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Image denoising methods must effectively model, implicitly or explicitly, the vast diversity of patterns and textures that occur in natural images.
Kodak lossless true color image suite
R. Franzen · 1999
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.
Image quality assessment: from error visibility to structural similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, et al · 2004
Earlier work this paper cites.
A non-local algorithm for image denoising
A. Buades, B. Coll, and J.-M. Morel · 2005
Earlier work this paper cites.
Image denoising via sparse and redundant representations over learned dictionaries
M. Elad and M. Aharon · 2006
Earlier work this paper cites.
Color image denoising via sparse 3d collaborative filtering with grouping constraint in luminance-chrominance space
K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian · 2007
Earlier work this paper cites.
Image denoising by sparse 3-d transform-domain collaborative filtering
K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian · 2007
Earlier work this paper cites.
Fields of experts
S. Roth and M. J. Black · 2009
Earlier work this paper cites.
Color demosaicking by local directional interpolation and nonlocal adaptive thresholding
L. Zhang, X. Wu, A. Buades, and X. Li · 2011
Earlier work this paper cites.
From learning models of natural image patches to whole image restoration
D. Zoran and Y. Weiss · 2011
Earlier work this paper cites.
Image denoising: Can plain neural networks compete with bm3d?
H. C. Burger, C. J. Schuler, and S. Harmeling · 2012
Earlier work this paper cites.
Combining the power of internal and external denoising
I. Mosseri, M. Zontak, and M. Irani · 2013
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Plug-and-play priors for model based reconstruction
S. V. Venkatakrishnan, C. A. Bouman, and B. Wohlberg · 2013
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Shrinkage fields for effective image restoration
U. Schmidt and S. Roth · 2014
Cited alongside, same era.
Single image super-resolution from transformed self-exemplars
J.-B. Huang, A. Singh, and N. Ahuja · 2015
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Learning to compare image patches via convolutional neural networks
S. Zagoruyko and N. Komodakis · 2015
Cited alongside, same era.
Densely connected convolutional networks
G. Huang, Z. Liu, K. Q. Weinberger, and L. van der Maaten · 2017
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Non-local color image denoising with convolutional neural networks
S. Lefkimmiatis · 2017
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Waterloo exploration database: New challenges for image quality assessment models
K. Ma, Z. Duanmu, Q. Wu, Z. Wang, H. Yong, H. Li, and L. Zhang · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
K. Zhang, W. Zuo, Y. Chen, D. Meng, and L. Zhang · 2017
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Learning deep cnn denoiser prior for image restoration
K. Zhang, W. Zuo, S. Gu, and L. Zhang · 2017
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Deep boosting for image denoising
C. Chen, Z. Xiong, X. Tian, and F. Wu · 2018
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Learning local image descriptors with deep siamese and triplet convolutional networks by minimising global loss functions
B. Kumar, G. Carneiro, and I. Reid · 2016
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Stereo matching by training a convolutional neural network to compare image patches
J. Zbontar and Y. LeCun · 2016
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Deep mean-shift priors for image restoration
S. A. Bigdeli, M. Zwicker, P. Favaro, and M. Jin · 2017
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One network to solve them all-solving linear inverse problems using deep projection models
J.-H. R. Chang, C.-L. Li, B. Poczos, B. V. Kumar, and A. C. Sankaranarayanan · 2017
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Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Y. Chen and T. Pock · 2017
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Non-local recurrent network for image restoration
D. Liu, B. Wen, Y. Fan, C. C. Loy, and T. S. Huang · 2018
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Neural nearest neighbors networks
T. Plötz and S. Roth · 2018
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Bm3d-net: A convolutional neural network for transform-domain collaborative filtering
D. Yang and J. Sun · 2018
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Ffdnet: Toward a fast and flexible solution for cnn based image denoising
K. Zhang, W. Zuo, and L. Zhang · 2018
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