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 40714080 of 7282 papers

TitleStatusHype
Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis0
Training Diffusion Models with Federated Learning0
Multiview Hessian Discriminative Sparse Coding for Image Annotation0
A Fourier Space Perspective on Diffusion Models0
Multi-View Networks for Denoising of Arbitrary Numbers of Channels0
Training Energy-Based Models with Diffusion Contrastive Divergences0
Multi-View Treelet Transform0
Multi-wavelet residual dense convolutional neural network for image denoising0
Equal is Not Always Fair: A New Perspective on Hyperspectral Representation Non-Uniformity0
Mumford-Shah and Potts Regularization for Manifold-Valued Data with Applications to DTI and Q-Ball Imaging0
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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