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 17011710 of 7282 papers

TitleStatusHype
Non-local Meets Global: An Integrated Paradigm for Hyperspectral DenoisingCode1
Unprocessing Images for Learned Raw DenoisingCode1
Noise2Void - Learning Denoising from Single Noisy ImagesCode1
Deep Recurrent Neural Networks for ECG Signal DenoisingCode1
Fully Convolutional Pixel Adaptive Image DenoiserCode1
Toward Convolutional Blind Denoising of Real PhotographsCode1
From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image RestorationCode1
Speech Denoising with Deep Feature LossesCode1
Deep Energy Estimator NetworksCode1
k-Space Deep Learning for Accelerated MRICode1
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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