Results 31 to 40 of about 18,250,374 (304)
Super Resolution for Noisy Images Using Convolutional Neural Networks
Mathematics, 2022 The images in high resolution contain more useful information than the images in low resolution. Thus, high-resolution digital images are preferred over low-resolution images.
Zaid Bin Mushtaq +5 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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Super-resolution of remotely sensed images with variable-pixel linear reconstruction [PDF]
, 2007 This paper describes the development and applications of a super-resolution method, known as Super-Resolution Variable-Pixel Linear Reconstruction. The algorithm works combining different lower resolution images in order to obtain, as a result, a higher ...
Núñez de Murga, Jorge, 1955- +1 more
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Remote Sensing, 2021 Super-resolution (SR) technology has emerged as an effective tool for image analysis and interpretation. However, single hyperspectral (HS) image SR remains challenging, due to the high spectral dimensionality and lack of available high-resolution ...
Xiaochen Lu +3 more
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Applied Sciences, 2020 The super-resolution generative adversarial network (SRGAN) is a seminal work that is capable of generating realistic textures during single image super-resolution. However, the hallucinated details are often accompanied by unpleasant artifacts.
Zetao Jiang, Yongsong Huang, Lirui Hu
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Image Super-Resolution with Adversarial Learning [PDF]
, 2022 Single-image super-resolution refers to the problem of generating a high-resolution image from a low-resolution one. In this work we address to the problem of single-image super-resolution of degraded low-resolution images.
Boem, Davide
core
Terrain Self-Similarity-Based Transformer for Generating Super Resolution DEMs
Remote Sensing, 2023 High-resolution digital elevation models (DEMs) are important for relevant geoscience research and practical applications. Compared with traditional hardware-based methods, super-resolution (SR) reconstruction techniques are currently low-cost and ...
Xin Zheng, Zelun Bao, Qian Yin
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Deep Learning-Based Single-Image Super-Resolution: A Comprehensive Review
IEEE Access, 2023 High-fidelity information, such as 4K quality videos and photographs, is increasing as high-speed internet access becomes more widespread and less expensive.
Karansingh Chauhan +7 more
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Super-resolution fluorescence imaging with single molecules [PDF]
Current Opinion in Structural Biology, 2013 The ability to detect, image and localize single molecules optically with high spatial precision by their fluorescence enables an emergent class of super-resolution microscopy methods which have overcome the longstanding diffraction barrier for far-field light-focusing optics.
Steffen J, Sahl, W E, Moerner
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Generative collaborative networks for single image super-resolution [PDF]
Neurocomputing, 2020 A common issue of deep neural networks-based methods for the problem of Single Image Super-Resolution (SISR), is the recovery of finer texture details when super-resolving at large upscaling factors. This issue is particularly related to the choice of the objective loss function. In particular, recent works proposed the use of a VGG loss which consists
Mohamed El Amine Seddik +2 more
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