Reproducible Image Denoising State Of The Art Save

Collection of popular and reproducible image denoising works.

Project README


Collection of popular and reproducible single image denoising works. This collection is inspired by the summary by flyywh

Criteria: works must have codes available, and the reproducible results demonstrate state-of-the-art performances.

Check out the following collections of reproducible state-of-the-art algorithms:

Denoising Algorithms (AWGN)


  • NLM [Web] [Code] [PDF]
    • A non-local algorithm for image denoising (CVPR 05), Buades et al.
    • Image denoising based on non-local means filter and its method noise thresholding (SIVP2013), B. Kumar
  • BM3D [Web] [Code] [PDF]
    • Image restoration by sparse 3D transform-domain collaborative filtering (SPIE Electronic Imaging 2008), Dabov et al.
  • PID [Web] [Code] [PDF]
    • Progressive Image Denoising (TIP 2014), C. Knaus et al.

Sparse Coding

  • KSVD [Web] [Code] [PDF]
    • Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries (TIP 2006), Elad et al.
  • LSSC [Web] [Code] [PDF]
    • Non-local Sparse Models for Image Restoration (ICCV 2009), Mairal et al.
  • NCSR [Web] [Code] [PDF]
    • Nonlocally Centralized Sparse Representation for Image Restoration (TIP 2012), Dong et al.
  • OCTOBOS [Web] [Code] [PDF]
    • Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications (IJCV 2015), Wen et al.
  • GSR [Web] [Code] [PDF]
    • Group-based Sparse Representation for Image Restoration (TIP 2014), Zhang et al.
  • TWSC [Web] [Code] [PDF]
    • A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising (ECCV 2018), Xu et al.

Classical External Priors

  • EPLL [Web] [Code] [PDF]
    • From Learning Models of Natural Image Patches to Whole Image Restoration (ICCV2011), Zoran et al.
  • GHP [[Web]][Code] [PDF]
    • Texture Enhanced Image Denoising via Gradient Histogram Preservation (CVPR2013), Zuo et al.
  • PGPD [[Web]][Code] [PDF]
    • Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising (ICCV 2015), Xu et al.
  • PCLR [[Web]][Code] [PDF]
    • External Patch Prior Guided Internal Clustering for Image Denoising (ICCV 2015), Chen et al.  

Low Rank

  • SAIST [Web] [Code by request] [PDF]
    • Nonlocal image restoration with bilateral variance estimation: a low-rank approach (TIP2013), Dong et al.
  • WNNM [Web] [Code] [PDF]
    • Weighted Nuclear Norm Minimization with Application to Image Denoising (CVPR2014), Gu et al.
  • Multi-channel WNNM [Web] [Code] [PDF]
    • Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising (ICCV 2017), Xu et al.

Deep Denoising

  • TNRD [Web] [Code] [PDF]
    • Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration (TPAMI 2016), Chen et al.
  • RED [Web] [Code] [PDF]
    • Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections (NIPS2016), Mao et al.
  • DnCNN [Web] [Code] [PDF]
    • Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP2017), Zhang et al.
  • MemNet [Web] [Code] [PDF]
    • MemNet: A Persistent Memory Network for Image Restoration (ICCV2017), Tai et al.
  • NLCNN [Web] [Code] [PDF]
    • Non-Local Color Image Denoising with Convolutional Neural Networks (CVPR 2017), Lefkimmiatis.
  • xUnit [Web] [Code] [PDF]
    • xUnit: Learning a Spatial Activation Function for Efficient Image Restoration (CVPR 2018), Kligvasser et al.
  • UDNet [Web] [Code] [PDF]
    • Universal Denoising Networks : A Novel CNN Architecture for Image Denoising (CVPR 2018), Lefkimmiatis.
  • Wavelet-CNN [Web] [Code] [PDF]
    • Multi-level Wavelet-CNN for Image Restoration (CVPR 2018), Liu et al.
  • IRN [Web] [Code] [PDF]
    • Deep Image Demosaicking using a Cascade of Convolutional Residual Denoising Networks (ECCV 2018), Lefkimmiatis.
  • FFDNet [Web] [Code] [PDF]
    • FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising (TIP 2018), Zhang et al.
  • UDN [Web] [Code] [PDF]
    • Universal Denoising Networks- A Novel CNN Architecture for Image Denoising (CVPR 2018), Lefkimmiatis.
  • N3 [Web] [Code] [PDF]
    • Neural Nearest Neighbors Networks (NIPS 2018), Plotz et al.
  • NLRN [Web] [Code] [PDF]
    • Non-Local Recurrent Network for Image Restoration (NIPS 2018), Liu et al.
  • RDN+ [Web] [Code] [PDF]
    • Residual Dense Network for Image Restoration (CVPR 2018), Zhang et al.
  • FC-AIDE [Web] [Code] [PDF]
    • Fully Convolutional Pixel Adaptive Image Denoiser (ICCV 2019), Cha et al.
  • FOCNet [Web] [Code] [PDF]
    • FOCNet: A Fractional Optimal Control Network for Image Denoising (CVPR 2019), Jia et al.

