zhen-Yu], Guo, Z.C.[Zhi-Chang], Dong, G.[Gang], Sun, J.[Jiebao], Zhang, D.Z.[Da-Zhi], Wu, B.[Boying],
A Doubly Degenerate Diffusion Model Based on the Gray Level Indicator for Multiplicative Noise Removal,
IP(24), No. 1, January 2015, pp. 249-260.
IEEE DOI 1502
image denoising BibRef

Arivazhagan, S., Sugitha, N., Vijay, A.,
A novel image denoising scheme based on fusing multiresolution and spatial filters,
SIViP(9), No. 4, May 2015, pp. 885-892.
WWW Link. 1504
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Fang, X., Xu, Y., Li, X., Lai, Z., Wong, W.K.,
Learning a Nonnegative Sparse Graph for Linear Regression,
IP(24), No. 9, September 2015, pp. 2760-2771.
IEEE DOI 1506
Image reconstruction BibRef

Huang, C.T.[Chao-Tsung],
Bayesian Inference for Neighborhood Filters With Application in Denoising,
IP(24), No. 11, November 2015, pp. 4299-4311.
IEEE DOI 1509
BibRef
Earlier: CVPR15(1657-1665)
IEEE DOI 1510
Bayes methods BibRef

Huang, C.T.[Chao-Tsung],
Fast Distribution Fitting for Parameter Estimation of Range-Weighted Neighborhood Filters,
SPLetters(23), No. 3, March 2016, pp. 331-335.
IEEE DOI 1603
entropy BibRef

Lopes, P.A.C., Gerald, J.A.B., Piedade, M.S.,
The Random Walk Model Kalman Filter in Multichannel Active Noise Control,
SPLetters(22), No. 12, December 2015, pp. 2244-2248.
IEEE DOI 1512
Kalman filters BibRef

Nejati, M.[Mansour], Samavi, S.[Shadrokh], Derksen, H.[Harm], Najarian, K.[Kayvan],
Denoising by low-rank and sparse representations,
JVCIR(36), No. 1, 2016, pp. 28-39.
Elsevier DOI 1603
Image denoising BibRef

Nejati, M.[Mansour], Samavi, S.[Shadrokh], Karimi, N., Soroushmehr, S.M.R.[S.M. Reza], Najarian, K.[Kayvan],
Boosted Dictionary Learning for Image Compression,
IP(25), No. 10, October 2016, pp. 4900-4915.
IEEE DOI 1610
data compression BibRef

Nejati, M.[Mansour], Samavi, S.[Shadrokh], Soroushmehr, S.M.R.[S.M. Reza], Najarian, K.[Kayvan],
Low-rank regularized collaborative filtering for image denoising,
ICIP15(730-734)
IEEE DOI 1512
Image denoising BibRef

Liu, Q.[Qian], Zhang, C.[Caiming], Guo, Q.A.[Qi-Ang], Xu, H.[Hui], Zhou, Y.F.[Yuan-Feng],
Adaptive sparse coding on PCA dictionary for image denoising,
VC(32), No. 4, April 2016, pp. 535-549.
WWW Link. 1604
BibRef

Perrot, G.[Gilles], Domas, S.[Stéphane], Couturier, R.[Raphaël], Bertaux, N.[Nicolas],
Fast GPU-based denoising filter using isoline levels,
RealTimeIP(12), No. 1, June 2016, pp. 31-42.
Springer DOI 1606
BibRef

Coliban, R.M., Ivanovici, M., Richard, N.,
Improved probabilistic pseudo-morphology for noise reduction in colour images,
IET-IPR(10), No. 7, 2016, pp. 505-514.
DOI Link 1608
filtering theory BibRef

Moir, T.J.,
FIR system identification for correlated noise using the convolution matrix, an investigation,
SIViP(10), No. 6, June 2016, pp. 1049-1054.
WWW Link. 1608
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Mbarki, Z.[Zouhair], Seddik, H.[Hassene], Ben Braiek, E.[Ezzedine],
A rapid hybrid algorithm for image restoration combining parametric Wiener filtering and wave atom transform,
JVCIR(40, Part B), No. 1, 2016, pp. 694-707.
Elsevier DOI 1610
Image restoration BibRef

