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

Showing 19011910 of 7282 papers

TitleStatusHype
Denoising random forests0
Denoising Imaging Polarimetry by an Adapted BM3D Method0
Denoising Hyperspectral Image with Non-i.i.d. Noise Structure0
Blind Channel Estimation for Massive MIMO: A Deep Learning Assisted Approach0
Blockwise SURE Shrinkage for Non-Local Means0
Denoising Score Matching with Random Fourier Features0
Diffusion Models to Enhance the Resolution of Microscopy Images: A Tutorial0
Denoising Self-attentive Sequential Recommendation0
Diffusion Models: Tutorial and Survey0
DiffusionPID: Interpreting Diffusion via Partial Information Decomposition0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified