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 3461–3470 of 7282 papers

TitleStatusHype
Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis—0
Hyperspectral Image Denoising via Global Spatial-Spectral Total Variation Regularized Nonconvex Local Low-Rank Tensor Approximation—0
Enhanced segmentation of femoral bone metastasis in CT scans of patients using synthetic data generation with 3D diffusion models—0
Hyperspectral Image Denoising with Log-Based Robust PCA—0
Controllable Diverse Sampling for Diffusion Based Motion Behavior Forecasting—0
Controllable Confidence-Based Image Denoising—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
Hyperspectral Image Recovery via Hybrid Regularization—0
Hyperspectral Image Denoising via Multi-modal and Double-weighted Tensor Nuclear Norm—0
Enhanced Low-Rank Matrix Approximation—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