*Zhou, Y.T.*,
*Chellappa, R.*, and
*Jenkins, B.K.*,

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*ASSP(36)*, July 1988, pp. 1141-1151.
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*Figueiredo, M.A.T.*,
*Leitao, J.M.N.*,

**Sequential and Parallel Image Restoration:
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*IP(3)*, No. 6, November 1994, pp. 789-801.

IEEE DOI
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**Adaptive discontinuity location in image restoration**,

*ICIP94*(II: 665-669).

IEEE DOI
**9411**

BibRef

*Wong, H.S.[Hau-San]*,
*Guan, L.[Ling]*,

**Adaptive Regularization in Image Restoration Using a
Model Based Neural Network**,

*OptEng(36)*, No. 12, December 1997, pp. 3297-3308.
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*Wong, H.S.[Hau-San]*,
*Guan, L.[Ling]*,

**Adaptive Regularization in Image Restoration by Unsupervised Learning**,

*JEI(7)*, No. 1, January 1998, pp. 211-221.
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And:

**A Fuzzy Model-based Neural Network for Adaptive Regularization in Image
Restoration**,

*ICIP99*(I:391-395).

IEEE DOI
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*Leitao, J.M.N.*,
*Figueiredo, M.A.T.*,

**Absolute Phase Image-Reconstruction:
A Stochastic Nonlinear Filtering Approach**,

*IP(7)*, No. 6, June 1998, pp. 868-882.

IEEE DOI
**9806**

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*Wang, Y.*,
*Wahl, F.M.*,

**Multiobjective Neural Network for Image Reconstruction**,

*VISP(144)*, No. 4, August 1997, pp. 233-236.
**9806**

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*Sun, Y.[Yi]*,
*Li, J.G.[Jie-Gu]*,
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**Improvement on performance of modified Hopfield neural network for
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*IP(4)*, No. 5, May 1995, pp. 688-692.

IEEE DOI
**0402**

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*Wang, Y.M.[Yuan-Mei]*,

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*IJIST(9)*, No. 5, 1999, pp. 381-387.
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*Woo, W.L.*,
*Khor, L.C.*,

**Blind restoration of nonlinearly mixed signals using multilayer
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*Woo, W.L.*,
*Dlay, S.S.*,

**Regularised nonlinear blind signal separation using sparsely connected
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*Woo, W.L.*,
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**Nonlinear blind source separation using a hybrid RBF-FMLP network**,

*VISP(152)*, No. 2, April 2005, pp. 173-183.

DOI Link
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*Khor, L.C.*,
*Woo, W.L.*,
*Dlay, S.S.*,

**Nonlinear blind signal separation with intelligent controlled learning**,

*VISP(152)*, No. 3, June 2005, pp. 297-306.

DOI Link
**0510**

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*Wei, C.*,
*Woo, W.L.*,
*Dlay, S.S.*,
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**Maximum a posteriori-based approach to blind nonlinear underdetermined
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**An Edge-Preserving Image Reconstruction Using Neural Network**,

*JMIV(14)*, No. 2, March 2001, pp. 117-130.

DOI Link
**0106**

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*Wang, Y.Q.[Yi-Qing]*,
*Morel, J.M.[Jean-Michel]*,

**Can a Single Image Denoising Neural Network Handle All Levels of
Gaussian Noise?**,

*SPLetters(21)*, No. 9, Sept 2014, pp. 1150-1153.

IEEE DOI
**1406**

See also SURE Guided Gaussian Mixture Image Denoising. Gaussian noise
BibRef

*Wang, Y.Q.[Yi-Qing]*,

**A Note on the Size of Denoising Neural Networks**,

*SIIMS(9)*, No. 1, 2016, pp. 275-286.

DOI Link
**1604**

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*Wang, Y.Q.[Yi-Qing]*,

**Small Neural Networks can Denoise Image Textures Well:
A Useful Complement to BM3D**,

*IPOL(6)*, 2016, pp. 1-7.

