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In this paper we introduce a natural image prior that directly represents a Gaussian-smoothed version of the natural image distribution.
Nonlinear total variation based noise removal algorithms
Leonid I. Rudin, Stanley Osher, and Emad Fatemi · 1992
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Mean shift: A robust approach toward feature space analysis
Dorin Comaniciu and Peter Meer · 2002
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Image denoising using scale mixtures of gaussians in the wavelet domain
J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli · 2003
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High-quality linear interpolation for demosaicing of bayer-patterned color images
Henrique S Malvar, Li-wei He, and Ross Cutler · 2004
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A non-local algorithm for image denoising
Antoni Buades, Bartomeu Coll, and J-M Morel · 2005
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Fields of experts: A framework for learning image priors
Stefan Roth and Michael J Black · 2005
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Image denoising with block-matching and 3d filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2006
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Removing camera shake from a single photograph
Rob Fergus, Barun Singh, Aaron Hertzmann, Sam T Roweis, and William T Freeman · 2006
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Image and depth from a conventional camera with a coded aperture
Anat Levin, Rob Fergus, Frédo Durand, and William T Freeman · 2007
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Fast image deconvolution using hyper-laplacian priors
Dilip Krishnan and Rob Fergus · 2009
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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
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Contour detection and hierarchical image segmentation
Pablo Arbelaez, Michael Maire, Charless Fowlkes, and Jitendra Malik · 2011
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Natural image denoising: Optimality and inherent bounds
Anat Levin and Boaz Nadler · 2011
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From learning models of natural image patches to whole image restoration
Daniel Zoran and Yair Weiss · 2011
Cited alongside, same era.
Low-complexity single-image super-resolution based on nonnegative neighbor embedding
Marco Bevilacqua, Aline Roumy, Christine Guillemot, and Marie-Line Alberi-Morel · 2012
Cited alongside, same era.
Plug-and-play priors for model based reconstruction
Singanallur V Venkatakrishnan, Charles A Bouman, and Brendt Wohlberg · 2013
Cited alongside, same era.
Non-uniform camera shake removal using a spatially-adaptive sparse penalty
Haichao Zhang and David Wipf · 2013
Learning joint demosaicing and denoising based on sequential energy minimization
Teresa Klatzer, Kerstin Hammernik, Patrick Knobelreiter, and Thomas Pock · 2016
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A logarithmic image prior for blind deconvolution
Daniele Perrone and Paolo Favaro · 2016
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The little engine that could: Regularization by denoising (red)
Yaniv Romano, Michael Elad, and Peyman Milanfar · 2016
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Cascades of regression tree fields for image restoration
Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin, Stefan Roth, and Carsten Rother · 2016
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Visualizing image priors
Tamar Rott Shaham and Tomer Michaeli · 2016
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
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Cited alongside, same era.
What regularized auto-encoders learn from the data-generating distribution
Guillaume Alain and Yoshua Bengio · 2014
Cited alongside, same era.
Joint demosaicing and denoising via learned nonparametric random fields
Daniel Khashabi, Sebastian Nowozin, Jeremy Jancsary, and Andrew W Fitzgibbon · 2014
Cited alongside, same era.
Shrinkage fields for effective image restoration
Uwe Schmidt and Stefan Roth · 2014
Cited alongside, same era.
Scale adaptive blind deblurring
Haichao Zhang and Jianchao Yang · 2014
Cited alongside, same era.
Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2016
Cited alongside, same era.
Deep joint demosaicking and denoising
Michaël Gharbi, Gaurav Chaurasia, Sylvain Paris, and Frédo Durand · 2016
Cited alongside, same era.
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2016
Later among the works it cites.
Image restoration using autoencoding priors
Siavash Arjomand Bigdeli and Matthias Zwicker · 2017
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One network to solve them all—solving linear inverse problems using deep projection models
JH Chang, Chun-Liang Li, Barnabas Poczos, BVK Kumar, and Aswin C Sankaranarayanan · 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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Noise-blind image deblurring
M. Jin, S. Roth, and P. Favaro · 2017
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Learning proximal operators: Using denoising networks for regularizing inverse imaging problems
Tim Meinhardt, Michael Möller, Caner Hazirbas, and Daniel Cremers · 2017
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Discriminative transfer learning for general image restoration
Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Schölkopf, and Michael Hirsch · 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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