Results 1 to 10 of about 667 (91)
Constrained Plug-and-Play Priors for Image Restoration [PDF]
Journal of ImagingThe Plug-and-Play framework has demonstrated that a denoiser can implicitly serve as the image prior for model-based methods for solving various inverse problems such as image restoration tasks.
Alessandro Benfenati, Pasquale Cascarano
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A Novel Iterative Thresholding Algorithm Based on Plug-and-Play Priors for Compressive Sampling
Future Internet, 2017 We propose a novel fast iterative thresholding algorithm for image compressive sampling (CS) recovery using three existing denoisers—i.e., TV (total variation), wavelet, and BM3D (block-matching and 3D filtering) denoisers.
Lingjun Liu, Zhonghua Xie, Cui Yang
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Attention re-alignment in multimodal large language models via intermediate-layer guidance [PDF]
Scientific ReportsMultimodal large language models (MLLMs) have achieved impressive performance in understanding and describing visual content, setting new state-of-the-art results on a variety of visual question answering (VQA) benchmarks. However, during decoding, these
Yanming Chen +5 more
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Video Super-Resolution Using Plug-and-Play Priors
IEEE AccessVideo super-resolution is a fundamental task in computer vision, aiming to enhance the resolution and visual quality of low-resolution videos. Plug-and-Play Priors is one of the most widely used frameworks for solving computational imaging problems by ...
Matina Ch. Zerva, Lisimachos P. Kondi
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Aerial image quality enhancement via correction of spatially variant aberrations [PDF]
Scientific ReportsAerial cameras are susceptible to optical aberrations under complex operating conditions, resulting in spatially varying image degradation. This degradation essentially stems from the point spread function (PSF) varying continuously across both spatial ...
Changyan Du, Jihong Xiu, Lin Sun
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Deep Equilibrium Learning of Explicit Regularization Functionals for Imaging Inverse Problems
IEEE Open Journal of Signal Processing, 2023 There has been significant recent interest in the use of deep learning for regularizing imaging inverse problems. Most work in the area has focused on regularization imposed implicitly by convolutional neural networks (CNNs) pre-trained for image ...
Zihao Zou +3 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 The increasing volume of hyperspectral images (HSIs) brings great challenges to storage and transmission. Recently, snapshot compressive imaging (SCI), which compresses 3-D HSIs into 2-D measurements, has received increasing attention. Since the original
Huan Li, Xi-Le Zhao, Jie Lin, Yong Chen
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In hyperspectral image (HSI) processing, a fundamental issue is to restore HSI data from various degradations such as noise corruption and information missing.
Tian-Hui Ma +3 more
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IET Intelligent Transport Systems, 2023 Spatiotemporal traffic data usually suffers from missing entries in the data acquisition and transmission process. Existing imputation methods only consider the global/local structure of spatiotemporal traffic data, resulting in insufficient estimation ...
Peng‐Ling Wu +2 more
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Plug-and-Play Prior Based on Gaussian Mixture Model Learning for Image Restoration in Sensor Network
IEEE Access, 2018 In this paper, we propose a method that use the Gaussian mixture model (GMM) as a plug-and-play prior for image restoration in sensor network. The “plug-and-play" concept as an image prior is extended to image restoration and just mentioned in ...
Mingzhu Shi, Liang Feng
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