DOI Link
**1601**

See also Image denoising: Can plain neural networks compete with BM3D?.
See also Analysis and Implementation of the BM3D Image Denoising Method, Image Processing, An.
See also Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing, A.
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*Lyu, G.[Guohao]*,
*Yin, H.[Hui]*,
*Yu, X.[Xinyan]*,
*Luo, S.W.[Si-Wei]*,

**A Local Characteristic Image Restoration Based on Convolutional Neural
Network**,

*IEICE(E99-D)*, No. 8, August 2016, pp. 2190-2193.

WWW Link.
**1608**

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*Zhang, K.[Kai]*,
*Zuo, W.M.[Wang-Meng]*,
*Chen, Y.J.[Yun-Jin]*,
*Meng, D.Y.[De-Yu]*,
*Zhang, L.[Lei]*,

**Beyond a Gaussian Denoiser:
Residual Learning of Deep CNN for Image Denoising**,

*IP(26)*, No. 7, July 2017, pp. 3142-3155.

IEEE DOI
**1706**

Computational modeling, Image denoising, Neural networks,
Noise level, Noise reduction, Training, Transform coding,
Image denoising, batch normalization,
convolutional neural networks, residual, learning
BibRef

*Zhang, K.[Kai]*,
*Zuo, W.M.[Wang-Meng]*,
*Zhang, L.[Lei]*,

**FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image
Denoising**,

*IP(27)*, No. 9, September 2018, pp. 4608-4622.

IEEE DOI
**1807**

image denoising, image sampling,
learning (artificial intelligence), neural nets,
spatially variant noise
See also Analysis and Implementation of the FFDNet Image Denoising Method, An.
BibRef

*Zhang, K.[Kai]*,
*Zuo, W.M.[Wang-Meng]*,
*Gu, S.*,
*Zhang, L.[Lei]*,

**Learning Deep CNN Denoiser Prior for Image Restoration**,

*CVPR17*(2808-2817)

IEEE DOI
**1711**

Image restoration, Inverse problems, Learning systems,
Noise reduction, Optimization, methods
BibRef

*Zhang, F.[Fu]*,
*Cai, N.[Nian]*,
*Wu, J.X.[Ji-Xiu]*,
*Cen, G.D.[Guan-Dong]*,
*Wang, H.[Han]*,
*Chen, X.D.[Xin-Du]*,

**Image denoising method based on a deep convolution neural network**,

*IET-IPR(12)*, No. 4, April 2018, pp. 485-493.

DOI Link
**1804**

BibRef

*Yin, J.*,
*Chen, B.*,
*Li, Y.*,

**Highly Accurate Image Reconstruction for Multimodal Noise Suppression
Using Semisupervised Learning on Big Data**,

*MultMed(20)*, No. 11, November 2018, pp. 3045-3056.

IEEE DOI
**1810**

Image reconstruction, Noise measurement, Streaming media,
Cost function, Semisupervised learning, Big Data, Imaging,
semisupervised learning
BibRef

*Tassano, M.[Matias]*,
*Delon, J.[Julie]*,
*Veit, T.[Thomas]*,

**An Analysis and Implementation of the FFDNet Image Denoising Method**,

*IPOL(9)*, 2019, pp. 1-25.

DOI Link
**1901**

*Code, Noise Removal*.
See also FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising.
BibRef

*Xu, W.J.[Wen-Jia]*,
*Xu, G.L.[Guang-Luan]*,
*Wang, Y.[Yang]*,
*Sun, X.[Xian]*,
*Lin, D.[Daoyu]*,
*Wu, Y.R.[Yi-Rong]*,

**Deep Memory Connected Neural Network for Optical Remote Sensing Image
Restoration**,

*RS(10)*, No. 12, 2018, pp. xx-yy.

