Results 51 to 60 of about 750,933 (209)
Anchored neighborhood deep network for single-image super-resolution
EURASIP Journal on Image and Video Processing, 2018 Real-time image and video processing is a challenging problem in smart surveillance applications. It is necessary to trade off between high frame rate and high resolution to meet the limited bandwidth requirement in many specific applications.
Wuzhen Shi +4 more
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Reference Based Face Super-Resolution
IEEE Access, 2019 Despite the great progress of image super-resolution in recent years, face super-resolution has still much room to explore good visual quality while preserving original facial attributes for larger up-scaling factors.
Zhi-Song Liu, Wan-Chi Siu, Yui-Lam Chan
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Sensors, 2023 Remote sensing images often have limited resolution, which can hinder their effectiveness in various applications. Super-resolution techniques can enhance the resolution of remote sensing images, and arbitrary resolution super-resolution techniques ...
Jinming Luo +4 more
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Image Super-Resolution Reconstruction Method Based on Embeddable Network Structure [PDF]
Jisuanji gongcheng, 2021 The existing Super-Resolution(SR) image reconstruction models based on Convolutional Neural Networks(CNN) have multiple deficiencies,such as instable model training process and low convergence speed.To address the problem,this paper proposes an ...
QIANG Baohua, PANG Yuanchao, YANG Minghao, ZENG Kun, ZHENG Hong, XIE Wu, MO Ye
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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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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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Lightweight Image Super-Resolution with Information Multi-distillation Network [PDF]
ACM Multimedia, 2019 In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results. Thanks to the powerful representation capabilities of the deep networks, numerous previous ways can learn the ...
Zheng Hui +3 more
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SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models [PDF]
Neurocomputing, 2021 Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from the given low-resolution (LR) ones, which is an ill-posed problem because one LR image corresponds to multiple HR images. Recently, learning-based SISR methods have
Haoying Li +6 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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