Integrating Local and Non-local Denoiser Priors for Image Restoration
暂无分享,去创建一个
[1] Lei Zhang,et al. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising , 2016, IEEE Transactions on Image Processing.
[2] Marshall F. Tappen,et al. Utilizing Variational Optimization to Learn Markov Random Fields , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[3] 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).
[4] Anat Levin,et al. Accurate Blur Models vs. Image Priors in Single Image Super-resolution , 2013, 2013 IEEE International Conference on Computer Vision.
[5] Donald Geman,et al. Nonlinear image recovery with half-quadratic regularization , 1995, IEEE Trans. Image Process..
[6] Lei Zhang,et al. Weighted Nuclear Norm Minimization with Application to Image Denoising , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[7] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[8] V. Katkovnik,et al. DEBLURRING BY AUGMENTED LANGRANGIAN WITH BM 3 D FRAME PRIOR , 2010 .
[9] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[10] Thomas S. Huang,et al. Image super-resolution as sparse representation of raw image patches , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[11] Michal Irani,et al. Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..
[12] Bernhard Schölkopf,et al. A Machine Learning Approach for Non-blind Image Deconvolution , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Michael J. Black,et al. Fields of Experts: a framework for learning image priors , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[14] Michal Irani,et al. Combining the power of Internal and External denoising , 2013, IEEE International Conference on Computational Photography (ICCP).
[15] Luc Van Gool,et al. Generic 3D Convolutional Fusion for Image Restoration , 2016, ACCV Workshops.
[16] Frédo Durand,et al. Understanding and evaluating blind deconvolution algorithms , 2009, CVPR.
[17] Brendt Wohlberg,et al. Plug-and-Play priors for model based reconstruction , 2013, 2013 IEEE Global Conference on Signal and Information Processing.
[18] Nong Sang,et al. Fast image super resolution via local regression , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).
[19] David Zhang,et al. Learning Iteration-wise Generalized Shrinkage–Thresholding Operators for Blind Deconvolution , 2016, IEEE Transactions on Image Processing.
[20] 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.
[21] Junfeng Yang,et al. A New Alternating Minimization Algorithm for Total Variation Image Reconstruction , 2008, SIAM J. Imaging Sci..
[22] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[23] Wangmeng Zuo,et al. Learning Deep CNN Denoiser Prior for Image Restoration , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Lei Zhang,et al. Nonlocally Centralized Sparse Representation for Image Restoration , 2013, IEEE Transactions on Image Processing.
[25] Kyoung Mu Lee,et al. Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Luc Van Gool,et al. A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution , 2014, ACCV.
[27] Radu Timofte,et al. Anchored fusion for image restoration , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[28] Michael Elad,et al. A Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution , 2014, IEEE Transactions on Image Processing.
[29] Karen O. Egiazarian,et al. Decoupled inverse and denoising for image deblurring: Variational BM3D-frame technique , 2011, 2011 18th IEEE International Conference on Image Processing.
[30] Michael Elad,et al. The Little Engine That Could: Regularization by Denoising (RED) , 2016, SIAM J. Imaging Sci..
[31] Lei Zhang,et al. Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision , 2016, International Journal of Computer Vision.
[32] Stefan Harmeling,et al. Learning How to Combine Internal and External Denoising Methods , 2013, GCPR.
[33] Xiaoou Tang,et al. Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Stamatios Lefkimmiatis,et al. Non-local Color Image Denoising with Convolutional Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[36] Lei Zhang,et al. Convolutional Sparse Coding for Image Super-Resolution , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).