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Deep convolutional neural networks perform better on images containing spatially invariant noise (synthetic noise); however, their performance is limited on real-noisy photographs and requires multiple stage network modeling.
Digital image processing (book)
Rafael C Gonzalez and Paul Wintz · 1977
Earlier work this paper cites.
Learning long-term dependencies with gradient descent is difficult
Yoshua Bengio, Patrice Simard, and Paolo Frasconi · 1994
Earlier work this paper cites.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
D. Martin, C. Fowlkes, D. Tal, and J. Malik · 2001
Earlier work this paper cites.
A non-local algorithm for image denoising
Antoni Buades, Bartomeu Coll, and Jean-Michel Morel · 2005
Earlier work this paper cites.
An iterative regularization method for total variation-based image restoration
Stanley Osher, Martin Burger, Donald Goldfarb, Jinjun Xu, and Wotao Yin · 2005
Earlier work this paper cites.
K-svd: An algorithm for designing overcomplete dictionaries for sparse representation
Michal Aharon, Michael Elad, and Alfred Bruckstein · 2006
Earlier work this paper cites.
Image denoising by sparse 3-D transform-domain collaborative filtering
Kostadin Dabov, Alessandro F., Vladimir Katkovnik, and Karen Egiazarian · 2007
Earlier work this paper cites.
Color image denoising via sparse 3-D collaborative filtering with grouping constraint in luminance-chrominance space
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
Earlier work this paper cites.
Pointwise shape-adaptive DCT for high-quality denoising and deblocking of grayscale and color images
Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
Earlier work this paper cites.
What makes a good model of natural images?
Yair Weiss and William T Freeman · 2007
Earlier work this paper cites.
Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising
Jinjun Xu and Stanley Osher · 2007
Earlier work this paper cites.
Persistent homology-a survey
Herbert Edelsbrunner and John Harer · 2008
Earlier work this paper cites.
An improved non-local denoising algorithm
Bart Goossens, Hiêp Luong, Aleksandra Pizurica, and Wilfried Philips · 2008
Earlier work this paper cites.
BM3D image denoising with shape-adaptive principal component analysis
K. Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2009
Earlier work this paper cites.
Example-based regularization deployed to super-resolution reconstruction of a single image
Michael Elad and Dmitry Datsenko · 2009
Earlier work this paper cites.
Non-local sparse models for image restoration
Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, and Andrew Zisserman · 2009
Earlier work this paper cites.
Fields of experts
Stefan Roth and Michael J Black · 2009
Earlier work this paper cites.
Fast image recovery using variable splitting and constrained optimization
Manya V Afonso, José M Bioucas-Dias, and Mário AT Figueiredo · 2010
Earlier work this paper cites.
Is denoising dead?
P. Chatterjee and P. Milanfar · 2010
Earlier work this paper cites.
Learning photographic global tonal adjustment with a database of input/output image pairs
Vladimir Bychkovsky, Sylvain Paris, Eric Chan, and Frédo Durand · 2011
Earlier work this paper cites.
Sparsity-based image denoising via dictionary learning and structural clustering
Weisheng Dong, Xin Li, D. Zhang, and Guangming Shi · 2011
Earlier work this paper cites.
Natural image denoising: Optimality and inherent bounds
A. Levin and B. Nadler · 2011
Earlier work this paper cites.
From learning models of natural image patches to whole image restoration
Daniel Zoran and Yair Weiss · 2011
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Image denoising: Can plain neural networks compete with bm3d?
Harold Christopher Burger, Christian J Schuler, and Stefan Harmeling · 2012
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Nonlocally centralized sparse representation for image restoration
Weisheng Dong, Lei Zhang, Guangming Shi, and Xin Li · 2012
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Rasl: Robust alignment by sparse and low-rank decomposition for linearly correlated images
Yigang Peng, Arvind Ganesh, John Wright, Wenli Xu, and Yi Ma · 2012
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A nonlocal bayesian image denoising algorithm
M Lebrun, Antoni Buades, and Jean-Michel Morel · 2013
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Weighted nuclear norm minimization with application to image denoising
Shuhang Gu, Lei Zhang, Wangmeng Zuo, and Xiangchu Feng · 2014
Chaining identity mapping modules for image denoising
Saeed Anwar, Cong Phouc Huynh, and Fatih Porikli · 2017
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Category-specific object image denoising
Saeed Anwar, Fatih Porikli, and Cong Phuoc Huynh · 2017
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Beyond deep residual learning for image restoration: Persistent homology-guided manifold simplification
Woong Bae, Jaejun Yoo, and Jong Chul Ye · 2017
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Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Yunjin Chen and Thomas Pock · 2017
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Formresnet: Formatted residual learning for image restoration
Jianbo Jiao, Wei-Chih Tu, Shengfeng He, and Rynson WH Lau · 2017
Later among the works it cites.
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Flexisp: A flexible camera image processing framework
Felix Heide, Markus Steinberger, Yun-Ta Tsai, Mushfiqur Rouf, Dawid Pajak, Dikpal Reddy, Orazio Gallo, Jing Liu, Wolfgang Heidrich, Karen Egiazarian, et al · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Shrinkage fields for effective image restoration
Uwe Schmidt and Stefan Roth · 2014
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Cid: Combined image denoising in spatial and frequency domains using web images
H. Yue, X. Sun, J. Yang, and F. Wu · 2014
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External Patch Prior Guided Internal Clustering for Image Denoising
L. Zhang F. Chen and H. Yu · 2015
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The noise clinic: a blind image denoising algorithm
Marc Lebrun, Miguel Colom, and Jean-Michel Morel · 2015
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Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Benchmarking denoising algorithms with real photographs
Tobias Plötz and Stefan Roth · 2017
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The little engine that could: Regularization by denoising (red)
Yaniv Romano, Michael Elad, and Peyman Milanfar · 2017
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Multi-channel weighted nuclear norm minimization for real color image denoising
Jun Xu, Lei Zhang, David Zhang, and Xiangchu Feng · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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Learning deep cnn denoiser prior for image restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, and Lei Zhang · 2017
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A high-quality denoising dataset for smartphone cameras
Abdelrahman Abdelhamed, Stephen Lin, and Michael S Brown · 2018
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Renoir–a dataset for real low-light image noise reduction
Josue Anaya and Adrian Barbu · 2018
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Toward convolutional blind denoising of real photographs
Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Neural nearest neighbors networks
Tobias Plötz and Stefan Roth · 2018
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Real-world noisy image denoising: A new benchmark
Jun Xu, Hui Li, Zhetong Liang, David Zhang, and Lei Zhang · 2018
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A trilateral weighted sparse coding scheme for real-world image denoising
Jun Xu, Lei Zhang, and David Zhang · 2018
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Ffdnet: Toward a fast and flexible solution for cnn-based image denoising
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
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Image super-resolution using very deep residual channel attention networks
Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, and Yun Fu · 2018
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Unprocessing images for learned raw denoising
Tim Brooks, Ben Mildenhall, Tianfan Xue, Jiawen Chen, Dillon Sharlet, and Jonathan T Barron · 2019
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