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 3971–3980 of 7282 papers

TitleStatusHype
MRI denoising using Deep Learning and Non-local averaging—0
MRI denoising with a non-blind deep complex-valued convolutional neural network—0
MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion—0
MR imaging in the low-field: Leveraging the power of machine learning—0
MRI motion correction via efficient residual-guided denoising diffusion probabilistic models—0
MRI Recovery with A Self-calibrated Denoiser—0
MRIR: Integrating Multimodal Insights for Diffusion-based Realistic Image Restoration—0
MS-UNet-v2: Adaptive Denoising Method and Training Strategy for Medical Image Segmentation with Small Training Data—0
TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking—0
Mu^2SLAM: Multitask, Multilingual Speech and Language Models—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