Plug-and-Play Image Restoration With Deep Denoiser Prior
暂无分享,去创建一个
Luc Van Gool | Radu Timofte | Kai Zhang | Wangmeng Zuo | Lei Zhang | Yawei Li | L. Gool | R. Timofte | K. Zhang | W. Zuo | Lei Zhang | Yawei Li
[1] Vladimir Katkovnik,et al. SINGLE IMAGE SUPER-RESOLUTION VIA BM 3 D SPARSE CODING , 2015 .
[2] Tomer Michaeli,et al. Multi-scale Weighted Nuclear Norm Image Restoration , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[3] Anat Levin,et al. Accurate Blur Models vs. Image Priors in Single Image Super-resolution , 2013, 2013 IEEE International Conference on Computer Vision.
[4] Jean-Christophe Pesquet,et al. Deep unfolding of a proximal interior point method for image restoration , 2018, Inverse Problems.
[5] Xiaoou Tang,et al. Compression Artifacts Reduction by a Deep Convolutional Network , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[6] Zahra Kadkhodaie,et al. Robust and interpretable blind image denoising via bias-free convolutional neural networks , 2019, ICLR.
[7] Lei Zhang,et al. FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising , 2017, IEEE Transactions on Image Processing.
[8] William H. Richardson,et al. Bayesian-Based Iterative Method of Image Restoration , 1972 .
[9] Michael S. Brown,et al. Noise Flow: Noise Modeling With Conditional Normalizing Flows , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[10] Martin J. Wainwright,et al. Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..
[11] Marshall F. Tappen,et al. Separable Markov Random Field Model and Its Applications in Low Level Vision , 2013, IEEE Transactions on Image Processing.
[12] Yunjin Chen,et al. Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13] J. Morel,et al. Residual Learning for Effective joint Demosaicing-Denoising , 2020, ArXiv.
[14] Adrian Barbu,et al. Training an Active Random Field for Real-Time Image Denoising , 2009, IEEE Transactions on Image Processing.
[15] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[16] Raja Giryes,et al. Image Restoration by Iterative Denoising and Backward Projections , 2017, IEEE Transactions on Image Processing.
[17] Jitendra Malik,et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[18] Tom Tirer,et al. Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal Learning , 2018, IEEE Signal Processing Letters.
[19] Michael Elad,et al. Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries , 2006, IEEE Transactions on Image Processing.
[20] Wangmeng Zuo,et al. Revisiting Single Image Super-Resolution Under Internet Environment: Blur Kernels and Reconstruction Algorithms , 2015, PCM.
[21] Zun Li,et al. Learning Deep CNN Denoiser Priors for Depth Image Inpainting , 2019 .
[22] Nam Ik Cho,et al. Meta-Transfer Learning for Zero-Shot Super-Resolution , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Stamatios Lefkimmiatis,et al. Non-local Color Image Denoising with Convolutional Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Hassan Mansour,et al. A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems , 2017, IEEE Signal Processing Letters.
[25] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Stefan Roth,et al. Shrinkage Fields for Effective Image Restoration , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[27] Lei Zhang,et al. Waterloo Exploration Database: New Challenges for Image Quality Assessment Models , 2017, IEEE Transactions on Image Processing.
[28] Stephen P. Boyd,et al. Proximal Algorithms , 2013, Found. Trends Optim..
[29] Brendt Wohlberg,et al. Plug-and-Play priors for model based reconstruction , 2013, 2013 IEEE Global Conference on Signal and Information Processing.
[30] Jean-Yves Tourneret,et al. Fast Single Image Super-Resolution Using a New Analytical Solution for $\ell _{2}$ – $\ell _{2}$ Problems , 2016, IEEE Transactions on Image Processing.
[31] Kyoung Mu Lee,et al. Enhanced Deep Residual Networks for Single Image Super-Resolution , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[32] Lei Zhang,et al. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising , 2016, IEEE Transactions on Image Processing.
[33] Jonathan T. Barron,et al. Unprocessing Images for Learned Raw Denoising , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Yun Fu,et al. Residual Non-local Attention Networks for Image Restoration , 2019, ICLR.
[35] Luc Van Gool,et al. Integrating Local and Non-local Denoiser Priors for Image Restoration , 2018, 2018 24th International Conference on Pattern Recognition (ICPR).
[36] Karen O. Egiazarian,et al. BM3D Frames and Variational Image Deblurring , 2011, IEEE Transactions on Image Processing.
[37] Lei Tian,et al. Regularized Fourier Ptychography Using an Online Plug-and-play Algorithm , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[38] Masatoshi Okutomi,et al. Beyond Color Difference: Residual Interpolation for Color Image Demosaicking , 2016, IEEE Transactions on Image Processing.
[39] Wei Ye,et al. Color Image Demosaicing Using Iterative Residual Interpolation , 2015, IEEE Transactions on Image Processing.
[40] Wangmeng Zuo,et al. Learning Deep CNN Denoiser Prior for Image Restoration , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[41] Yair Weiss,et al. From learning models of natural image patches to whole image restoration , 2011, 2011 International Conference on Computer Vision.
[42] Carsten Rother,et al. Learning to Push the Limits of Efficient FFT-Based Image Deconvolution , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[43] Yu Sun,et al. Block Coordinate Regularization by Denoising , 2019, IEEE Transactions on Computational Imaging.
