Results 211 to 220 of about 1,202 (247)
Automatic modeling of high genus geological bodies using improved EdgeConnect and deep plug and play super resolution GAN. [PDF]
Sci RepRen B, Zuo Y, Han S, Song Y.
europepmc +1 more source
Plug-and-Play Priors for Model Based Reconstruction [PDF]
2013 IEEE Global Conference on Signal and Information Processing, 2013 Model-based reconstruction is a powerful framework for solving a variety of inverse problems in imaging. In recent years, enormous progress has been made in the problem of denoising, a special case of an inverse problem where the forward model is an identity operator.
Charles Addison Bouman +2 more
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Face Restoration via Plug-and-Play 3D Facial Priors [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 State-of-the-art face restoration methods employ deep convolutional neural networks (CNNs) to learn a mapping between degraded and sharp facial patterns by exploring local appearance knowledge. However, most of these methods do not well exploit facial structures and identity information, and only deal with task-specific face restoration (e.g.,face ...
Wenqi Ren, Hongbin Zha, Xiaochun Cao
exaly +7 more sources
Plug-and-Play Synthetic Aperture Radar Image Formation Using Deep Priors
IEEE Transactions on Computational Imaging, 2021 The reconstruction of synthetic aperture radar (SAR) images from phase history data is an ill-posed inverse problem which, in several lines of recent work, is solved by minimizing a cost function. Existing reconstruction methods use regularization to tackle the ill-posed nature of the imaging task. However, in general, these regularizers are either too
Muhammed Burak Alver +2 more
exaly +6 more sources
A Plug-and-Play Priors Framework for Hyperspectral Unmixing [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Spectral unmixing is a widely used technique in hyperspectral image processing and analysis. It aims to separate mixed pixels into the component materials and their corresponding abundances. Early solutions to spectral unmixing are performed independently on each pixel. Nowadays, investigating proper priors into the unmixing problem has been popular as
Wei Chen, Jie Chen, Min Zhao
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Deep Learning for Linear Inverse Problems Using the Plug-and-Play Priors Framework [PDF]
, 2021 Linear inverse problems appear in many applications, where different algorithms are typically employed to solve each inverse problem. Nowadays, the rapid development of deep learning (DL) provides a fresh perspective for solving the linear inverse ...
Miguel R D Rodrigues
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Provable Convergence of Plug-and-Play Priors With MMSE Denoisers
IEEE Signal Processing Letters, 2020 Plug-and-play priors (PnP) is a methodology for regularized image reconstruction that specifies the prior through an image denoiser. While PnP algorithms are well understood for denoisers performing maximum a posteriori probability (MAP) estimation, they have not been analyzed for the minimum mean squared error (MMSE) denoisers.
Ulugbek Kamilov, Yu Sun, Jiaming Liu
exaly +3 more sources
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Hyperspectral Unmixing Via Plug-And-Play Priors
2020 IEEE International Conference on Image Processing (ICIP), 2020Hyperspectral unmixing aims at separating a mixed pixel into a set of pure spectral signatures and their corresponding fractional abundances. Investigating prior spatial and spectral information to regularize the unmixing problem can effectively improve the estimation performance.
Xiuheng Wang +2 more
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