python去噪算法_最新可复现图像去噪算法汇总
reproducible-image-denoising-state-of-the-art
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)
Filtering
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
Kodak [Web]
USC SIPI-Misc [Web]
Commonly Used Image Quality Metrics
PSNR (Peak Signal-to-Noise Ratio) [Wiki] [Matlab Code] [Python Code]
NIQE (Naturalness Image Quality Evaluator) [Web] [Matlab Code] [Python Code]