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 6801–6825 of 7282 papers

TitleStatusHype
An Extended Framework for Marginalized Domain AdaptationCode0
Analyzing the Weighted Nuclear Norm Minimization and Nuclear Norm Minimization based on Group Sparse Representation—0
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines—0
Deep Kernelized Autoencoders—0
Scene-adapted plug-and-play algorithm with convergence guarantees—0
Using Complex Wavelet Transform and Bilateral Filtering for Image Denoising—0
A method of limiting performance loss of CNNs in noisy environments—0
Side Information in Robust Principal Component Analysis: Algorithms and Applications—0
Eye-Movement behavior identification for AD diagnosis—0
Density—0
Denoising Hyperspectral Image with Non-i.i.d. Noise Structure—0
A New Method for Removing the Moire' Pattern from Images—0
Pruned non-local means—0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Deep Convolutional Denoising of Low-Light ImagesCode1
Deep Class Aware DenoisingCode0
Image denoising using group sparsity residual and external nonlocal self-similarity prior—0
Modeling documents with Generative Adversarial Networks—0
Signature of Geometric Centroids for 3D Local Shape Description and Partial Shape Matching—0
Joint denoising and distortion correction of atomic scale scanning transmission electron microscopy images—0
Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising—0
Local Sparse Approximation for Image Restoration with Adaptive Block Size Selection—0
Deeply Aggregated Alternating Minimization for Image Restoration—0
Cloud Dictionary: Sparse Coding and Modeling for Point CloudsCode0
A Multilinear Tongue Model Derived from Speech Related MRI Data of the Human Vocal TractCode0
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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