[44] Luc Van Gool,et al. Seven Ways to Improve Example-Based Single Image Super Resolution , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Wei Wu,et al. Feedback Network for Image Super-Resolution , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[46] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[47] José M. Bioucas-Dias,et al. Image restoration and reconstruction using variable splitting and class-adapted image priors , 2016, 2016 IEEE International Conference on Image Processing (ICIP).
[48] Noel E. O'Connor,et al. A Deep Residual Architecture for Skin Lesion Segmentation , 2018, OR 2.0/CARE/CLIP/ISIC@MICCAI.
[49] Michael Elad,et al. The Little Engine That Could: Regularization by Denoising (RED) , 2016, SIAM J. Imaging Sci..
[50] Antonin Chambolle,et al. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.
[51] Henrique S. Malvar,et al. High-quality linear interpolation for demosaicing of Bayer-patterned color images , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[52] Shu-Tao Xia,et al. Second-Order Attention Network for Single Image Super-Resolution , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[53] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[54] Frédo Durand,et al. Deep joint demosaicking and denoising , 2016, ACM Trans. Graph..
[55] Florian Jug,et al. Noise2Void - Learning Denoising From Single Noisy Images , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Kari Pulli,et al. FlexISP , 2014, ACM Trans. Graph..
[57] Stamatios Lefkimmiatis,et al. Iterative Joint Image Demosaicking and Denoising Using a Residual Denoising Network , 2018, IEEE Transactions on Image Processing.
[58] Eirikur Agustsson,et al. NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[59] Yun Fu,et al. Image Super-Resolution Using Very Deep Residual Channel Attention Networks , 2018, ECCV.
[60] Mathews Jacob,et al. MoDL: Model-Based Deep Learning Architecture for Inverse Problems , 2017, IEEE Transactions on Medical Imaging.
[61] Stefan Roth,et al. Neural Nearest Neighbors Networks , 2018, NeurIPS.
[62] Wangmeng Zuo,et al. Toward Convolutional Blind Denoising of Real Photographs , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[63] A. Basarab,et al. Fast Single Image Super-resolution using a New Analytical Solution for l2-l2 Problems. , 2016, IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.
[64] Hongdong Li,et al. Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[65] Lin Liu,et al. Joint Demosaicing and Denoising With Self Guidance , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[66] Ruturaj G. Gavaskar,et al. Plug-and-Play ISTA Converges With Kernel Denoisers , 2020, IEEE Signal Processing Letters.
[67] Michal Irani,et al. Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..
[68] Lei Zhang,et al. Color demosaicking by local directional interpolation and nonlocal adaptive thresholding , 2011, J. Electronic Imaging.
[69] Michael J. Black,et al. Fields of Experts , 2009, International Journal of Computer Vision.
[70] Donald Geman,et al. Nonlinear image recovery with half-quadratic regularization , 1995, IEEE Trans. Image Process..
[71] Guangming Shi,et al. Denoising Prior Driven Deep Neural Network for Image Restoration , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[72] Karen O. Egiazarian,et al. Single image super-resolution via BM3D sparse coding , 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).
[73] Lei Zhang,et al. Weighted Nuclear Norm Minimization with Application to Image Denoising , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[74] Fahad Shahbaz Khan,et al. CycleISP: Real Image Restoration via Improved Data Synthesis , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[75] Ser-Nam Lim,et al. Quantization Guided JPEG Artifact Correction , 2020, ECCV.
[76] Thomas S. Huang,et al. Non-Local Recurrent Network for Image Restoration , 2018, NeurIPS.
[77] Jean-Michel Morel,et al. A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[78] Jeff Donahue,et al. Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.
[79] Xiaohan Chen,et al. Plug-and-Play Methods Provably Converge with Properly Trained Denoisers , 2019, ICML.
[80] Marshall F. Tappen,et al. Utilizing Variational Optimization to Learn Markov Random Fields , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[81] Stanley H. Chan,et al. Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications , 2016, IEEE Transactions on Computational Imaging.
[82] Richard G. Baraniuk,et al. From Denoising to Compressed Sensing , 2014, IEEE Transactions on Information Theory.
[83] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[84] Xiangchu Feng,et al. FOCNet: A Fractional Optimal Control Network for Image Denoising , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[85] Jaakko Lehtinen,et al. Noise2Noise: Learning Image Restoration without Clean Data , 2018, ICML.
[86] Guillermo Sapiro,et al. Non-local sparse models for image restoration , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[87] Loïc Royer,et al. Noise2Self: Blind Denoising by Self-Supervision , 2019, ICML.
[88] Qingjie Liu,et al. Road Extraction by Deep Residual U-Net , 2017, IEEE Geoscience and Remote Sensing Letters.
[89] Frédo Durand,et al. Understanding and evaluating blind deconvolution algorithms , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[90] Luc Van Gool,et al. Deep Unfolding Network for Image Super-Resolution , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[91] Bernard Ghanem,et al. ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[92] Xiaoou Tang,et al. Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[93] Radu Timofte,et al. Demosaicing Based on Directional Difference Regression and Efficient Regression Priors , 2016, IEEE Transactions on Image Processing.
[94] K. Siddaraju,et al. DIGITAL IMAGE RESTORATION , 2011 .
[95] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.