Jul 2, 2020 · We reformulate a specific instance of the Condat-Vu primal-dual hybrid gradient (PDHG) algorithm as a deep network with fixed layers. The ...

Dec 20, 2021 · Finally, the proposed network is evaluated on image restoration and single image super-resolution problems with different levels of complexity.

Mar 25, 2024 · In this work, a deep encoder-decoder based primal-dual proximal network is proposed for image restoration task. We firstly reformulate the ...

This work designs a deep network, named DeepPDNet, built from primal-dual proximal iterations associated with the minimization of a standard penalized ...

In this work, we design a deep network, named DeepPDNet, built from primal-dual proximal iterations associated with the minimization of a standard penalized ...

Image restoration is a popular and challenge task, which is regarded as a classical inverse problem. Condat-V ũ primal-dual algorithm based on proximal ...

Jan 5, 2024 · The adaptive fully variable partial differential image restoration model proposed in this paper has the characteristics of good edge protection ...

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 ...

A deep primal-dual proximal network for image restoration ... In this work, we design a deep network, named DeepPDNet, built from primal-dual proximal iterations ...

Apr 25, 2024 · A Deep Primal-Dual Proximal Network for Image Restoration. IEEE J. Sel. Top. Signal Process. 15(2): 190-203 (2021). [c9]. view. electronic ...