Unsupervised / Weakly-Supervised Deep Denoising

  • Noise2Noise [Web] [TF Code] [Keras Unofficial Code] [PDF]
    • Noise2Noise: Learning Image Restoration without Clean Data (ICML 2018), Lehtinen et al.
  • DIP [Web] [Code] [PDF]
    • Deep Image Prior (CVPR 2018), Ulyanov et al.
  • Noise2Void [Web] [Code] [PDF]
    • Learning Denoising from Single Noisy Images (CVPR 2019), Krull et al.
  • Noise2Self [Web] [Code] [PDF]
    • Noise2Self: Blind Denoising by Self-Supervision (ICML 2019), Batson and Royer
  • Self-Supervised Denoising [Web] [Code] [PDF]
    • High-Quality Self-Supervised Deep Image Denoising (NIPS 2019), Laine et al.

Hybrid Model for Denoising

  • STROLLR [PDF] [Code]
    • When Sparsity Meets Low-Rankness: Transform Learning With Non-Local Low-Rank Constraint for Image Restoration (ICASSP 2017), Wen et al.
  • Meets High-level Tasks [PDF] [Code]
    • When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach (IJCAI 2018), Liu et al.
  • USA [PDF] [Code]
    • Segmentation-aware Image Denoising Without Knowing True Segmentation (Arxiv), Wang et al.

Blind Denoising or Real Noise Removal

  • RIDNet [Web] [Code] [PDF]
    • Real Image Denoising with Feature Attention (ICCV 2019), Anwar and Barnes.
  • CBDNet [Web] [Code] [PDF]
    • Toward Convolutional Blind Denoising of Real Photographs (CVPR 2019), Guo et al.
  • VDNNet [Web] [Code] [PDF]
    • Variational Denoising Network: Toward Blind Noise Modeling and Removal (NIPS 2019), Yue et al.

Image Noise Level Estimation

  • SINLE [PDF] [Code] [Slides]
    • Single-image Noise Level Estimation for Blind Denoising (TIP 2014), Liu et al.

Novel Real Denoising Benchmark

  • ReNOIR [Web] [Data] [PDF]
    • RENOIR - A Dataset for Real Low-Light Image Noise Reduction (Arxiv 2014), Anaya, Barbu.
  • Darmstadt [Web] [Data] [PDF]
    • Benchmarking Denoising Algorithms with Real Photographs (CVPR 2017), Tobias Plotz, Stefan Roth.
  • PolyU [Web] [Data] [PDF]
    • Real-world Noisy Image Denoising: A New Benchmark (Arxiv), Xu et al.
  • SIDD [Web] [Data] [PDF]
    • A High-Quality Denoising Dataset for Smartphone Cameras (CV{R 2018), Abdelhamed et al.

Commonly Used Denoising Dataset

Commonly Used Image Quality Metrics

Open Source Agenda is not affiliated with "Reproducible Image Denoising State Of The Art" Project. README Source: wenbihan/reproducible-image-denoising-state-of-the-art