mlsanityData to 7 Oct 2026

Diffusion Model for Generative Image Denoising

arXiv 2302.02398 ↗First posted 5 Feb 2023cs.CVcited by 27

On the map: Diffusion models → Diffusion foundations and sampling

Abstract (arXiv)

In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model. L2 norm loss or other distance functions are used as the objective function for training. It often leads to an over-smooth result with less image details. In this paper, we regard the denoising task as a problem of estimating the posterior distribution of clean images conditioned on noisy images. We apply the idea of diffusion model to realize generative image denoising. According to the noise model in denoising tasks, we redefine the diffusion process such that it is different from the original one. Hence, the sampling of the posterior distribution is a reverse process of dozens of steps from the noisy image. We consider three types of noise model, Gaussian, Gamma and Poisson noise. With the guarantee of theory, we derive a unified strategy for model training. Our method is verified through experiments on three types of noise models and achieves excellent performance.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 17 of its 33 references that are in the map. First posted on arXiv 5 Feb 2023.

Builds on

17 of 33 references.

Closest ancestors · 3

Same direction, newest first

  1. 2021Diffusion Models Beat GANs on Image Synthesis11 May
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equations26 Nov
  3. 2020Denoising Diffusion Probabilistic Models19 Jun

Other references · 14

  1. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  2. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  3. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  4. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  5. 2017FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoisingcited by 509
  6. 2020Learning Enriched Features for Real Image Restoration and Enhancementcited by 311
  7. 2018Toward Convolutional Blind Denoising of Real Photographscited by 274
  8. 2020CycleISP: Real Image Restoration via Improved Data Synthesiscited by 212
  9. 2019Real Image Denoising with Feature Attentioncited by 176
  10. 2019Variational Denoising Network: Toward Blind Noise Modeling and Removalcited by 117
  11. 2020Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalizationcited by 92
  12. 2020NBNet: Noise Basis Learning for Image Denoising with Subspace Projectioncited by 77
2 more
  1. 2021Invertible Denoising Network: A Light Solution for Real Noise Removalcited by 68
  2. 2022Trained Model in Supervised Deep Learning is a Conditional Risk Minimizercited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 12; 2025: 5; 2026: 3.

27 papers.

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  1. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  2. 2024IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illuminationcited by 67
  3. 2023Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensemblingcited by 17
  4. 2023DiffDP: Radiotherapy Dose Prediction via a Diffusion Modelcited by 13
  5. 2024MD-Dose: A diffusion model based on the Mamba for radiation dose predictioncited by 11
  6. 2024A Dataset and Benchmark for Copyright Infringement Unlearning from Text-to-Image Diffusion Modelscited by 11
  7. 2024On the Asymptotic Mean Square Error Optimality of Diffusion Modelscited by 10
  8. 2024Diff-Shadow: Global-guided Diffusion Model for Shadow Removalcited by 10
  9. 2023SVNR: Spatially-variant Noise Removal with Denoising Diffusioncited by 8
  10. 2023Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encodingcited by 5
  11. 2024Listening to the Noise: Blind Denoising with Gibbs Diffusioncited by 5
  12. 2024RLCP: A Reinforcement Learning-based Copyright Protection Method for Text-to-Image Diffusion Modelcited by 4
15 more
  1. 2025Inverse Flow and Consistency Modelscited by 4
  2. 2024ARTIST: Improving the Generation of Text-rich Images with Disentangled Diffusion Models and Large Language Modelscited by 3
  3. 2023SP-DiffDose: A Conditional Diffusion Model for Radiation Dose Prediction Based on Multi-Scale Fusion of Anatomical Structures, Guided by SwinTransformer and Projectorcited by 2
  4. 2024ODE-DPS: ODE-based Diffusion Posterior Sampling for Inverse Problems in Partial Differential Equationcited by 2
  5. 2025Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrappingcited by 2
  6. 2023DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Modelscited by 1
  7. 2024Visual Privacy Auditing with Diffusion Modelscited by 1
  8. 2024Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generationcited by 1
  9. 2025A Simple Combination of Diffusion Models for Better Quality Trade-Offs in Image Denoisingcited by 1
  10. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Reviewcited by 1
  11. 2024Investigating Self-Supervised Image Denoising with Denaturationcited by 0
  12. 2025Geometric Analysis of Magnetic Labyrinthine Stripe Evolution via Deep Learning Segmentationcited by 0
  13. 2026PedestrianDiffusion: Multimodal Generative Denoising and Dense State Estimation for Inertial Navigationcited by 0
  14. 2026γ-Bridge: A Look-Parametric Diffusion Bridgecited by 0
  15. 2026On the Diffusibility of High-Dimensional Latentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Real-World Denoising via Diffusion Model
  2. 2022Diffusion Models in Vision: A Survey
  3. 2022Image Embedding for Denoising Generative Models
  4. 2025Beyond Fixed Horizons: A Theoretical Framework for Adaptive Denoising Diffusions
  5. 2025Is Noise Conditioning Necessary for Denoising Generative Models?
  6. 2023Reconstruct-and-Generate Diffusion Model for Detail-Preserving Image Denoising
  7. 2021Non Gaussian Denoising Diffusion Models
  8. 2022Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models