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https://github.com/flyywh/Image-Denoising-State-of-the-art


https://github.com/flyywh/Image-Denoising-State-of-the-art

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README 

        
# Image Denoising State-of-the-art



**A curated list of image denoising resources and a benchmark for image denoising approaches.**



**This list is maintained by:** **Wenhan Yang** **[[STRUCT]](http://www.icst.pku.edu.cn/struct/struct.html) PKU (PI: Prof. Jiaying Liu)**



## State-of-the-art algorithms

#### Filter

 * BM3D [[Web]](http://www.cs.tut.fi/~foi/GCF-BM3D/) [[Code]](http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D.zip) [[PDF]](http://www.cs.tut.fi/~foi/GCF-BM3D/SPIE08_deblurring.pdf)

   * Image restoration by sparse 3D transform-domain collaborative filtering (SPIE Electronic Imaging 2008), Dabov et al.

 * Activity-tuned Image Filtering [[PDF]](https://arxiv.org/pdf/1707.02637.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.



#### Sparse Coding

 * KSVD [[Web]](http://www.cs.technion.ac.il/~ronrubin/software.html) [[Code]](https://github.com/jbhuang0604/SelfSimSR/tree/master/Lib/KSVD) [[PDF]](http://www.egr.msu.edu/~aviyente/elad06.pdf)

   * Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries (TIP2006), Elad et al.

 * SAINT [[Web]](http://see.xidian.edu.cn/faculty/wsdong/wsdong_Publication.htm) [Code] [[PDF]](http://see.xidian.edu.cn/faculty/wsdong/Papers/Journal/TIP_LASSC.pdf)

   * Nonlocal image restoration with bilateral variance estimation: a low-rank approach (TIP2013), Dong et al.

 * NCSR [[Web]](http://www4.comp.polyu.edu.hk/~cslzhang/NCSR.htm) [[Code]](http://www4.comp.polyu.edu.hk/~cslzhang/code/NCSR.rar) [[PDF]](http://www4.comp.polyu.edu.hk/~cslzhang/paper/NCSR_TIP_final.pdf)

   * Nonlocally Centralized Sparse Representation for Image Restoration (TIP2012), Dong et al.

 * LSSC [[Web]](http://www.di.ens.fr/~fbach/) [Code] [[PDF]](http://www.di.ens.fr/~fbach/iccv09_mairal.pdf)

   * Non-local Sparse Models for Image Restoration (ICCV2009), Mairal et al.

 * TWSC [[Web]](https://github.com/csjunxu/TWSC-ECCV2018) [Code] [[PDF]](http://openaccess.thecvf.com/content_ECCV_2018/papers/XU_JUN_A_Trilateral_Weighted_ECCV_2018_paper.pdf)

   * A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising (ECCV2018), Xu et al.



#### Effective Prior

 * EPLL [[Web]](https://people.csail.mit.edu/danielzoran/) [[Code]](https://people.csail.mit.edu/danielzoran/epllcode.zip) [[PDF]](http://people.ee.duke.edu/~lcarin/EPLICCVCameraReady.pdf)

   * From Learning Models of Natural Image Patches to Whole Image Restoration (ICCV2011), Zoran et al.

 * Bayesian Hyperprior [[PDF]](https://arxiv.org/pdf/1706.03261.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]](https://arxiv.org/pdf/1705.04505.pdf)

   * External Prior Guided Internal Prior Learning for Real Noisy Image Denoising, Jun Xu, Lei Zhang, and David Zhang.

 * Multi-Layer Image Representation [[PDF]](https://arxiv.org/pdf/1707.02194.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]](https://arxiv.org/ftp/arxiv/papers/1704/1704.08090.pdf)

   * A Faster Patch Ordering Method for Image Denoising, Badre Munir.

  

#### Low Rank

 * WNNM [[Web]](https://sites.google.com/site/shuhanggu/home) [[Code]](http://www4.comp.polyu.edu.hk/~cslzhang/code/WNNM_code.zip) [[PDF]](https://pdfs.semanticscholar.org/6d55/6272625b672ba54b5ab3d9e6474088a4b78f.pdf)

   * Weighted Nuclear Norm Minimization with Application to Image Denoising (CVPR2014), Gu et al.

 * Low-rank MoG filter [[PDF]](http://openaccess.thecvf.com/content_cvpr_2016/papers/Zhu_From_Noise_Modeling_CVPR_2016_paper.pdf)

   * From Noise Modeling to Blind Image Denoising (CVPR2016), Zhu et al.

 * Multi-channel Weighted Nuclear Norm [[Web]](https://github.com/csjunxu/MCWNNM-ICCV2017) [Code] [[PDF]](https://arxiv.org/pdf/1705.09912.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]](https://tomer.net.technion.ac.il/files/2018/04/MS-WNNM-IR.pdf)

   * Multi-Scale Weighted Nuclear Norm Image Restoration (CVPR2018), Noam Yair, Tomer Michaeli.