DOI Link
**1901**

BibRef

*Cho, S.I.*,
*Kang, S.*,

**Gradient Prior-Aided CNN Denoiser With Separable Convolution-Based
Optimization of Feature Dimension**,

*MultMed(21)*, No. 2, February 2019, pp. 484-493.

IEEE DOI
**1902**

Convolution, Noise reduction, Image denoising, Feature extraction,
Training, Noise measurement, Indexes, Image denoising,
image noise
BibRef

*Xue, H.Z.[Hong-Zhi]*,
*Cui, H.W.[Hong-Wei]*,

**Research on image restoration algorithms based on BP neural network**,

*JVCIR(59)*, 2019, pp. 204-209.

Elsevier DOI
**1903**

Image restoration, Image processing, Image denoising, BP neural network
BibRef

*Shi, W.Z.[Wu-Zhen]*,
*Jiang, F.[Feng]*,
*Zhang, S.P.[Sheng-Ping]*,
*Wang, R.[Rui]*,
*Zhao, D.B.[De-Bin]*,
*Zhou, H.Y.[Hui-Yu]*,

**Hierarchical residual learning for image denoising**,

*SP:IC(76)*, 2019, pp. 243-251.

Elsevier DOI
**1906**

Image denoising, Convolutional neural network,
Residual learning, Hierarchical residual learning, Multi-scale information
BibRef

*Shin, S.Y.[Soo-Yeon]*,
*Kim, D.M.[Dong-Myung]*,
*Suh, J.W.[Jae-Won]*,

**Image Denoiser Using Convolutional Neural Network with Deconvolution
and Modified Residual Network**,

*IEICE(E102-D)*, No. 8, August 2019, pp. 1598-1601.

WWW Link.
**1908**

BibRef

*Dong, W.S.[Wei-Sheng]*,
*Wang, P.Y.[Pei-Yao]*,
*Yin, W.T.[Wo-Tao]*,
*Shi, G.M.[Guang-Ming]*,
*Wu, F.F.[Fang-Fang]*,
*Lu, X.T.[Xiao-Tong]*,

**Denoising Prior Driven Deep Neural Network for Image Restoration**,

*PAMI(41)*, No. 10, October 2019, pp. 2305-2318.

IEEE DOI
**1909**

Task analysis, Noise reduction, Image restoration, Optimization,
Image resolution, Neural networks, Iterative algorithms,
image restoration
BibRef

*Wang, F.*,
*Huang, H.*,
*Liu, J.*,

**Variational-Based Mixed Noise Removal With CNN Deep Learning
Regularization**,

*IP(29)*, No. , 2020, pp. 1246-1258.

IEEE DOI
**1911**

Deep learning, Noise reduction, Image restoration,
Learning systems, TV, Data models, Deep learning, CNN, regularization,
image restoration
BibRef

*Jiang, Y.*,
*Li, H.*,
*Rangaswamy, M.*,

**Deep Learning Denoising Based Line Spectral Estimation**,

*SPLetters(26)*, No. 11, November 2019, pp. 1573-1577.

IEEE DOI
**1911**

convolutional neural nets, learning (artificial intelligence),
minimisation, signal denoising, deep learning
BibRef

*Thakur, R.S.[Rini Smita]*,
*Yadav, R.N.[Ram Narayan]*,
*Gupta, L.[Lalita]*,

**State-of-art analysis of image denoising methods using convolutional
neural networks**,

*IET-IPR(13)*, No. 13, November 2019, pp. 2367-2380.

DOI Link
**1911**

BibRef

*Qu, C.*,
*Moiseikin, M.*,
*Voth, S.*,
*Beyerer, J.[Jurgen]*,

**CNN-based Image Denoising for Outdoor Active Stereo**,

*MVA19*(1-6)

DOI Link
**1911**

computer vision, convolutional neural nets, image denoising,
image matching, image reconstruction, image texture,
Adaptive equalizers
BibRef

*Somasundaran, B.V.[Biju Venkadath]*,
*Soundararajan, R.[Rajiv]*,
*Biswas, S.[Soma]*,

**Robust image retrieval by cascading a deep quality assessment network**,

*SP:IC(80)*, 2020, pp. 115652.

