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 3671–3680 of 7282 papers

TitleStatusHype
Examining Joint Demosaicing and Denoising for Single-, Quad-, and Nona-Bayer Patterns—0
Examining the Mapping Functions of Denoising Autoencoders in Singing Voice Separation—0
Example-based super-resolution for point-cloud video—0
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising—0
Explainable Deep Learning Framework for SERS Bio-quantification—0
Explainable Synthetic Image Detection through Diffusion Timestep Ensembling—0
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data—0
SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions—0
Explicit Diffusion of Gaussian Mixture Model Based Image Priors—0
Exploiting Model Sparsity in Adaptive MPC: A Compressed Sensing Viewpoint—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