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Gradient and Multi Scale Feature Inspired Deep Blind Gaussian Denoiser

https://doi.org/10.1109/access.2022.3162608

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/tee.22223openalex-snapshot

Additive noise reduction in natural images using second‐generation wavelet transform hidden Markov models

inferredcites →https://doi.org/10.1007/978-3-030-01267-0_33openalex-snapshot

Deep Burst Denoising

inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot

U-Net: Convolutional Networks for Biomedical Image Segmentation

inferredcites →https://doi.org/10.1007/s00371-017-1439-9openalex-snapshot

Natural image noise removal using nonlocal means and hidden Markov models in transform domain

inferredcites →https://doi.org/10.1007/s10044-020-00871-yopenalex-snapshot

Densely connected network for impulse noise removal

inferredcites →https://doi.org/10.1007/s11042-019-7556-xopenalex-snapshot

A generative adversarial network for image denoising

inferredcites →https://doi.org/10.1016/j.neunet.2019.08.022openalex-snapshot

Image denoising using deep CNN with batch renormalization

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Attention-guided CNN for image denoising

inferredcites →https://doi.org/10.1016/j.neunet.2020.07.025openalex-snapshot

Deep learning on image denoising: An overview

inferredcites →https://doi.org/10.1016/j.patcog.2020.107639openalex-snapshot

Image denoising using complex-valued deep CNN

inferredcites →https://doi.org/10.1049/iet-ipr.2017.0389openalex-snapshot

Image denoising method based on a deep convolution neural network

inferredcites →https://doi.org/10.1049/trit.2018.1054openalex-snapshot

Enhanced CNN for image denoising

inferredcites →https://doi.org/10.1109/72.279181openalex-snapshot

Learning long-term dependencies with gradient descent is difficult

inferredcites →https://doi.org/10.1109/access.2019.2910879openalex-snapshot

Image Denoising via Multi-Scale Gated Fusion Network

inferredcites →https://doi.org/10.1109/access.2019.2917537openalex-snapshot

Adaptively Tuning a Convolutional Neural Network by Gate Process for Image Denoising

inferredcites →https://doi.org/10.1109/access.2019.2921451openalex-snapshot

Multi-Level Wavelet Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/access.2020.3040542openalex-snapshot

Multi-Wavelet Residual Dense Convolutional Neural Network for Image Denoising

inferredcites →https://doi.org/10.1109/access.2021.3061062openalex-snapshot

A Residual Dense U-Net Neural Network for Image Denoising

inferredcites →https://doi.org/10.1109/access.2021.3081697openalex-snapshot

BoostNet: A Boosted Convolutional Neural Network for Image Blind Denoising

inferredcites →https://doi.org/10.1109/access.2021.3084951openalex-snapshot

DRNet: A Deep Neural Network With Multi-Layer Residual Blocks Improves Image Denoising

inferredcites →https://doi.org/10.1109/cvpr.2012.6247952openalex-snapshot

Image denoising: Can plain neural networks compete with BM3D?

inferredcites →https://doi.org/10.1109/cvpr.2014.366openalex-snapshot

Weighted Nuclear Norm Minimization with Application to Image Denoising

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.300openalex-snapshot

Learning Deep CNN Denoiser Prior for Image Restoration

inferredcites →https://doi.org/10.1109/cvpr.2018.00179openalex-snapshot

Deep Back-Projection Networks for Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2018.00333openalex-snapshot

Image Blind Denoising with Generative Adversarial Network Based Noise Modeling

inferredcites →https://doi.org/10.1109/cvpr.2018.00344openalex-snapshot

Learning a Single Convolutional Super-Resolution Network for Multiple Degradations

inferredcites →https://doi.org/10.1109/cvpr.2019.00059openalex-snapshot

Feature Denoising for Improving Adversarial Robustness

inferredcites →https://doi.org/10.1109/cvpr.2019.00181openalex-snapshot

Toward Convolutional Blind Denoising of Real Photographs

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00196openalex-snapshot

Self2Self With Dropout: Learning Self-Supervised Denoising From Single Image

inferredcites →https://doi.org/10.1109/cvprw.2017.152openalex-snapshot

Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification

inferredcites →https://doi.org/10.1109/cvprw.2019.00262openalex-snapshot

Deep Iterative Down-Up CNN for Image Denoising

inferredcites →https://doi.org/10.1109/cvprw.2019.00263openalex-snapshot

Densely Connected Hierarchical Network for Image Denoising

inferredcites →https://doi.org/10.1109/cvprw50498.2020.00262openalex-snapshot

GradNet Image Denoising

inferredcites →https://doi.org/10.1109/gcce.2018.8574671openalex-snapshot

Non-blind Image Restoration Based on Convolutional Neural Network

inferredcites →https://doi.org/10.1109/iccv.2001.937655openalex-snapshot

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

inferredcites →https://doi.org/10.1109/iccv.2011.6126278openalex-snapshot

From learning models of natural image patches to whole image restoration

inferredcites →https://doi.org/10.1109/iccv.2015.62openalex-snapshot

An Efficient Statistical Method for Image Noise Level Estimation

inferredcites →https://doi.org/10.1109/iccv.2017.486openalex-snapshot

MemNet: A Persistent Memory Network for Image Restoration

inferredcites →https://doi.org/10.1109/iccvw54120.2021.00210openalex-snapshot

SwinIR: Image Restoration Using Swin Transformer

inferredcites →https://doi.org/10.1109/icip42928.2021.9506653openalex-snapshot

Deep Gaussian Denoiser Epistemic Uncertainty and Decoupled Dual-Attention Fusion

inferredcites →https://doi.org/10.1109/lsp.2017.2782270openalex-snapshot

Deep Shrinkage Convolutional Neural Network for Adaptive Noise Reduction

inferredcites →https://doi.org/10.1109/sibgrapi51738.2020.00022openalex-snapshot

Image Denoising using Attention-Residual Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/tgrs.2020.2993319openalex-snapshot