Elsevier DOI
**1912**

BibRef

Earlier:

**Image Denoising for Image Retrieval by Cascading a Deep Quality
Assessment Network**,

*ICIP18*(525-529)

IEEE DOI
**1809**

Image enhancement, Image quality assessment,
Deep convolutional neural network, Denoising, Image retrieval.
Noise reduction, Image denoising, Image quality,
Noise measurement, Training.
BibRef

*Guo, Y.C.[Yong-Cun]*,
*Jia, X.F.[Xiao-Fen]*,
*Zhao, B.T.[Bai-Ting]*,
*Chai, H.R.[Hua-Rong]*,
*Huang, Y.R.[You-Rui]*,

**Multifeature extracting CNN with concatenation for image denoising**,

*SP:IC(81)*, 2020, pp. 115690.

Elsevier DOI
**1912**

BibRef

*Ma, R.*,
*Hu, H.*,
*Xing, S.*,
*Li, Z.*,

**Efficient and Fast Real-World Noisy Image Denoising by Combining
Pyramid Neural Network and Two-Pathway Unscented Kalman Filter**,

*IP(29)*, 2020, pp. 3927-3940.

IEEE DOI
**2002**

Image prior, real-world noisy image denoising, pyramid network,
two-pathway unscented Kalman filter
BibRef

*Spigler, G.[Giacomo]*,

**Denoising Autoencoders for Overgeneralization in Neural Networks**,

*PAMI(42)*, No. 4, April 2020, pp. 998-1004.

IEEE DOI
**2003**

Training, Neural networks, Computational modeling, Noise reduction,
Data models, Support vector machines, Mars, Overgeneralization,
neural networks
BibRef

*Yang, X.*,
*Xu, Y.*,
*Quan, Y.*,
*Ji, H.*,

**Image Denoising via Sequential Ensemble Learning**,

*IP(29)*, 2020, pp. 5038-5049.

IEEE DOI
**2003**

Image denoising, Noise reduction, Machine learning, Transforms,
Noise measurement, Iterative methods, Manifolds, Image denoising,
ensemble denoiser
BibRef

*Jin, Z.*,
*Iqbal, M.Z.*,
*Bobkov, D.*,
*Zou, W.*,
*Li, X.*,
*Steinbach, E.*,

**A Flexible Deep CNN Framework for Image Restoration**,

*MultMed(22)*, No. 4, April 2020, pp. 1055-1068.

IEEE DOI
**2004**

Training, Image restoration, Image coding, Automobiles,
Task analysis, Transform coding, Image denoising, residual learning
BibRef

*Wen, B.*,
*Li, Y.*,
*Bresler, Y.*,

**Image Recovery via Transform Learning and Low-Rank Modeling:
The Power of Complementary Regularizers**,

*IP(29)*, 2020, pp. 5310-5323.

IEEE DOI
**2004**

Transforms, Image denoising, Adaptation models, Image restoration,
Image reconstruction, Magnetic resonance imaging,
machine learning
BibRef

*Xiang, Q.[Qian]*,
*Peng, L.[Likun]*,
*Pang, X.L.[Xue-Liang]*,

**Image DAEs based on residual entropy maximum**,

*IET-IPR(14)*, No. 6, 11 May 2020, pp. 1164-1169.

DOI Link
**2005**

denoising auto-encoders. Learn mapping from noisy to target image.
BibRef

*Jiao, J.B.[Jian-Bo]*,
*Tu, W.C.[Wei-Chih]*,
*Liu, D.[Ding]*,
*He, S.F.[Sheng-Feng]*,
*Lau, R.W.H.[Rynson W. H.]*,
*Huang, T.S.[Thomas S.]*,

**FormNet: Formatted Learning for Image Restoration**,

*IP(29)*, 2020, pp. 6302-6314.