Chen, Y.J.[Yun-Jin], Pock, T.[Thomas],
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration,
PAMI(39), No. 6, June 2017, pp. 1256-1272.
IEEE DOI 1705
Analytical models, Computational modeling, Diffusion processes, Image denoising, Image restoration, Mathematical model, JPEG deblocking, Nonlinear reaction diffusion, image denoising, image super resolution, loss, specific, training BibRef

Chen, Y.J.[Yun-Jin], Yu, W.[Wei], Pock, T.[Thomas],
On learning optimized reaction diffusion processes for effective image restoration,
CVPR15(5261-5269)
IEEE DOI 1510
BibRef


Wong, T.S.[Tak-Shing], Milanfar, P.[Peyman],
Turbo denoising for mobile photographic applications,
ICIP16(988-992)
IEEE DOI 1610
Boosting. Fast and fits on camera. BibRef

Said, A.[Ahmed_Ben], Foufou, S.[Sebti],
Multispectral Image Denoising Using Optimized Vector NLM Filter,
PSIVT15(309-320).
Springer DOI 1602
BibRef

Albarqouni, S.[Shadi], Baust, M.[Maximilian], Conjeti, S.[Sailesh], Al-Amoudi, A.[Asharf], Navab, N.[Nassir],
Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Lu, X.[Xin], Lin, Z.[Zhe], Jin, H.L.[Hai-Lin],
Tree-Based Locally Linear Regression for Image Denoising,
WACV15(472-479)
IEEE DOI 1503
Databases;Noise level;Noise measurement;Noise reduction;PSNR;Training BibRef

Mei, X.[Xing], Qi, H., Hu, B.G.[Bao-Gang], Lyu, S.W.[Si-Wei],
Improving Image Restoration with Soft-Rounding,
ICCV15(459-467)
IEEE DOI 1602
Convolution BibRef

Mei, X.[Xing], Dong, W.M.[Wei-Ming], Hu, B.G.[Bao-Gang], Lyu, S.W.[Si-Wei],
UniHIST: A unified framework for image restoration with marginal histogram constraints,
CVPR15(3753-3761)
IEEE DOI 1510
BibRef
Earlier: A1, A3, A4, Only:
Non-blind image restoration with symmetric generalized Pareto priors,
ICIP14(4477-4481)
IEEE DOI 1502
Computational modeling BibRef

Romano, Y.[Yaniv], Elad, M.[Michael],
Improving K-SVD denoising by post-processing its method-noise,
ICIP13(435-439)
IEEE DOI 1402
Dictionaries BibRef

Menon, S.V.[Sreeram V.], Seelamantula, C.S.[Chandra Sekhar],
Sure-optimal two-dimensional Savitzky-Golay filters for image denoising,
ICIP13(459-463)
IEEE DOI 1402
Approximation methods BibRef

Chen, Y.J.[Yun-Jin], Pock, T.[Thomas], Ranftl, R.[René], Bischof, H.[Horst],
Revisiting Loss-Specific Training of Filter-Based MRFs for Image Restoration,
GCPR13(271-281).
Springer DOI 1311
BibRef

Milani, S.[Simone], Bernardini, R.[Riccardo], Rinaldo, R.[Roberto],
Adaptive denoising filtering for object detection applications,
ICIP12(1013-1016).
IEEE DOI 1302
BibRef

Jancsary, J.[Jeremy], Nowozin, S.[Sebastian], Rother, C.[Carsten],
Loss-Specific Training of Non-Parametric Image Restoration Models: A New State of the Art,
ECCV12(VII: 112-125).
Springer DOI 1210
BibRef

Aswatha, S.M., Mukhopadhyay, J., Bhowmick, P.,
Image Denoising by Scaled Bilateral Filtering,
NCVPRIPG11(122-125).
IEEE DOI 1205
BibRef

