SOTAVerified

Image Denoising

Image Denoising is a computer vision task that involves removing noise from an image. Noise can be introduced into an image during acquisition or processing, and can reduce image quality and make it difficult to interpret. Image denoising techniques aim to restore an image to its original quality by reducing or removing the noise, while preserving the important features of the image.

( Image credit: Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 801–850 of 1220 papers

TitleStatusHype
3D Quasi-Recurrent Neural Network for Hyperspectral Image DenoisingCode1
Restore from Restored: Single Image Denoising with Pseudo Clean Image—0
ADRN: Attention-based Deep Residual Network for Hyperspectral Image Denoising—0
Gauss-Newton Unrolled Neural Networks and Data-driven Priors for Regularized PSSE with Robustness—0
Single-exposure absorption imaging of ultracold atoms using deep learningCode1
Flashlight CNN Image DenoisingCode0
Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising—0
Momentum-Net for Low-Dose CT Image Reconstruction—0
Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance NormalizationCode0
Generalized Octave Convolutions for Learned Multi-Frequency Image CompressionCode0
Self-Supervised Poisson-Gaussian DenoisingCode1
Multi-wavelet residual dense convolutional neural network for image denoising—0
NoiseBreaker: Gradual Image Denoising Guided by Noise Analysis—0
Reconstructing the Noise Manifold for Image Denoising—0
Differentiable Forward and Backward Fixed-Point Iteration Layers—0
Noise2Inverse: Self-supervised deep convolutional denoising for tomographyCode1
Spatial-Adaptive Network for Single Image DenoisingCode1
Ada-LISTA: Learned Solvers Adaptive to Varying ModelsCode1
Depth Completion Using a View-constrained Deep Prior—0
CNN-based InSAR Denoising and Coherence MetricCode1
Image denoising via K-SVD with primal-dual active set algorithm—0
Implementation of the VBM3D Video Denoising Method and Some VariantsCode1
First image then video: A two-stage network for spatiotemporal video denoisingCode0
Deep Learning on Image Denoising: An overview—0
Scale-wise Convolution for Image RestorationCode1
Image Restoration using Plug-and-Play CNN MAP DenoisersCode0
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image ProcessingCode0
Image Processing Using Multi-Code GAN PriorCode0
Spatial-Frequency Domain Nonlocal Total Variation for Image Denoising—0
Quantum-Inspired Hamiltonian Monte Carlo for Bayesian SamplingCode0
Deep Learning based Switching Filter for Impulsive Noise Removal in Color ImagesCode0
Noise2Blur: Online Noise Extraction and Denoising—0
Fully Unsupervised Probabilistic Noise2VoidCode0
Noise Robust Generative Adversarial NetworksCode0
Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy—0
Fast and Flexible Image Blind Denoising via Competition of Experts—0
FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems—0
LIDIA: Lightweight Learned Image Denoising with Instance AdaptationCode0
Adaptive Rates for Total Variation Image Denoising—0
Scientific Image Restoration AnywhereCode1
Approximate Bayesian Computation with the Sliced-Wasserstein DistanceCode0
Noisier2Noise: Learning to Denoise from Unpaired Noisy DataCode0
Mobile Recognition of Wikipedia Featured Sites using Deep Learning and Crowd-sourced Imagery—0
KRNET: Image Denoising with Kernel Regulation Network—0
Image Restoration Using Deep Regulated Convolutional NetworksCode0
OpenDenoising: an Extensible Benchmark for Building Comparative Studies of Image DenoisersCode0
Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst ImagesCode0
SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT PerfusionCode0
Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image DenoisingCode0
ERNet Family: Hardware-Oriented CNN Models for Computational Imaging Using Block-Based Inference—0
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All datasetsSIDDDNDELD SonyA7S2 x200SID SonyA7S2 x250ELD SonyA7S2 x100SID x100SID x300SID SonyA7S2 x100urban100 sigma15Urban100 sigma50BSD68 sigma50SID SonyA7S2 x300

