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

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Showing 6851–6900 of 7282 papers

TitleStatusHype
Learning Deep Representations Using Convolutional Auto-encoders with Symmetric Skip ConnectionsCode0
Dictionary Learning with Equiprobable Matching Pursuit—0
Times series averaging and denoising from a probabilistic perspective on time-elastic kernelsCode0
Semi-supervised Learning using Denoising Autoencoders for Brain Lesion Detection and Segmentation—0
Image Segmentation Using Overlapping Group Sparsity—0
Straight to Shapes: Real-time Detection of Encoded ShapesCode0
Learning to Distill: The Essence Vector Modeling Framework—0
Non-Local Color Image Denoising with Convolutional Neural Networks—0
Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution—0
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold SimplificationCode0
Reweighted Low-Rank Tensor Decomposition based on t-SVD and its Applications in Video Denoising—0
Mesh Denoising via Cascaded Normal Regression—0
Motion Estimated-Compensated Reconstruction with Preserved-Features in Free-Breathing Cardiac MRI—0
Can fully convolutional networks perform well for general image restoration problems?—0
The Little Engine that Could: Regularization by Denoising (RED)Code0
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks—0
Point Cloud Denoising via Moving RPCA: MRPCA—0
Stationary time-vertex signal processing—0
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction—0
Learning Adaptive Parameter Tuning for Image Processing—0
Sparse Signal Subspace Decomposition Based on Adaptive Over-complete Dictionary—0
Automated OCT Segmentation for Images with DME—0
Multispectral image denoising with optimized vector non-local mean filter—0
Deep Identity-aware Transfer of Facial Attributes—0
Amortised MAP Inference for Image Super-resolution—0
Statistical Inference Using Mean Shift Denoising—0
Quantum spectral analysis: frequency in time, with applications to signal and image processing—0
Restoring STM images via Sparse Coding: noise and artifact removal—0
A New Data Representation Based on Training Data Characteristics to Extract Drug Named-Entity in Medical Text—0
Neural-based Noise Filtering from Word EmbeddingsCode0
Neural Structural Correspondence Learning for Domain AdaptationCode0
Near-Infrared Coloring via a Contrast-Preserving Mapping Model—0
Nonsymbolic Text Representation—0
Low-dose CT denoising with convolutional neural network—0
Retrieval Term Prediction Using Deep Learning Methods—0
Tensor Based Second Order Variational Model for Image Reconstruction—0
Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches—0
Image Denoising via Multi-scale Nonlinear Diffusion Models—0
Poisson Noise Reduction with Higher-order Natural Image Prior Model—0
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signalsCode0
Image denoising via group sparsity residual constraint—0
Learning Sparse Graphs Under Smoothness Prior—0
Rectifier Neural Network with a Dual-Pathway Architecture for Image Denoising—0
An empirical study on the effects of different types of noise in image classification tasksCode0
Image Denoising Via Collaborative Support-Agnostic Recovery—0
Adaptive Regularization in Convex Composite Optimization for Variational Imaging Problems—0
Guided Filter based Edge-preserving Image Non-blind Deconvolution—0
An Adaptive Parameter Estimation for Guided Filter based Image Deconvolution—0
Convexified Convolutional Neural NetworksCode0
MindX: Denoising Mixed Impulse Poisson-Gaussian Noise Using Proximal Algorithms—0
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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