Sahu, A.[Anshuman], Runger, G.[George], Apley, D.[Daniel],
Image denoising with a multi-phase kernel principal component approach and an ensemble version,
AIPR11(1-7).
IEEE DOI 1204
BibRef

Tian, H.Y.[Hai-Ying], Cai, H.M.[Hong-Min], Lai, J.H., Xu, X.Y.[Xiao-Yin],
Effective image noise removal based on difference eigenvalue,
ICIP11(3357-3360).
IEEE DOI 1201
BibRef

Trinh, D.H.[Dinh Hoan], Wong, M.[Marie], Rocchisani, J.M.[Jean-Marie], Pham, C.D.[Canh Duong], Dibos, F.[Françoise],
Medical image denoising using Kernel Ridge Regression,
ICIP11(1597-1600).
IEEE DOI 1201
BibRef
And:
Adaptive Medical Image Denoising Using Support Vector Regression,
CAIP11(I: 494-502).
Springer DOI 1109
BibRef

Hantos, N.[Norbert], Balázs, P.[Péter],
A Fast Algorithm for Reconstructing hv-Convex Binary Images from Their Horizontal Projection,
ISVC14(II: 789-798).
Springer DOI 1501
BibRef
And:
Fast Heuristics for Eliminating Switching Components in Binary Matrices by 0-1 Flips,
CIARP14(62-69).
Springer DOI 1411
BibRef
Earlier:
Reconstruction and Enumeration of hv-Convex Polyominoes with Given Horizontal Projection,
CIARP13(I:100-107).
Springer DOI 1311
BibRef

Hantos, N.[Norbert], Balázs, P.[Péter], Palágyi, K.[Kálmán],
Binary Image Reconstruction from Two Projections and Skeletal Information,
IWCIA12(263-273).
Springer DOI 1211
BibRef

Hantos, N.[Norbert], Balázs, P.[Péter],
Image Enhancement by Median Filters in Algebraic Reconstruction Methods: An Experimental Study,
ISVC10(III: 339-348).
Springer DOI 1011
BibRef

Coulange, B.[Baptiste], Moisan, L.[Lionel],
An aliasing detection algorithm based on suspicious colocalizations of Fourier coefficients,
ICIP10(2013-2016).
IEEE DOI 1009
BibRef

Schoberl, M.[Michael], Schnurrer, W.[Wolfgang], Oberdorster, A.[Alexander], Fossel, S.[Siegfried], Kaup, A.[Andre],
Dimensioning of optical birefringent anti-alias filters for digital cameras,
ICIP10(4305-4308).
IEEE DOI 1009
BibRef

Rajwade, A.[Ajit], Rangarajan, A.[Anand], Banerjee, A.[Arunava],
Automated Filter Parameter Selection Using Measures of Noiseness,
CRV10(86-93).
IEEE DOI 1005
Automatic choice of parameters for optimal response. BibRef

Sezer, O.G.[Osman G.], Altunbasak, Y.[Yucel],
Weighted average denoising with Sparse Orthonormal Transforms,
ICIP09(3849-3852).
IEEE DOI 0911
BibRef

Wang, L.[Lei], Zou, Y.K.[Yun-Kang], Zhang, H.J.[Hong-Jun],
A Medical Image Denoising Arithmetic Based on Wiener Filter Parallel Model of Wavelet Transform,
CISP09(1-4).
IEEE DOI 0910
BibRef

Li, H.Y.[Hong-Yan], Zhao, Q.H.[Qing-Hua], Zhao, J.Q.[Jing-Qing], Xiao, B.J.[Bao-Jin],
Blind Separation of Noisy Mixed Images Based on Wiener Filtering and Independent Component Analysis,
CISP09(1-5).
IEEE DOI 0910
BibRef

Lou, Y.F.[Yi-Fei], Favaro, P.[Paolo], Soatto, S.[Stefano], Bertozzi, A.L.[Andrea L.],
Nonlocal Similarity Image Filtering,
CIAP09(62-71).
Springer DOI 0909
Filters to find similar features at different location, orientation, scale. Apply to denoising. BibRef