#### Deep Learning

 * TNRD [[Web]](http://www.icg.tugraz.at/Members/Chenyunjin/about-yunjin-chen) [[Code]](https://www.dropbox.com/s/8j6b880m6ddxtee/TNRD-Codes.zip?dl=0) [[PDF]](https://arxiv.org/pdf/1508.02848.pdf)

   * Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration (TPAMI2016), Chen et al.

 * DnCNN [[Web]](https://github.com/cszn/DnCNN) [[PDF]](https://arxiv.org/pdf/1608.03981v1.pdf)

   * Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP2017), Zhang et al.

 * DAAM [[Web]](https://arxiv.org/abs/1612.06508) [[PDF]](https://arxiv.org/pdf/1612.06508.pdf)

   * Deeply Aggregated Alternating Minimization for Image Restoration (Arxiv2016), Youngjung Kim et al.

 * Adversirial Denoising [[PDF]](https://arxiv.org/pdf/1708.00159.pdf)

   * Image Denoising via CNNs: An Adversarial Approach (Arxiv2017), Nithish Divakar, R. Venkatesh Babu.

 * Unrolled Optimization Deep Priors [[PDF]](https://arxiv.org/pdf/1705.08041.pdf)

   * Unrolled Optimization with Deep Priors (Arxiv2017), Steven Diamond, Vincent Sitzmann, Felix Heide, Gordon Wetzstein.

 * Recurrent Inference Machines [[PDF]](https://arxiv.org/pdf/1706.04008.pdf)

   * Recurrent Inference Machines for Solving Inverse Problems(Arxiv2017), Patrick Putzky, Max Welling.

 * Kernel Prediction [[PDF]](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/3761.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]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Image_Blind_Denoising_CVPR_2018_paper.pdf)

   * 	Image Blind Denoising With Generative Adversarial Network Based Noise Modeling (CVPR2018), Jingwen Chen, Jiawei Chen, Hongyang Chao, Ming Yang. 

 * Universal Denoising Networks [[PDF]](https://arxiv.org/pdf/1711.07807.pdf)

   * 	Universal Denoising Networks : A Novel CNN Architecture for Image Denoising (CVPR2018), Stamatios Lefkimmiatis.

 * Non-Local Recurrent Network [[PDF]](https://arxiv.org/pdf/1806.02919.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]](https://arxiv.org/pdf/1806.05229.pdf)

   * 	Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising (Arxiv2018), Zhihao Xia, Ayan Chakrabarti.

 * Dynamically Unfolding Recurrent Restorer [[PDF]](https://arxiv.org/pdf/1805.07709.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]](https://arxiv.org/pdf/1807.07569.pdf)

   *  Fully Convolutional Pixel Adaptive Image Denoiser (Arxiv2018), Sungmin Cha and Taesup Moon.

 * Convolutional Blind Denoising [[PDF]](https://arxiv.org/pdf/1807.04686.pdf) [[WEB]](https://github.com/GuoShi28/CBDNet)

   *  Toward Convolutional Blind Denoising of Real Photographs (Arxiv2018), Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, Lei Zhang.

 * Noise2Noise [[PDF]](https://arxiv.org/pdf/1803.04189.pdf)

   *  Noise2Noise: Learning Image Restoration without Clean Data (ICML2018), Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila.

   

   

#### Combined with High-Level Tasks

 * Meets High-level Tasks [[PDF]](https://arxiv.org/pdf/1706.04284.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]](https://arxiv.org/pdf/1706.02867.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]](https://arxiv.org/pdf/1808.06562.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]](https://arxiv.org/pdf/1809.01826.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.



#### Benchmark

 * ReNOIR [[PDF]](https://arxiv.org/pdf/1409.8230.pdf) [[WEB]](http://ani.stat.fsu.edu/~abarbu/Renoir.html)

   * RENOIR - A Dataset for Real Low-Light Image Noise Reduction (JVCIR2018), Josue Anaya, Adrian Barbu.

 * Darmsdadt [[PDF]](https://arxiv.org/pdf/1707.01313.pdf) [[WEB]](https://noise.visinf.tu-darmstadt.de/)

   * Benchmarking Denoising Algorithms with Real Photographs (CVPR2017), Tobias Plotz, Stefan Roth.

 * Smartphone Cameras Dataset [[PDF]](http://www.cse.yorku.ca/~mbrown/pdf/sidd_cvpr2018.pdf)

   * A High-Quality Denoising Dataset for Smartphone Cameras (CVPR2018), Abdelrahman Abdelhamed, Stephen Lin, Michael S. Brown.

 * PolyU [[PDF]](https://arxiv.org/pdf/1804.02603.pdf) [[WEB]](https://github.com/csjunxu/PolyU-Real-World-Noisy-Images-Dataset)

   * Real-world Noisy Image Denoising: A New Benchmark (Arxiv2018), Jun Xu, Hui Li, Zhetong Liang, David Zhang, and Lei Zhang.