Results 31 to 40 of about 441,901 (274)
Super-Resolution Imaging [PDF]
Journal of Electronic Imaging, 2013 This book serves as an introduction to the flourishing field of super-resolution imaging. It is a compiled volume, with different authors for each of its 14 chapters. While not having a strong outline or textbook format, the chapters group into several sections.
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Image Super-Resolution Using Generative Adversarial Networks with Learned Degradation Operators [PDF]
MATEC Web of Conferences, 2022 Image super-resolution is a research endeavour that has gained notoriety in computer vision. The research goal is to increase the spatial dimensions of an image using corresponding low-resolution and high-resolution image pairs to enhance the perceptual ...
Molefe Molefe, Klein Richard
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Pairwise Operator Learning for Patch Based Single-image Super-resolution [PDF]
, 2016 Motivated by the fact that image patches could be inherently represented by matrices, single-image super-resolution is treated as a problem of learning regression operators in a matrix space in this paper. The regression operators that map low-resolution
Shao, Ling, Tang, Yi
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SUPER-RESOLUTION OF MULTISPECTRAL IMAGES [PDF]
Modelling and Simulation in Science, 2007 In this paper we propose and analyze a globally and locally adaptive super-resolution Bayesian methodology for pansharpening of multispectral images. The methodology incorporates prior knowledge on the expected characteristics of the multispectral images uses the sensor characteristics to model the observation process of both panchromatic and ...
M. Vega +3 more
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Image Super-Resolution Via Iterative Refinement
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 We present SR3, an approach to image Super-Resolution via Repeated Refinement. SR3 adapts denoising diffusion probabilistic models to conditional image generation and performs super-resolution through a stochastic denoising process. Inference starts with pure Gaussian noise and iteratively refines the noisy output using a U-Net model trained on ...
Chitwan Saharia +5 more
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Microsphere super-resolution imaging [PDF]
, 2016 Recently, it was discovered that microsphere can generate super-resolution focusing beyond diffraction limit. This has led to the development of an exciting super-resolution imaging technique -microsphere nanoscopy- that features a record resolution of 50 nm under white lights.
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Super-resolution microscopy based on interpolation and wide spectrum de-noising
Компьютерная оптика, 2023 In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function.
T. Cheng, T. Chenchen
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Image Super-resolution Reconstruction Based on Sparse Representation and Guided Filtering [PDF]
Jisuanji gongcheng, 2018 In view of the fact that the image super-resolution reconstruction method cannot effectively reconstruct more high frequency image information in the process of image processing and storage,this paper proposes an image super-resolution reconstruction ...
ZHANG Wanxu,SHI Jianxiong,CHEN Xiaoxuan,WANG Lin,ZHAO Ming,ZHOU Yan,NIU Jinping
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Joint Image Reconstruction and Super-Resolution for Accelerated Magnetic Resonance Imaging
Bioengineering, 2023 Magnetic resonance (MR) image reconstruction and super-resolution are two prominent techniques to restore high-quality images from undersampled or low-resolution k-space data to accelerate MR imaging. Combining undersampled and low-resolution acquisition
Wei Xu +6 more
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Volatile-Nonvolatile Memory Network for Progressive Image Super-Resolution
IEEE Access, 2021 Single-image super-resolution, i.e., reconstructing a high-resolution image from a low-resolution image, is a critical concern in many computer vision applications. Recent deep learning-based image super-resolution methods employ massive numbers of model
Jun-Ho Choi +3 more
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