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 4311–4320 of 7282 papers

TitleStatusHype
Image Denoising via Collaborative Dual-Domain Patch Filtering—0
Image Denoising Via Collaborative Support-Agnostic Recovery—0
Image denoising via group sparsity residual constraint—0
Image denoising via K-SVD with primal-dual active set algorithm—0
Image Denoising via Multi-scale Nonlinear Diffusion Models—0
Image Denoising via Style Disentanglement—0
Image denoising with generalized Gaussian mixture model patch priors—0
Image Denoising with Kernels based on Natural Image Relations—0
Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation—0
Image Deraining and Denoising Convolutional Neural Network ForAutonomous Driving—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