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CGNetPSNR (sRGB)40.39—Unverified
2KBNetPSNR (sRGB)40.35—Unverified
3NAFNetPSNR (sRGB)40.3—Unverified
4SSAMANPSNR (sRGB)40.08—Unverified
5PNGANPSNR (sRGB)40.07—Unverified
6RestormerPSNR (sRGB)40.02—Unverified
7HINetPSNR (sRGB)39.99—Unverified
8MAXIM-3SPSNR (sRGB)39.96—Unverified
9Uformer-BPSNR (sRGB)39.89—Unverified
10SRMNetPSNR (sRGB)39.72—Unverified
#ModelMetricClaimedVerifiedStatus
1DualDnPSNR (sRGB)40.59—Unverified
2PNGANPSNR (sRGB)40.18—Unverified
3SSAMANPSNR (sRGB)40.05—Unverified
4RestormerPSNR (sRGB)40.03—Unverified
5Uformer-BPSNR (sRGB)39.98—Unverified
6NBNetPSNR (sRGB)39.89—Unverified
7MIRNetPSNR (sRGB)39.88—Unverified
8MAXIM-3SPSNR (sRGB)39.84—Unverified
9MPRNetPSNR (sRGB)39.8—Unverified
10SADNetPSNR (sRGB)39.59—Unverified
#ModelMetricClaimedVerifiedStatus
1LLD*PSNR (Raw)44.95—Unverified
2PMNPSNR (Raw)44.51—Unverified
3SFRNPSNR (Raw)44.1—Unverified
4LLDPSNR (Raw)43.84—Unverified
5ELDPSNR (Raw)43.43—Unverified
6LRDPSNR (Raw)43.32—Unverified
7Paired Data(SID)PSNR (Raw)41.97—Unverified
8StarlightPSNR (Raw)40.86—Unverified
9ExposureDiffusion (UNet+ELD)PSNR (Raw)40.39—Unverified
10Noise FlowPSNR (Raw)39.23—Unverified
#ModelMetricClaimedVerifiedStatus
1LLD*PSNR (Raw)41.02—Unverified
2PMNPSNR (Raw)40.92—Unverified
3SFRNPSNR (Raw)40.22—Unverified
4LLDPSNR (Raw)39.76—Unverified
5Paired Data (SID)PSNR (Raw)39.6—Unverified
6ELDPSNR (Raw)39.44—Unverified
7LEDPSNR (Raw)39.34—Unverified
8LRDPSNR (Raw)39.25—Unverified
9StarlightPSNR (Raw)36.25—Unverified
10Noise FlowPSNR (Raw)35.8—Unverified
#ModelMetricClaimedVerifiedStatus
1LLD*PSNR (Raw)46.74—Unverified
2PMNPSNR (Raw)46.5—Unverified
3SFRNPSNR (Raw)46.02—Unverified
4LLDPSNR (Raw)45.61—Unverified
5ELDPSNR (Raw)45.45—Unverified
6LRDPSNR (Raw)44.95—Unverified
7Paired Data(SID)PSNR (Raw)44.47—Unverified
8StarlightPSNR (Raw)43.8—Unverified
9Noise FlowPSNR (Raw)41.05—Unverified
#ModelMetricClaimedVerifiedStatus
1LLD*PSNR (Raw)43.36—Unverified
2PMNPSNR (Raw)43.16—Unverified
3SFRNPSNR (Raw)42.29—Unverified
4LLDPSNR (Raw)42.1—Unverified
5SID (paired real data)PSNR (Raw)42.06—Unverified
6ELDPSNR (Raw)41.95—Unverified
7StarlightPSNR (Raw)40.47—Unverified
8Noise FlowPSNR (Raw)38.89—Unverified
#ModelMetricClaimedVerifiedStatus
1LLD*PSNR (Raw)37.8—Unverified
2PMNPSNR (Raw)37.77—Unverified
3SFRNPSNR (Raw)36.87—Unverified
4Paired Data(SID)PSNR (Raw)36.85—Unverified
5LLDPSNR (Raw)36.76—Unverified
6ELDPSNR (Raw)36.36—Unverified
7StarlightPSNR (Raw)32.99—Unverified
8Noise FlowPSNR (Raw)32.29—Unverified
#ModelMetricClaimedVerifiedStatus
1PMNPSNR (Raw)43.16—Unverified
2SFRNPSNR (Raw)42.29—Unverified
3LEDPSNR (Raw)41.98—Unverified
4ELDPSNR (Raw)41.95—Unverified
5LRDPSNR (Raw)41.95—Unverified
#ModelMetricClaimedVerifiedStatus
1AKDTAverage PSNR35.64—Unverified
2MaIR+PSNR35.42—Unverified
3MaIRPSNR35.35—Unverified
4SCUNet SCUNetAverage PSNR35.18—Unverified
#ModelMetricClaimedVerifiedStatus
1MaIR+PSNR30.41—Unverified
2MaIRPSNR30.3—Unverified
3SCUNet SCUNetPSNR30.14—Unverified
4AKDTPSNR29.82—Unverified
#ModelMetricClaimedVerifiedStatus
1MaIR+PSNR30.08—Unverified
2MaIRPSNR28.66—Unverified
#ModelMetricClaimedVerifiedStatus
1LEDPSNR (Raw)36.67—Unverified
2LRDPSNR (Raw)36.03—Unverified
#ModelMetricClaimedVerifiedStatus
1MaIR+PSNR33.3—Unverified
2MaIRPSNR33.22—Unverified
#ModelMetricClaimedVerifiedStatus
1R3LPSNR27.67—Unverified
#ModelMetricClaimedVerifiedStatus
1BRGMLPIPS0.24—Unverified
#ModelMetricClaimedVerifiedStatus
1BRGMLPIPS0.24—Unverified
#ModelMetricClaimedVerifiedStatus
1ExposureDiffusion (UNet+paired data)PSNR (Raw)36.82—Unverified
#ModelMetricClaimedVerifiedStatus
1PNGANPSNR40.78—Unverified
#ModelMetricClaimedVerifiedStatus
1PNGANPSNR40.55—Unverified
#ModelMetricClaimedVerifiedStatus
1absDLODRMSE0.07—Unverified