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 4301–4350 of 7282 papers

TitleStatusHype
Image Denoising using Attention-Residual Convolutional Neural Networks—0
Image Denoising Using Convolutional Autoencoder—0
Diffusion prior as a direct regularization term for FWI—0
Image denoising using group sparsity residual and external nonlocal self-similarity prior—0
Image Denoising Using Low Rank Minimization With Modified Noise Estimation—0
Image Denoising using New Adaptive Based Median Filters—0
Image Denoising using Optimally Weighted Bilateral Filters: A Sure and Fast Approach—0
Image Denoising Using Sparsifying Transform Learning and Weighted Singular Values Minimization—0
Image Denoising via Adaptive Soft-Thresholding Based on Non-Local Samples—0
Image Denoising via CNNs: An Adversarial Approach—0
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
Image Deraining via Self-supervised Reinforcement Learning—0
Image Edge Restoring Filter—0
Image enhancement in acoustic-resolution photoacoustic microscopy enabled by a novel directional algorithm—0
Image Generation from Contextually-Contradictory Prompts—0
Image Generation with Multimodal Priors using Denoising Diffusion Probabilistic Models—0
Image Inpainting Using Directional Tensor Product Complex Tight Framelets—0
Image Processing Tools for Financial Time Series Classification—0
A Domain Translation Framework with an Adversarial Denoising Diffusion Model to Generate Synthetic Datasets of Echocardiography Images—0
Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers—0
The Benefit of Distraction: Denoising Camera-Based Physiological Measurements Using Inverse Attention—0
Image Reconstruction Using Deep Learning—0
Image Reconstruction using Enhanced Vision Transformer—0
Image Restoration and Reconstruction using Variable Splitting and Class-adapted Image Priors—0
The Benefit of Distraction: Denoising Remote Vitals Measurements using Inverse Attention—0
The Blind Normalized Stein Variational Gradient Descent-Based Detection for Intelligent Random Access in Cellular IoT—0
Image Restoration using Autoencoding Priors—0
Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians—0
Image Restoration using Total Variation Regularized Deep Image Prior—0
The Brittleness of AI-Generated Image Watermarking Techniques: Examining Their Robustness Against Visual Paraphrasing Attacks—0
Image Restoration with Locally Selected Class-Adapted Models—0
A Domain Adaptation Regularization for Denoising Autoencoders—0
The conjugated null space method of blind PSF estimation and deconvolution optimization—0
Image Segmentation and Restoration Using Parametric Contours With Free Endpoints—0
Image Segmentation Using Overlapping Group Sparsity—0
Image Speckle Noise Denoising by a Multi-Layer Fusion Enhancement Method based on Block Matching and 3D Filtering—0
Sparse Solutions of a Class of Constrained Optimization Problems—0
Image Tag Completion by Low-rank Factorization with Dual Reconstruction Structure Preserved—0
Image-to-Image Translation with Diffusion Transformers and CLIP-Based Image Conditioning—0
The Deep Kernelized Autoencoder—0
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies—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