IEEE DOI
**2005**

BibRef

Earlier: A1, A2, A4, A5, Only:

**FormResNet: Formatted Residual Learning for Image Restoration**,

*NTIRE17*(1034-1042)

IEEE DOI
**1709**

Image restoration, Task analysis, Noise reduction, Training,
Visualization, Noise measurement, Image reconstruction, CNN.
Image reconstruction, Image resolution, Neural networks.
BibRef

IEEE DOI

feature extraction, image denoising, image resolution, image restoration, neural nets, PSNR, self-guided network, Image denoising BibRef

*Izadi, S.*,
*Mirikharaji, Z.*,
*Zhao, M.*,
*Hamarneh, G.*,

**WhiteNNer-Blind Image Denoising via Noise Whiteness Priors**,

*VRMI19*(476-484)

IEEE DOI
**2004**

Noise measurement, Image denoising, Noise reduction,
Image reconstruction, Training, Biomedical imaging, deep learning,
blind image denoising
BibRef

*Brooks, T.[Tim]*,
*Mildenhall, B.[Ben]*,
*Xue, T.F.[Tian-Fan]*,
*Chen, J.[Jiawen]*,
*Sharlet, D.[Dillon]*,
*Barron, J.T.[Jonathan T.]*,

**Unprocessing Images for Learned Raw Denoising**,

*CVPR19*(11028-11037).

IEEE DOI
**2002**

BibRef

*Krull, A.[Alexander]*,
*Buchholz, T.O.[Tim-Oliver]*,
*Jug, F.[Florian]*,

**Noise2Void - Learning Denoising From Single Noisy Images**,

*CVPR19*(2124-2132).

IEEE DOI
**2002**

BibRef

*Zou, H.*,
*Lan, R.*,
*Zhong, Y.*,
*Liu, Z.*,
*Luo, X.*,

**EDCNN: A Novel Network for Image Denoising**,

*ICIP19*(1129-1133)

IEEE DOI
**1910**

Image denoising, residual learning, convolutional neural network,
residual excitation
BibRef

*Mukherjee, S.[Subhayan]*,
*Kottayil, N.K.[Navaneeth Kamballur]*,
*Sun, X.[Xinyao]*,
*Cheng, I.[Irene]*,

**CNN-Based Real-Time Parameter Tuning for Optimizing Denoising Filter
Performance**,

*ICIAR19*(I:112-125).

Springer DOI
**1909**

BibRef

*Ren, H.[Haoyu]*,
*El-khamy, M.[Mostafa]*,
*Lee, J.[Jungwon]*,

**DN-ResNet: Efficient Deep Residual Network for Image Denoising**,

*ACCV18*(V:215-230).

Springer DOI
**1906**

BibRef

*Yu, K.*,
*Dong, C.*,
*Lin, L.*,
*Loy, C.C.*,

**Crafting a Toolchain for Image Restoration by Deep Reinforcement
Learning**,

*CVPR18*(2443-2452)

IEEE DOI
**1812**

Image restoration, Tools, Distortion, Task analysis,
Transform coding, Complexity theory
BibRef

*Lefkimmiatis, S.*,

**Universal Denoising Networks:
A Novel CNN Architecture for Image Denoising**,

*CVPR18*(3204-3213)

IEEE DOI
**1812**

Image restoration, Noise level, Distortion, Image denoising,
Training, Noise reduction, Transforms
BibRef

*Ryu, J.*,
*Kim, Y.*,

**Conditional Distribution Learning with Neural Networks and its
Application to Universal Image Denoising**,

*ICIP18*(3214-3218)

IEEE DOI
**1809**

Neural networks, Noise reduction, Noise measurement,
Context modeling, Gray-scale, Boats, Training, Universal denoising,
plug-in approach
BibRef

*Song, P.*,
*Rodrigues, M.R.D.*,

**Multimodal Image Denoising Based on Coupled Dictionary Learning**,

*ICIP18*(515-519)

