Color Image Denoising

Benchmarks archive 2025-07-28

80 leaderboard tables shown for this task, 80 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 80 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

9 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 32 papers with code (51 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
  13 Aug 2016 22 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  Discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance.
• Residual Dense Network for Image Super-Resolution
  24 Feb 2018 16 repositories listed Syntology ran 7 of 24 samples · 17 unverified · 1 pointer-only (licence)
  In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR.
• Restormer: Efficient Transformer for High-Resolution Image Restoration
  18 Nov 2021 13 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restoration and related tasks.
• SwinIR: Image Restoration Using Swin Transformer
  23 Aug 2021 9 repositories listed Syntology ran 30 of 45 samples · 15 unverified · 5 pointer-only (licence)
  In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.
• FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
  11 Oct 2017 8 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising.
• Pre-Trained Image Processing Transformer
  1 Dec 2020 6 repositories listed
  To maximally excavate the capability of transformer, we present to utilize the well-known ImageNet benchmark for generating a large amount of corrupted image pairs.
• Improving Image Restoration by Revisiting Global Information Aggregation
  8 Dec 2021 3 repositories listed
  Our TLC converts global operations to local ones only during inference so that they aggregate features within local spatial regions rather than the entire large images.
• Real Image Denoising with Feature Attention
  16 Apr 2019 3 repositories listed
  Deep convolutional neural networks perform better on images containing spatially invariant noise (synthetic noise); however, their performance is limited on real-noisy photographs and requires multiple stage network…
• LYT-NET: Lightweight YUV Transformer-based Network for Low-light Image Enhancement
  26 Jan 2024 2 repositories listed
  This letter introduces LYT-Net, a novel lightweight transformer-based model for low-light image enhancement (LLIE).
• Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
  5 Jul 2019 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  Blind and universal image denoising consists of using a unique model that denoises images with any level of noise.
• MemNet: A Persistent Memory Network for Image Restoration
  7 Aug 2017 2 repositories listed
  We apply MemNet to three image restoration tasks, i.
• Learning Deep CNN Denoiser Prior for Image Restoration
  11 Apr 2017 2 repositories listed
  Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e.
• DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables
  20 Mar 2025 1 repository listed
  While deep neural networks have revolutionized image denoising capabilities, their deployment on edge devices remains challenging due to substantial computational and memory requirements.
• AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising
  26 Feb 2025 1 repository listed
  At the core of AKDT, the NE is seamlessly integrated within standard Transformer components to form the Noise-Guided Feed-Forward Network (NG-FFN) and Noise-Guided Multi-Headed Self-Attention (NG-MSA).
• Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
  5 May 2024 1 repository listed Syntology ran 11 of 12 samples · 1 unverified · 11 pointer-only (licence)
  In this work, we propose a novel Residual-Conditioned Optimal Transport (RCOT) approach, which models image restoration as an optimal transport (OT) problem for both unpaired and paired settings, introducing the…
• Color Image Denoising Using The Green Channel Prior
  13 Feb 2024 1 repository listed
  In this paper, we propose a simple and effective one step GCP-based image denoising (GCP-ID) method, which aims to exploit the GCP for denoising in the sRGB space by integrating it into the classic nonlocal transform…
• A Theoretically Guaranteed Quaternion Weighted Schatten p-norm Minimization Method for Color Image Restoration
  24 Jul 2023 1 repository listed
  Very recently, a quaternion-based WNNM approach (QWNNM) has been developed to mitigate this issue, which is capable of representing the color image as a whole in the quaternion domain and preserving the inherent…
• A Novel Truncated Norm Regularization Method for Multi-channel Color Image Denoising
  16 Jul 2023 1 repository listed
  However, those methods mostly ignore either the cross-channel difference or the spatial variation of noise, which limits their capacity in real world color image denoising.
• Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
  8 Jul 2023 1 repository listed
  Image denoising is a fundamental problem in computational photography, where achieving high perception with low distortion is highly demanding.
• Towards Resilient and Secure Smart Grids against PMU Adversarial Attacks: A Deep Learning-Based Robust Data Engineering Approach
  6 Jun 2023 1 repository listed
  In an attempt to provide reliable power distribution, smart grids integrate monitoring, communication, and control technologies for better energy consumption and management.
• KBNet: Kernel Basis Network for Image Restoration
  6 Mar 2023 1 repository listed Syntology ran 6 of 9 samples · 3 unverified
  In this paper, we propose a kernel basis attention (KBA) module, which introduces learnable kernel bases to model representative image patterns for spatial information aggregation.
• Hypernetwork-Based Adaptive Image Restoration
  13 Jun 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Adaptive image restoration models can restore images with different degradation levels at inference time without the need to retrain the model.
• Adversarial Distortion Learning for Medical Image Denoising
  29 Apr 2022 1 repository listed
  The proposed ADL consists of two auto-encoders: a denoiser and a discriminator.
• Patch Craft: Video Denoising by Deep Modeling and Patch Matching
  25 Mar 2021 1 repository listed Syntology ran 4 of 8 samples · 4 unverified · 8 pointer-only (licence)
  Our algorithm augments video sequences with patch-craft frames and feeds them to a CNN.
• Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNN
  8 Dec 2020 1 repository listed
  We demonstrate the capabilities of the proposed 3-stage structure with three typical color image restoration tasks: color image demosaicking, color compression artifacts reduction, and real-world color image denoising.
• Rank-One Network: An Effective Framework for Image Restoration
  25 Nov 2020 1 repository listed
  The RO decomposition is developed to decompose a corrupted image into the RO components and residual.
• Rethinking the CSC Model for Natural Images
  12 Sep 2019 1 repository listed
  Sparse representation with respect to an overcomplete dictionary is often used when regularizing inverse problems in signal and image processing.
• A Brief Review of Real-World Color Image Denoising
  10 Sep 2018 1 repository listed
  Filtering real-world color images is challenging due to the complexity of noise that can not be formulated as a certain distribution.
• Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising
  13 Jun 2018 1 repository listed
  In this work, we propose a new method for natural image denoising that trains a deep neural network to determine whether patches in a noisy image input share common underlying patterns.
• Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification
  19 Nov 2016 1 repository listed
  To address this issue, here we propose a novel feature space deep residual learning algorithm that outperforms the existing residual learning.

Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.