Results 11 to 20 of about 390,825 (274)
Survey of single image super‐resolution reconstruction
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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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 ...
Baran Ataman, Mert Seker, David McKee
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Transformer for Single Image Super-Resolution
Accepted by CVPR workshop ...
Zhisheng Lu +5 more
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Super-resolution from a single image [PDF]
Methods for super-resolution can be broadly classified into two families of methods: (i) The classical multi-image super-resolution (combining images obtained at subpixel misalignments), and (ii) Example-Based super-resolution (learning correspondence between low and high resolution image patches from a database).
Daniel Glasner, Shai Bagon, Michal Irani
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Review and Prospect of Image Super-Resolution Technology
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
doaj +1 more source
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations [PDF]
Single Image Super-Resolution (SISR) aims to generate a high-resolution (HR) image of a given low-resolution (LR) image. The most of existing convolutional neural network (CNN) based SISR methods usually take an assumption that a LR image is only bicubicly down-sampled version of an HR image. However, the true degradation (i.e.
UMER, RAO MUHAMMAD +2 more
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Fast and simple super-resolution with single images
AbstractWe present a fast and simple algorithm for super-resolution with single images. It is based on penalized least squares regression and exploits the tensor structure of two-dimensional convolution. A ridge penalty and a difference penalty are combined; the former removes singularities, while the latter eliminates ringing. We exploit the conjugate
Eilers, Paul H. C., Ruckebusch, Cyril
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Suitability of Single Image Super Resolution Models for Video Super Resolution
This project is an attempt to understand the suitability of the Single image super resolution models to video super resolution. Super Resolution refers to the process of enhancing the quality of low resolution images and video. Single image super resolution algorithms refer to those algorithms that can be applied on a single image to enhance its ...
Shreyas D G +2 more
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Edge-Informed Single Image Super-Resolution [PDF]
The recent increase in the extensive use of digital imaging technologies has brought with it a simultaneous demand for higher-resolution images. We develop a novel edge-informed approach to single image super-resolution (SISR). The SISR problem is reformulated as an image inpainting task.
Kamyar Nazeri +2 more
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Analysis of Single Image Super Resolution Models
Image Super-Resolution (SR) is a set of image processing techniques which improve the resolution of images and videos. Deep learning approaches have made remarkable improvement in image super-resolution in recent years. This article aims and seeks to provide a comprehensive analysis on recent advances of models which has been used in image ...
Köprülü, Mertali +1 more
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