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 3531–3540 of 7282 papers

TitleStatusHype
Deep learning denoising for EOG artifacts removal from EEG signals—0
Image Denoising via CNNs: An Adversarial Approach—0
Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows—0
Image Denoising Via Collaborative Support-Agnostic Recovery—0
Image denoising via group sparsity residual constraint—0
Image denoising via K-SVD with primal-dual active set algorithm—0
Deep learning denoiser assisted roughness measurements extraction from thin resists with low Signal-to-Noise Ratio(SNR) SEM images: analysis with SMILE—0
Image Denoising via Style Disentanglement—0
Auxiliary Features-Guided Super Resolution for Monte Carlo Rendering—0
Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain—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