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 6901–6925 of 7282 papers

TitleStatusHype
Online Adaptation of Deep Architectures with Reinforcement Learning—0
Sparse Filtered SIRT for Electron Tomography—0
Transductive Adaptation of Black Box Predictions—0
A Domain Adaptation Regularization for Denoising Autoencoders—0
Denoising based on wavelets and deblurring via self-organizing map for Synthetic Aperture Radar images—0
Neural shrinkage for wavelet-based SAR despeckling—0
Denoising and compression in wavelet domain via projection onto approximation coefficients—0
Online Nonnegative Matrix Factorization with General Divergences—0
A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics—0
Generic 3D Convolutional Fusion for image restoration—0
Mesh Denoising based on Normal Voting Tensor and Binary Optimization—0
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment—0
Optimal Rates of Statistical Seriation—0
A Permutation-based Model for Crowd Labeling: Optimal Estimation and Robustness—0
Accelerated first-order primal-dual proximal methods for linearly constrained composite convex programming—0
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip ConnectionsCode0
Fast Multi-Layer Laplacian Enhancement—0
Non Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoisingCode0
Towards stationary time-vertex signal processing—0
SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder—0
A two-stage learning method for protein-protein interaction prediction—0
Machine Learning Techniques and Applications For Ground-based Image Analysis—0
Simultaneous Inpainting and Denoising by Directional Global Three-part Decomposition: Connecting Variational and Fourier Domain Based Image Processing—0
Convolution by Evolution: Differentiable Pattern Producing Networks—0
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets—0
Show:102550
← PrevPage 277 of 292Next →
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