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Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation [PDF]
13 pages, 11 ...
Charles Addison Bouman +2 more
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A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems
In the past two decades, nonlinear image reconstruction methods have led to substantial improvements in the capabilities of numerous imaging systems. Such methods are traditionally formulated as optimization problems that are solved iteratively by simultaneously enforcing data consistency and incorporating prior models.
Ulugbek Kamilov +2 more
exaly +4 more sources
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Plug-and-Play Priors for Multi-Shot Compressive Hyperspectral Imaging
IEEE Transactions on Image Processing, 2023Multi-shot coded aperture snapshot spectral imaging (CASSI) uses multiple measurement snapshots to encode the three-dimensional hyperspectral image (HSI). Increasing the number of snapshots will multiply the number of measurements, making CASSI system more appropriate for detailed spatial or spectrally rich scenes.
Ting Xie 0003, Licheng Liu, Lina Zhuang
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Plug-and-Play Priors as a Score-Based Method
Plug-and-play (PnP) methods are extensively used for solving imaging inverse problems by integrating physical measurement models with pre-trained deep denoisers as priors. Score-based diffusion models (SBMs) have recently emerged as a powerful framework for image generation by training deep denoisers to represent the score of the image prior.
Ulugbek Kamilov +2 more
exaly +4 more sources
A Novel Plug-and-Play SAR Reconstruction Framework Using Deep Priors
The reconstruction of synthetic aperture radar (SAR) images from phase history data is an ill-posed inverse problem. Existing reconstruction methods use regularization to tackle the ill-posed nature of the imaging task, while assuming a forward model or ...
Muhammed Burak Alver +2 more
exaly +2 more sources
Turning a denoiser into a super-resolver using plug and play priors
2016 IEEE International Conference on Image Processing (ICIP), 2016Denoising and Super-Resolution are two inverse problems that have been extensively studied. Over the years, these two tasks were treated as two distinct problems that deserve a different algorithmic solution. In this paper we wish to exploit the recently introduced Plug-and-Play Prior (PPP) approach [1] to connect between the two.
Alon Brifman, Yaniv Romano, Michael Elad
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Sharpening Hyperspectral Images Using Plug-and-Play Priors
2017This paper addresses the problem of fusing hyperspectral (HS) images of low spatial resolution and multispectral (MS) images of high spatial resolution into images of high spatial and spectral resolution. By assuming that the target image lives in a low dimensional subspace, the problem is formulated with respect to the latent representation ...
Afonso M. Teodoro +2 more
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Image Restoration and Reconstruction using Targeted Plug-and-Play Priors
IEEE Transactions on Computational Imaging, 2019Leveraging current state-of-the-art denoisers to tackle other inverse problems in imaging is a challenging task, which has recently been the topic of significant research effort. In this paper, we present several contributions to this research front, based on two fundamental building blocks: 1) the recently proposed plug-and-play framework, which ...
Afonso M. Teodoro +2 more
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PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction
2022Magnetic particle imaging (MPI) is a recent modality that enables high contrast and frame-rate imaging of the magnetic nanoparticle (MNP) distribution. Based on a measured system matrix, MPI reconstruction can be cast as an inverse problem that is commonly solved via regularized iterative optimization.
Baris Askin +5 more
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Deep Plug-and-Play MRI Reconstruction Based on Multiple Complementary Priors
Magnetic Resonance ImagingMagnetic resonance imaging (MRI) is widely used in clinical diagnosis as a safe, non-invasive, high-resolution medical imaging technology, but long scanning time has been a major challenge for this technology. The undersampling reconstruction method has become an important technical means to accelerate MRI by reducing the data sampling rate while ...
Xinling Liu
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