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 6201–6225 of 7282 papers

TitleStatusHype
Denoising based on wavelets and deblurring via self-organizing map for Synthetic Aperture Radar images—0
Denoising based Sequence-to-Sequence Pre-training for Text Generation—0
Denoising-based Turbo Message Passing for Compressed Video Background Subtraction—0
Denoising-based UNMT is more robust to word-order divergence than MASS-based UNMT—0
Denoising bivariate signals via smoothing and polarization priors—0
Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage—0
Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering—0
Denoising Cosine Similarity: A Theory-Driven Approach for Efficient Representation Learning—0
Denoising Criterion for Variational Auto-Encoding Framework—0
Denoising Designs-inherited Search Framework for Image Denoising—0
Denoising Dictionary Learning Against Adversarial Perturbations—0
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties—0
You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors—0
Denoising diffusion-based synthetic generation of three-dimensional (3D) anisotropic microstructures from two-dimensional (2D) micrographs—0
An Adapter based Multi-label Pre-training for Speech Separation and Enhancement—0
Denoising Diffusion Error Correction Codes—0
Denoising Diffusion for 3D Hand Pose Estimation from Images—0
Denoising Diffusion for Sampling SAT Solutions—0
Denoising Diffusion Gamma Models—0
A multistep segmentation algorithm for vessel extraction in medical imaging—0
Denoising Diffusion Medical Models—0
Structural Vibration Signal Denoising Using Stacking Ensemble of Hybrid CNN-RNN—0
Denoising Diffusion Models for Anomaly Localization in Medical Images—0
Denoising diffusion models for high-resolution microscopy image restoration—0
Denoising Diffusion Models for Inpainting of Healthy Brain Tissue—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