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Call for Papers - Recent Advances in Plug-and-Play Methods for Signal, Image and Video Processing: Theory, Algorithms, and Applications

Guest Editors:
Tatiana Gelvez-Barrera: Université de Lyon, Lyon, France
Marcus Carlsson: Centre for Mathematical Sciences, Lund University
Carlos Hinojosa: King Abdullah University of Science and Technology (KAUST)
Sayantan Dutta: Weill Cornell Medicine, New York, New York, USA

Submission Status: Open   |   Submission Deadline: 30 November 2023

This special issue of the EURASIP Journal on Image and Video Processing invites leading researchers and practitioners in academia and industry to contribute original research on recent theoretical advances, algorithmic developments, and practical applications of the plug-and-play framework. Topics include new denoising operators, adaptive plug-and-play algorithms, convergence analysis, hyperparameter tuning, robustness, stability analysis, and signal, imaging, and video processing applications.

Model-based inverse problem solutions typically use optimization formulations that balance data fidelity and prior information. Selecting a suitable prior is critical to designing algorithms that converge efficiently and produce high-quality reconstructions. Traditional hand-crafted regularization priors can have limitations in handling complex and high-dimensional data encountered in signal, image, and video processing. The plug-and-play framework is a promising approach to solving inverse problems that replace traditional regularization priors with sophisticated denoisers or methods without being tied to an explicit optimization objective. Instead, the regularization prior is integrated as an operator in an iterative algorithm that alternates between data fidelity and prior steps. Advanced algorithms, like a denoiser or a deep neural network, can perform the prior step, offering several advantages, including bypassing the need for explicit inversion of the forward model and incorporating diverse and flexible methods.

Recent research advances have focused on developing adaptive plug-and-play algorithms that automatically adjust the regularization strength and parameters during the iterative process. Other works have explored the theoretical properties of the plug-and-play framework, such as convergence rates and stability guarantees.

About the collection

Prospective authors are encouraged to submit unpublished manuscripts for publication in this Special Issue. Subject of interests include, but are not limited to:

• Theoretical foundations of plug-and-play methods
• Plug and play methods for inverse problems in computational imaging
• Deep learning based unfolding or unrolling methods
• Advance algorithms for model-based data inversion
• Deep proximal operatorsRegularization by denoising (RED)
• Variational models for inverse problems
• Plug and Play convergence analysis Inverse problems recovery guarantees
• Automatic parameter tuning
• Novel regularization terms mathematical formulation
• Plug and Play applications on image and video communications, electronic imaging, biomedical imaging, image and video systems, remote sensing, and geophysics.

Image credit: © agsandrew / Fotolia

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of Research Articles. Before submitting your manuscript, please ensure you have read our submission guidelines. Articles for this Collection should be submitted via our submission system. During the submission process, under the section additional information, you will be asked whether you are submitting to a Collection, please select "Recent Advances in Plug-and-Play Methods for Signal, Image and Video Processing: Theory, Algorithms, and Applications" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.