mlsanityData to 7 Oct 2026

Alternative design of DeepPDNet in the context of image restoration

arXiv 2202.09810 ↗First posted 20 Feb 2022eess.IV cs.CV cs.LGcited by 1

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Abstract (arXiv)

This work designs an image restoration deep network relying on unfolded Chambolle-Pock primal-dual iterations. Each layer of our network is built from Chambolle-Pock iterations when specified for minimizing a sum of a ℓ2-norm data-term and an analysis sparse prior. The parameters of our network are the step-sizes of the Chambolle-Pock scheme and the linear operator involved in sparsity-based penalization, including implicitly the regularization parameter. A backpropagation procedure is fully described. Preliminary experiments illustrate the good behavior of such a deep primal-dual network in the context of image restoration on BSD68 database.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 18 of its 37 references that are in the map. First posted on arXiv 20 Feb 2022.

Builds on

18 of 37 references.

References · 18

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  3. 2017Learning Deep CNN Denoiser Prior for Image Restorationcited by 407
  4. 2020Deep Unfolding Network for Image Super-Resolutioncited by 253
  5. 2017Learned Primal-dual Reconstructioncited by 251
  6. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 244
  7. 2015Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restorationcited by 194
  8. 2018Multi-level Wavelet-CNN for Image Restorationcited by 184
  9. 2017Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problemscited by 107
  10. 2017A Review of Convolutional Neural Networks for Inverse Problems in Imagingcited by 81
  11. 2019Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learningcited by 60
  12. 2020Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problemscited by 38
6 more
  1. 2018Deep Unfolding of a Proximal Interior Point Method for Image Restorationcited by 23
  2. 2015Poisson Inverse Problems by the Plug-and-Play schemecited by 17
  3. 2020Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Networkcited by 12
  4. 2020A deep primal-dual proximal network for image restorationcited by 9
  5. 2019On the Proof of Fixed-Point Convergence for Plug-and-Play ADMMcited by 6
  6. 2014A Non-Local Structure Tensor Based Approach for Multicomponent Image Recovery Problemscited by 1

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Citing papers per year: 2023: 1.

1 paper.

  1. 2023Unfolded proximal neural networks for robust image Gaussian denoisingcited by 7