IEEE DOI
**1809**

Dictionaries, Image denoising, Machine learning, Training,
Noise reduction, Noise measurement, Image reconstruction,
guidance information
BibRef

*Li, Y.*,
*Zhang, B.*,
*Florent, R.*,

**Understanding neural-network denoisers through an activation function
perspective**,

*ICIP17*(2971-2975)

IEEE DOI
**1803**

Biological neural networks, Image denoising, Kernel,
Noise measurement, Noise reduction, Training, Activation function,
Neural network denoising
BibRef

*Li, J.J.[Jian-Jun]*,
*Xu, L.L.[Lan-Lan]*,
*Li, H.J.[Hao-Jie]*,
*Chang, C.C.[Chin-Chen]*,
*Sun, F.M.[Fu-Ming]*,

**Parameter Selection for Denoising Algorithms Using NR-IQA with CNN**,

*MMMod18*(I:381-392).

Springer DOI
**1802**

BibRef

*Gao, R.*,
*Grauman, K.[Kristen]*,

**On-demand Learning for Deep Image Restoration**,

*ICCV17*(1095-1104)

IEEE DOI
**1802**

convolution, image denoising, image restoration, interpolation,
learning (artificial intelligence), neural nets,
Training
BibRef

*Chaudhury, S.*,
*Roy, H.*,

**Can fully convolutional networks perform well for general image
restoration problems?**,

*MVA17*(254-257)

DOI Link
**1708**

Convolution, Image denoising, Image reconstruction,
Image restoration, Image segmentation, Noise measurement, Training
BibRef

*Divakar, N.*,
*Babu, R.V.*,

**Image Denoising via CNNs: An Adversarial Approach**,

*NTIRE17*(1076-1083)

IEEE DOI
**1709**

Feature extraction, Generators, Image denoising,
Image reconstruction, Noise measurement, Noise reduction, Training
BibRef

*Koziarski, M.[Michal]*,
*Cyganek, B.[Boguslaw]*,

**Deep Neural Image Denoising**,

*ICCVG16*(163-173).

Springer DOI
**1611**

BibRef

*Mejía-Lavalle, M.[Manuel]*,
*Ortiz, E.[Estela]*,
*Mújica, D.[Dante]*,
*Ruiz, J.[José]*,
*Reyes, G.[Gerardo]*,

**An Effective Image De-noising Alternative Approach Based on Third
Generation Neural Networks**,

*MCPR16*(64-73).

Springer DOI
**1608**

BibRef

*Jiang, M.Y.[Ming-Yong]*,
*Chen, X.N.[Xiang-Ning]*,
*Yu, X.Q.[Xia-Qiong]*,

**Adaptive Sub-Optimal Hopfield Neural Network image restoration base on
edge detection**,

*IASP11*(364-367).

IEEE DOI
**1112**

BibRef

*Bernues, E.*,
*Cisneros, G.*,
*Capella, M.*,

**Truncated edges estimation using MLP neural nets applied to regularized
image restoration**,

*ICIP02*(I: 341-344).

IEEE DOI
**0210**

BibRef

*Chen, Z.Y.[Zhong-Yu]*,
*Desai, M.*,

**Multiple-valued feedback neural networks for image restoration**,

*ICIP96*(I: 753-756).

IEEE DOI
**9610**

BibRef

*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**

BibRef

*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**

BibRef

*Muneyasu, M.*,
*Yamamoto, K.*,
*Hinamoto, T.*,

**Image restoration using layered neural networks and Hopfield networks**,

*ICIP95*(II: 33-36).

IEEE DOI
**9510**

BibRef

*Swiniarski, R.*,
*Butler, M.P.*,

**Neural recurrent estimator to gray scale image restoration based on 2D
Kalman filtering**,

*ICPR92*(III:425).

IEEE DOI
**9208**

BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in

Noise Removal, Denoising .

Last update:Jul 10, 2020 at 16:03:35