SAR Image Despeckling Employing a Recursive Deep CNN Prior

inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot

Image quality assessment: from error visibility to structural similarity

inferredcites →https://doi.org/10.1109/tip.2007.901238openalex-snapshot

Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering

inferredcites →https://doi.org/10.1109/tip.2017.2662206openalex-snapshot

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

inferredcites →https://doi.org/10.1109/tip.2018.2839891openalex-snapshot

FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising

inferredcites →https://doi.org/10.1109/tip.2018.2859044openalex-snapshot

Class-Aware Fully Convolutional Gaussian and Poisson Denoising

inferredcites →https://doi.org/10.1109/tip.2020.2976814openalex-snapshot

Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning

inferredcites →https://doi.org/10.1109/tmm.2020.3008057openalex-snapshot

Blind Image Denoising via Dynamic Dual Learning

inferredcites →https://doi.org/10.1109/tmm.2021.3094058openalex-snapshot

DBDnet: A Deep Boosting Strategy for Image Denoising

inferredcites →https://doi.org/10.1109/tpami.2020.2968521openalex-snapshot

Residual Dense Network for Image Restoration

inferredcites →https://doi.org/10.1109/tpami.2021.3088914openalex-snapshot

Plug-and-Play Image Restoration With Deep Denoiser Prior

inferredcites →https://doi.org/10.1109/tsp.2006.881199openalex-snapshot

$rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

inferredcites →https://doi.org/10.1109/tvcg.2019.2921336openalex-snapshot

Neural Style Transfer: A Review

inferredcites →https://doi.org/10.1109/vcip49819.2020.9301843openalex-snapshot

Deep Convolutional Neural Network Based on Multi-Scale Feature Extraction for Image Denoising

inferredcites →https://doi.org/10.1186/s42492-019-0016-7openalex-snapshot

Brief review of image denoising techniques

inferredcites →https://doi.org/10.5244/c.30.87openalex-snapshot

Wide Residual Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1007/s00034-025-03276-6openalex-snapshot

Multi-path Processing Structure for Multi-scale Feature Fusion in Speech Separation Transformer

inferred← citeshttps://doi.org/10.1007/s00500-023-09148-yopenalex-snapshot

Natural digital image mixed noise removal using regularization Perona–Malik model and pulse coupled neural networks

inferred← citeshttps://doi.org/10.1007/s11042-026-21385-5openalex-snapshot

SPCANet: spatial, pixel and channel attention guided deep image denoiser

inferred← citeshttps://doi.org/10.1007/s41064-026-00394-xopenalex-snapshot

MFEFC-Net: A Multi-Layer Feature Enhanced Frequency Correlation Network for Speckle Suppression

inferred← citeshttps://doi.org/10.1016/j.eswa.2024.125157openalex-snapshot

A high-quality self-supervised image denoising method based on SDDW-GAN and CHRNet

inferred← citeshttps://doi.org/10.1016/j.image.2025.117399openalex-snapshot

GIADNet: Gradient Inspired Attention Driven Denoising Network

inferred← citeshttps://doi.org/10.1016/j.patcog.2023.109603openalex-snapshot

Multi scale pixel attention and feature extraction based neural network for image denoising

inferred← citeshttps://doi.org/10.1109/igarss46834.2022.9883415openalex-snapshot

SIFSDNet: Sharp Image Feature Based SAR Denoising Network

inferred← citeshttps://doi.org/10.1109/indicon56171.2022.10040080openalex-snapshot

A Successive Variational Model for Multiplicative Noise and Blur Removal

inferred← citeshttps://doi.org/10.1109/indicon63790.2024.10958258openalex-snapshot

Gradient-Infused Multi-Scale Attention Based CNN for Robust Image Denoising

inferred← citeshttps://doi.org/10.1109/ingarss67683.2025.11583848openalex-snapshot

Deep Learning for Hyperspectral Image Denoising

inferred← citeshttps://doi.org/10.1109/ncc63735.2025.10983275openalex-snapshot

A Variational Model for Image Restoration under Blur and Noise using Nuclear Norm regularization

inferred← citeshttps://doi.org/10.1109/tencon55691.2022.9978143openalex-snapshot

Image Denoising based on Multi Domain Feature Inspired Convolutional Neural Network

inferred← citeshttps://doi.org/10.1109/tgrs.2024.3362510openalex-snapshot

LG-DBNet: Local and Global Dual-Branch Network for SAR Image Denoising

inferred← citeshttps://doi.org/10.1109/vcip56404.2022.10008856openalex-snapshot

Blind Gaussian Deep Denoiser Network using Multi-Scale Pixel Attention

inferred← citeshttps://doi.org/10.1117/12.2632954openalex-snapshot

Adversarial attacks for machine learning denoisers and how to resisit them

inferred← citeshttps://doi.org/10.2174/0118744400404813250924064413openalex-snapshot

A Review and Experimental Analysis of Denoising Techniques for Medical Images

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