Results 11 to 20 of about 389,857 (275)
Learning Curvelet-based Directional Dictionaries for Single Image Super Resolution [PDF]
AUT Journal of Electrical Engineering, 2021 Learning and reconstruction-based methods are the two main approaches to the solve single image super resolution (SISR) problem. In this paper, to exploit the advantages of both learning based and reconstruction based approaches, we propose a new SISR ...
Elhameh Mikaeli +2 more
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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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Cross-View Attention Interaction Fusion Algorithm for Stereo Super-Resolution
Applied Sciences, 2023 In the process of stereo super-resolution reconstruction, in addition to the richness of the extracted feature information directly affecting the texture details of the reconstructed image, the texture details of the corresponding pixels between stereo ...
Yaru Zhang +3 more
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Skip-Concatenated Image Super-Resolution Network for Mobile Devices
IEEE Access, 2023 Single-image super-resolution technology has been widely studied in various applications to improve the quality and resolution of degraded images acquired from noise-sensitive low-resolution sensors.
Ganzorig Gankhuyag +8 more
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, 2021 This study presents a chronological overview of the single image super-resolution problem. We first define the problem thoroughly and mention some of the serious challenges. Then the problem formulation and the performance metrics are defined. We give an overview of the previous methods relying on reconstruction based solutions and then continue with ...
Ataman, Baran, Seker, Mert, Mckee, David
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Single image super resolution via neighbor reconstruction [PDF]
Pattern Recognition Letters, 2019 Super Resolution (SR) is a complex, ill-posed problem where the aim is to construct the mapping between the low and high resolution manifolds of image patches. Anchored neighborhood regression for SR (namely A+ [27]) has shown promising results. In this paper we present a new regression-based SR algorithm that overcomes the limitations of A+ and ...
Zhihong Zhang +7 more
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Single image super resolution via sparse reconstruction [PDF]
SPIE Proceedings, 2012 High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms. Limitation of these methods are that the reconstruction only
Kruithof, M.C. +3 more
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Review and Prospect of Image Super-Resolution Technology
Jisuanji kexue yu tansuo, 2020 Image super-resolution (SR) is an important type of image processing technology for improving image and video resolution in computer vision. In recent years, thanks to the success of neural networks, image super-resolution technology based on deep ...
LIU Ying, ZHU Li, LIM Kengpang, LI Yinghua, WANG Fuping, LU Jin
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Survey of single image super‐resolution reconstruction
IET Image Processing, 2020 Image super‐resolution reconstruction refers to a technique of recovering a high‐resolution (HR) image (or multiple images) from a low‐resolution (LR) degraded image (or multiple images).
Kai Li +4 more
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Single Image Super Resolution via Multi-Attention Fusion Recurrent Network
IEEE Access, 2023 Deep convolutional neural networks have significantly enhanced the performance of single image super-resolution in recent years. However, the majority of the proposed networks are single-channel, making it challenging to fully exploit the advantages of ...
Qiqi Kou +5 more
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