Baek, Y.M.[Yeul-Min], Kim, J.G.[Joong-Geun], Cho, D.C.[Dong-Chan], Lee, J.A.[Jin-Aeon], Kim, W.Y.[Whoi-Yul],
Integrated Noise Modeling for Image Sensor Using Bayer Domain Images,
MIRAGE09(413-424).
Springer DOI 0905
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Wen, Y.W.[You-Wei], Ng, M.[Michael], Ching, W.K.[Wai-Ki],
CIDER: Corrected Inverse-Denoising Filter for Image Restoration,
EMMCVPR07(112-126).
Springer DOI 0708
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Liu, Q.S.[Qing-Shan], Cheng, J.[Jian], Lu, H.Q.[Han-Qing], Ma, S.D.[Song-De],
Distance based kernel PCA image reconstruction,
ICPR04(III: 670-673).
IEEE DOI 0409
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Jin, E., Fieguth, P.W., Winger, L., Jernigan, E.,
Adaptive Wiener filtering of noisy images and image sequences,
ICIP03(III: 349-352).
IEEE DOI 0312
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Sugiyama, M., Imaizumi, D., Ogawa, H.,
Subspace Information Criterion for Image Restoration: Mean Squared Error Estimatior for Linear Filters,
SCIA01(O-M5B). 0206
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Rodriguez-Florido, M., Ruiz-Alzola, J., Westin, C.F.,
Artifact Reduction in Sinc Interpolation Using Adaptive Filtering,
ICIP01(III: 884-887).
IEEE DOI 0108
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Shcherbakov, M.[Michael],
Pareto optimal nonlinear filters for image enhancement,
ICIP96(I: 769-772).
IEEE DOI BibRef 9600

Chen, Z.Y.[Zhong-Yu], Desai, M.,
Multiple-valued feedback neural networks for image restoration,
ICIP96(I: 753-756).
IEEE DOI 9610
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Kotropoulos, C.[Constantine], Pitas, I., Gabrani, M.,
Multichannel adaptive L-filters in color image filtering,
ICIP96(I: 989-992).
IEEE DOI BibRef 9600

Gabrani, M., Kotropoulos, C., Pitas, I.,
Cellular LMS L-filters for noise suppression in still images and image sequences,
ICIP94(I: 358-362).
IEEE DOI 9411
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Beaudot, W.H.A.[William H.A.],
Adaptive Spatiotemporal Filtering by a Neuromorphic Model of the Vertebrate Retina,
ICIP96(I: 427-430).
IEEE DOI BibRef 9600

Stajniak, A., Szostakowski, J.,
Neural implementation of ARMA type filters for image restoration,
ICIP95(II: 520-522).
IEEE DOI 9510
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Tan, B.H.[Beng-Heok], Wahah, A., Tan, E.C.[Eng-Chong],
A neural approach to optical image reconstruction,
ICIP95(II: 531-534).
IEEE DOI 9510
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Kashyap, R.L.,
A robust variable length nonlinear filter for edge enhancement and noise smoothing,
ICPR94(C:143-145).
IEEE DOI 9410
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Moody, E.B.,
Discrete orthogonal polynomial restoration of images degraded by spatially varying point spread functions,
ICIP94(II: 680-684).
IEEE DOI 9411
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Selkainaho, K.,
A one-parametric reduced filter for image restoration,
ICPR94(C:68-71).
IEEE DOI 9410
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Suesse, H., Voss, K.,
Inversion of convolution by small kernels,
CAIP93(123-127).
Springer DOI 9309
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Swiniarski, R., Butler, M.P.,
Neural recurrent estimator to gray scale image restoration based on 2D Kalman filtering,
ICPR92(III:425).
IEEE DOI 9208
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Lonnestad, T.,
Connected filters for noise removal,
ICPR88(II: 848-850).
IEEE DOI 8811
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Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Image Reconstruction .


Last update:Jun 24, 2017 at 21:08:28