A multiresolution block-coordinate Plug-and-Play algorithm that decomposes the image into wavelet blocks and applies a block-wise denoiser network to only a subset of blocks at each iteration, selected through a stochastic Gauss-Southwell-inspired activation rule.
Abstract
Plug-and-Play methods are among the state-of-the-art approaches for image reconstruction, but they do not scale well with the image size. We propose a multiresolution block-coordinate Plug-and-Play algorithm that decomposes the image into wavelet blocks and applies a block-wise denoiser network to only a subset of blocks at each iteration, selected through a stochastic Gauss-Southwell-inspired activation rule. Numerical results on deblurring show that the proposed method outperforms the standard Plug-and-Play in different degradation regimes, and in particular the adaptive rule dynamically adjusts to the degradation regime to match the optimal activation rule in every context.
Plug-and-play (PnP) methods, which embed powerful image denoisers into classical optimization algorithms, have achieved remarkable performance on a variety of imaging inverse problems. However, most existing PnP frameworks impose regularization only in the spatial domain. In many practical settings, measurement noise i...
Wen-Jian Du, Jia Li· IEEE Transactions on Image P...· 0 citations
This work establishes convergence guarantees for a broad family of Plug-and-Play algorithms with annealed noise level, spanning deterministic methods (RED and PnP--PGD) and stochastic methods (SNORE, equivariant RED, and a variant of PnP--Flow) and proves asymptotic stationarity of the iterates with respect to this obj...
In this work, we study a class of structured non-convex and non-smooth optimization problems arising in imaging applications, where the objective is the sum of three functions. We consider the Davis-Yin splitting method, a FISTA-type accelerated variant, along with a quasi-Newton line-search method and a plug-and-play...
An optimization-based algorithm is developed to compute the decomposition and establish convergence properties of the resulting iterates that enables the development of regularization techniques that enhance the quality of reconstruction by preserving important signal characteristics while suppressing noise.
Andrea Ebner, Dirk A. Lorenz, Mathias Staudigl· 0 citations
A new phase field model for image decomposition and smoothing based on a modification of the Cahn-Hilliard equation which allows only the decomposition of phase values into multiple layers.
Acar Ruyam· Balkan Journal of Electrical...· 0 citations
Abstract.
Flow matching-based generative models have been integrated into the plug-and-play image restoration framework, and the resulting plug-and-play flow matching (PnP-Flow) model has achieved some remarkable empirical success for image restoration. However, the theoretical understanding of PnP-Flow lags its empir...
Fan Jia, Yu-Hao Huang, Shih-Hsin Wang et al.· SIAM Journal of Imaging Scie...· 0 citations
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