A curated list of image denoising resources and a benchmark for image denoising approaches.
This list is maintained by: Wenhan Yang [STRUCT] PKU (PI: Prof. Jiaying Liu)
- BM3D [Web] [Code] [PDF]
- Image restoration by sparse 3D transform-domain collaborative filtering (SPIE Electronic Imaging 2008), Dabov et al.
- Activity-tuned Image Filtering [PDF]
- Local Activity-tuned Image Filtering for Noise Removal and Image Smoothing (Arxiv 2017), Lijun Zhao, Jie Liang, Huihui Bai, Lili Meng, Anhong Wang, and Yao Zhao.
- KSVD [Web] [Code] [PDF]
- Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries (TIP2006), Elad et al.
- SAINT [Web] [Code] [PDF]
- Nonlocal image restoration with bilateral variance estimation: a low-rank approach (TIP2013), Dong et al.
- NCSR [Web] [Code] [PDF]
- Nonlocally Centralized Sparse Representation for Image Restoration (TIP2012), Dong et al.
- LSSC [Web] [Code] [PDF]
- Non-local Sparse Models for Image Restoration (ICCV2009), Mairal et al.
- TWSC [Web] [Code] [PDF]
- A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising (ECCV2018), Xu et al.
- EPLL [Web] [Code] [PDF]
- From Learning Models of Natural Image Patches to Whole Image Restoration (ICCV2011), Zoran et al.
- Bayesian Hyperprior [PDF]
- A Bayesian Hyperprior Approach for Joint Image Denoising and Interpolation with an Application to HDR Imaging, Cecilia Aguerrebere, Andres Almansa, Julie Delon, Yann Gousseau and Pablo Muse.
- External Prior Guided [PDF]
- External Prior Guided Internal Prior Learning for Real Noisy Image Denoising, Jun Xu, Lei Zhang, and David Zhang.
- Multi-Layer Image Representation [PDF]
- A Multi-Layer Image Representation Using Regularized Residual Quantization: Application to Compression and Denoising, Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov.
- A Faster Patch Ordering [PDF]
- A Faster Patch Ordering Method for Image Denoising, Badre Munir.
- WNNM [Web] [Code] [PDF]
- Weighted Nuclear Norm Minimization with Application to Image Denoising (CVPR2014), Gu et al.
- Low-rank MoG filter [PDF]
- From Noise Modeling to Blind Image Denoising (CVPR2016), Zhu et al.
- Multi-channel Weighted Nuclear Norm [Web] [Code] [PDF]
- Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising (ICCV2017), Jun Xu, Lei Zhang, David Zhang, and Xiangchu Feng.
- Multi-Scale Weighted Nuclear Norm [PDF]
- Multi-Scale Weighted Nuclear Norm Image Restoration (CVPR2018), Noam Yair, Tomer Michaeli.
- TNRD [Web] [Code] [PDF]
- Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration (TPAMI2016), Chen et al.
- DnCNN [Web] [PDF]
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP2017), Zhang et al.
- DAAM [Web] [PDF]
- Deeply Aggregated Alternating Minimization for Image Restoration (Arxiv2016), Youngjung Kim et al.
- Adversirial Denoising [PDF]
- Image Denoising via CNNs: An Adversarial Approach (Arxiv2017), Nithish Divakar, R. Venkatesh Babu.
- Unrolled Optimization Deep Priors [PDF]
- Unrolled Optimization with Deep Priors (Arxiv2017), Steven Diamond, Vincent Sitzmann, Felix Heide, Gordon Wetzstein.
- Recurrent Inference Machines [PDF]
- Recurrent Inference Machines for Solving Inverse Problems(Arxiv2017), Patrick Putzky, Max Welling.
- Kernel Prediction [PDF]
- Burst Denoising With Kernel Prediction Networks (CVPR2018), Ben Mildenhall, Jonathan T. Barron, Jiawen Chen, Dillon Sharlet, Ren Ng, Robert Carroll.
- GAN-Based Noise Modeling [PDF]
- Image Blind Denoising With Generative Adversarial Network Based Noise Modeling (CVPR2018), Jingwen Chen, Jiawei Chen, Hongyang Chao, Ming Yang.
- Universal Denoising Networks [PDF]
- Universal Denoising Networks : A Novel CNN Architecture for Image Denoising (CVPR2018), Stamatios Lefkimmiatis.
- Non-Local Recurrent Network [PDF]
- Non-Local Recurrent Network for Image Restoration (Arxiv2018), Ding Liu, Bihan Wen, Yuchen Fan, Chen Change Loy, Thomas S. Huang.
- Recurring Patterns Network [PDF]
- Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising (Arxiv2018), Zhihao Xia, Ayan Chakrabarti.
- Dynamically Unfolding Recurrent Restorer [PDF]
- Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration (Arxiv2018), Xiaoshuai Zhang, Yiping Lu, Jiaying Liu, Bin Dong.
- Pixel Adaptive Image Denoiser [PDF]
- Fully Convolutional Pixel Adaptive Image Denoiser (Arxiv2018), Sungmin Cha and Taesup Moon.
- Convolutional Blind Denoising [PDF] [WEB]
- Toward Convolutional Blind Denoising of Real Photographs (Arxiv2018), Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, Lei Zhang.
- Noise2Noise [PDF]
- Noise2Noise: Learning Image Restoration without Clean Data (ICML2018), Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila.
- Meets High-level Tasks [PDF]
- When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach, Ding Liu (IJCAI2018), Bihan Wen, Xianming Liu, Thomas S. Huang.
- Class-Specific Denoising [PDF]
- Class-Specific Poisson Denoising By Patch-Based Importance Sampling (Arxiv2017), Milad Niknejad, Jose M. Bioucas-Dias, Mario A. T. Figueiredo.
- Class-Aware Denoising [PDF]
- Class-Aware Fully-Convolutional Gaussian and Poisson Denoising (Arxiv2018), Tal Remez, Or Litany, Raja Giryes, and Alex M. Bronstein.
- Image Denoising + High Level [PDF]
- Connecting Image Denoising and High-Level Vision Tasks via Deep Learning (Arxiv2018), Ding Liu, Bihan Wen, Jianbo Jiao, Xianming Liu, Zhangyang Wang, and Thomas S. Huang.
- ReNOIR [PDF] [WEB]
- RENOIR - A Dataset for Real Low-Light Image Noise Reduction (JVCIR2018), Josue Anaya, Adrian Barbu.
- Darmsdadt [PDF] [WEB]
- Benchmarking Denoising Algorithms with Real Photographs (CVPR2017), Tobias Plotz, Stefan Roth.
- Smartphone Cameras Dataset [PDF]
- A High-Quality Denoising Dataset for Smartphone Cameras (CVPR2018), Abdelrahman Abdelhamed, Stephen Lin, Michael S. Brown.
- PolyU [PDF] [WEB]
- Real-world Noisy Image Denoising: A New Benchmark (Arxiv2018), Jun Xu, Hui Li, Zhetong Liang, David Zhang, and Lei Zhang.