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

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Showing 351–400 of 1220 papers

TitleStatusHype
Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learning—0
Masked Image Training for Generalizable Deep Image DenoisingCode2
Zero-Shot Noise2Noise: Efficient Image Denoising without any Data—0
SUD^2: Supervision by Denoising Diffusion Models for Image Reconstruction—0
Hybrid Spectral Denoising Transformer with Guided AttentionCode1
Xformer: Hybrid X-Shaped Transformer for Image DenoisingCode1
Blind2Sound: Self-Supervised Image Denoising without Residual Noise—0
KBNet: Kernel Basis Network for Image RestorationCode2
Cloud K-SVD for Image DenoisingCode0
Self-Supervised Pre-Training for Deep Image Prior-Based Robust PET Image Denoising—0
Spatial-Frequency Attention for Image Denoising—0
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image DenoisingCode0
LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and DeblurringCode1
An Efficient and Robust Method for Chest X-Ray Rib Suppression that Improves Pulmonary Abnormality Diagnosis—0
Low Latency Video Denoising for Online Conferencing Using CNN Architectures—0
Explicit Diffusion of Gaussian Mixture Model Based Image Priors—0
A deep convolutional neural network for salt-and-pepper noise removal using selective convolutional blocksCode0
QS-ADN: Quasi-Supervised Artifact Disentanglement Network for Low-Dose CT Image Denoising by Local Similarity Among Unpaired DataCode0
How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk ControlCode1
Diffusion Model for Generative Image Denoising—0
NoiseTransfer: Image Noise Generation with Contrastive EmbeddingsCode0
Hierarchical Disentangled Representation for Invertible Image Denoising and Beyond—0
Mixed Attention Network for Hyperspectral Image DenoisingCode1
Image Restoration with Mean-Reverting Stochastic Differential EquationsCode2
Recent progress in image denoising: A training strategy perspective—0
Removing Structured Noise with Diffusion ModelsCode1
Representing Noisy Image Without DenoisingCode1
FEUNet: a flexible and effective U-shaped network for image denoisingCode0
Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --—0
WIRE: Wavelet Implicit Neural RepresentationsCode1
Skip-Attention: Improving Vision Transformers by Paying Less Attention—0
Task-specific Scene Structure RepresentationsCode1
Iterative Denoiser and Noise Estimator for Self-Supervised Image Denoising—0
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting—0
Noise2Info: Noisy Image to Information of Noise for Self-Supervised Image DenoisingCode0
Polarized Color Image Denoising—0
Deep Random Projector: Accelerated Deep Image PriorCode1
Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme Low-Light PhotographyCode1
Group Sparse Coding for Image Denoising—0
Single Cell Training on Architecture Search for Image Denoising—0
Learning to adapt unknown noise for hyperspectral image denoising—0
Noise2Contrast: Multi-Contrast Fusion Enables Self-Supervised Tomographic Image Denoising—0
FSID: Fully Synthetic Image Denoising via Procedural Scene GenerationCode4
Domino Denoise: An Accurate Blind Zero-Shot Denoiser using Domino Tilings—0
Quantum median filter for Total Variation image denoising—0
Fast Algorithm for Constrained Linear Inverse ProblemsCode0
Linear Combinations of Patches are Unreasonably Effective for Single-Image DenoisingCode0
Gradient Domain Weighted Guided Image Filtering—0
SinDDM: A Single Image Denoising Diffusion ModelCode1
Learn to See Faster: Pushing the Limits of High-Speed Camera with Deep Underexposed Image Denoising—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