mlsanityData to 7 Oct 2026

Plug-and-Play image restoration with Stochastic deNOising REgularization

arXiv 2402.01779 ↗First posted 1 Feb 2024eess.IV cs.CV cs.LGcited by 17

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Abstract (arXiv)

Plug-and-Play (PnP) algorithms are a class of iterative algorithms that address image inverse problems by combining a physical model and a deep neural network for regularization. Even if they produce impressive image restoration results, these algorithms rely on a non-standard use of a denoiser on images that are less and less noisy along the iterations, which contrasts with recent algorithms based on Diffusion Models (DM), where the denoiser is applied only on re-noised images. We propose a new PnP framework, called Stochastic deNOising REgularization (SNORE), which applies the denoiser only on images with noise of the adequate level. It is based on an explicit stochastic regularization, which leads to a stochastic gradient descent algorithm to solve ill-posed inverse problems. A convergence analysis of this algorithm and its annealing extension is provided. Experimentally, we prove that SNORE is competitive with respect to state-of-the-art methods on deblurring and inpainting tasks, both quantitatively and qualitatively.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 52 of its 83 references that are in the map. First posted on arXiv 1 Feb 2024.

Builds on

52 of 83 references.

References · 52

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  3. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  4. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  5. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,543
  6. 2022Diffusion Posterior Sampling for General Noisy Inverse Problemscited by 1,375
  7. 2022Denoising Diffusion Restoration Modelscited by 951
  8. 2013Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programmingcited by 716
  9. 2021Maximum Likelihood Training of Score-Based Diffusion Modelscited by 670
  10. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  11. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  12. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 526
38 more
  1. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  2. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraintscited by 501
  3. 2020Plug-and-Play Image Restoration with Deep Denoiser Priorcited by 467
  4. 2017Learning Deep CNN Denoiser Prior for Image Restorationcited by 407
  5. 2023Denoising Diffusion Models for Plug-and-Play Image Restorationcited by 335
  6. 2016The Little Engine that Could: Regularization by Denoising (RED)cited by 303
  7. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 284
  8. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 244
  9. 2022Convergence of denoising diffusion models under the manifold hypothesiscited by 237
  10. 2023A Variational Perspective on Solving Inverse Problems with Diffusion Modelscited by 217
  11. 2019Plug-and-Play Methods Provably Converge with Properly Trained Denoiserscited by 197
  12. 2021Gradient Step Denoiser for convergent Plug-and-Playcited by 107
  13. 2018Adversarial Regularizers in Inverse Problemscited by 102
  14. 2018Regularization by Denoising: Clarifications and New Interpretationscited by 102
  15. 2021Bayesian imaging using Plug & Play priors: when Langevin meets Tweediecited by 96
  16. 2022Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularizationcited by 79
  17. 2015Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolationcited by 78
  18. 2020Solving Linear Inverse Problems Using the Prior Implicit in a Denoisercited by 78
  19. 2022Multiscale Structure Guided Diffusion for Image Deblurringcited by 76
  20. 2018An Online Plug-and-Play Algorithm for Regularized Image Reconstructioncited by 70
  21. 2020Learning Maximally Monotone Operators for Image Recoverycited by 62
  22. 2022Verifying the Union of Manifolds Hypothesis for Image Datacited by 62
  23. 2020Regularization by Denoising via Fixed-Point Projection (RED-PRO)cited by 55
  24. 2023Provable Probabilistic Imaging using Score-Based Generative Priorscited by 51
  25. 2018prDeep: Robust Phase Retrieval with a Flexible Deep Networkcited by 46
  26. 2023Closed-Form Diffusion Modelscited by 46
  27. 2023Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inferencecited by 41
  28. 2019Block Coordinate Regularization by Denoisingcited by 33
  29. 2018Stochastic subgradient method converges at the rate O(k-1/4) on weakly convex functionscited by 31
  30. 2023Generative Plug and Play: Posterior Sampling for Inverse Problemscited by 24
  31. 2017Asymptotic Bias of Stochastic Gradient Searchcited by 19
  32. 2019An Inertial Newton Algorithm for Deep Learningcited by 14
  33. 2022On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descentcited by 14
  34. 2020A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problemscited by 12
  35. 2020SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategycited by 10
  36. 2023Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysiscited by 10
  37. 2023Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Modelscited by 8
  38. 2022PnP-ReG: Learned Regularizing Gradient for Plug-and-Play Gradient Descentcited by 7

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 6; 2026: 9.

17 papers.

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  1. 2025LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimizationcited by 14
  2. 2025Learning few-step posterior samplers by unfolding and distillation of diffusion modelscited by 5
  3. 2025Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Inverse Problemscited by 4
  4. 2026Beyond MMSE: Enhancing PnP Restoration with ProxiMAPcited by 2
  5. 2026NullFlow: One-Step Generative Reconstructioncited by 2
  6. 2024Equivariant Denoisers for Image Restorationcited by 1
  7. 2025Solving Inverse Problems using Diffusion with Iterative Colored Renoisingcited by 1
  8. 2025Fidelity-preserving enhancement of ptychography with foundational text-to-image modelscited by 1
  9. 2026Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Frameworkcited by 1
  10. 2024SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architecturescited by 0
  11. 2025Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurementscited by 0
  12. 2026Provably Contractive and High-Quality Denoisers for Convergent Restorationcited by 0
5 more
  1. 2026FlowADMM: Plug-and-play ADMM with Flow-based Renoise-Denoise Priorscited by 0
  2. 2026Multilevel Stochastic Plug-and-Play for Sparse-View CT Reconstructioncited by 0
  3. 2026Consistency Models for Fast MRI Reconstruction Using Regularization by Denoisingcited by 0
  4. 2026Convergent Plug-and-Play Image Restoration with Annealed Noise Levelscited by 0
  5. 2026Principled MAP estimation for inverse problems: bridging the gap between convergence and performancecited by 0

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  1. 2026Stochastic Generative Plug-and-Play Priors
  2. 2024PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
  3. 2025Image Restoration via Primal Dual Hybrid Gradient and Flow Generative Model
  4. 2025Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual
  5. 2025Multi Task Denoiser Training for Solving Linear Inverse Problems ↗
  6. 2024Plug-and-Play Priors as a Score-Based Method
  7. 2025Plug-and-Play Posterior Sampling for Blind Inverse Problems
  8. 2025Viscosity Stabilized Plug-and-Play Reconstruction ↗