SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5601–5625 of 7282 papers

TitleStatusHype
A Generative Adversarial Approach To ECG Synthesis And DenoisingCode0
Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User CommunicationsCode1
Extensions to the Proximal Distance Method of Constrained Optimization—0
Open-set Adversarial DefenseCode1
Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage—0
Operational vs Convolutional Neural Networks for Image Denoising—0
Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy—0
Unpaired Learning of Deep Image DenoisingCode1
Self-Organized Operational Neural Networks for Severe Image Restoration Problems—0
PCB Defect Detection Using Denoising Convolutional Autoencoders—0
Mixed Noise Removal with Pareto Prior—0
FLIP: A Difference Evaluator for Alternating ImagesCode1
Coupling BM3D with directional wavelet packets for image denoising—0
Deep Variational Network Toward Blind Image RestorationCode1
Block-wise Minimization-Majorization algorithm for Huber's criterion: sparse learning and applicationsCode1
Efficient Blind-Spot Neural Network Architecture for Image Denoising—0
A Critical Analysis of Patch Similarity Based Image Denoising Algorithms—0
Community-Aware Graph Signal Processing—0
PNEN: Pyramid Non-Local Enhanced Networks—0
Unsupervised Hyperspectral Mixed Noise Removal Via Spatial-Spectral Constrained Deep Image Prior—0
Spectral independent component analysis with noise modeling for M/EEG source separation—0
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image PriorCode1
Improving Blind Spot Denoising for MicroscopyCode1
Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography—0
Generative Adversarial Networks for Robust Cryo-EM Image DenoisingCode0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified