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Image Super-Resolution and Applications / Fathi E. Abd El ~ This book is devoted to the issue of image super-resolution—obtaining high-resolution images from single or multiple low-resolution images. Although there are numerous algorithms available for image interpolation and super-resolution, there’s been a need for a book that establishes a common thread between the two processes.
Image super-resolution and applications / Request PDF ~ This book is devoted to the issue of image super-resolution-obtaining high-resolution images from single or multiple low-resolution images. Although there are numerous algorithms available for .
Image super-resolution and applications (Book, 2013 ~ These steps are image registration and image fusion. 5. This book presents two directions for image super-resolution; super-resolution with a priori information and blind super-resolution. 6. This book presents applications for image interpolation and super-resolution in medical and satellite image processing. 7.
Image Super-Resolution and Applications - MATLAB ~ Image Super-Resolution and Applications presents image interpolation as a building block in the super-resolution reconstruction process.Instead of approaching image interpolation as either a polynomial-based problem or an inverse problem, this book breaks the mold and compares and contrasts the two approaches.
Image super-resolution and applications. - Free Online Library ~ 9781466557963 Image super-resolution and applications. El-Samie, Fathi E. Abd and Mohiy M. Hadhound, Said E. El-Khamy. CRC Press 2013 488 pages
(PDF) Image super-resolution: The techniques, applications ~ Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from the observed LR images. As SR has been developed for more than three decades, both multi-frame and single .
Image super-resolution The techniques, applications, and ~ Review Image super-resolution: The techniques, applications, and future Linwei Yuea, Huanfeng Shenb,c,n, Jie Lia, Qiangqiang Yuanc,d, Hongyan Zhanga,c, Liangpei Zhanga,c,n a The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, PR China b School of Resource and Environmental Science, Wuhan University, Wuhan, PR China
Super Resolution Applications in Modern Digital Image ~ images and videos, Super resolution of images has also grown. In the world of powerful processors and advanced display systems, SR has shown its existence and an overview of various applications based on super resolution has been given in this paper. Keywords FMRI, PET, OCT 1. INTRODUCTION
Image super-resolution: The techniques, applications, and ~ SR is a technique which reconstructs a higher-resolution image or sequence from the observed LR images. Technically, SR can be categorized as multi-frame or single-frame based on the input LR information , , , , .If multiple images of the same scene with sub-pixel misalignment can be acquired, the complementary information between them can be utilized to reconstruct a higher-resolution image .
image processing - Super-Resolution software - Software ~ SuperResolution plugin is a free trial software application from the Video Tools subcategory, part of the Audio & Multimedia category. The app is currently available in English and it was last updated on 2016-08-11. The program can be installed on Windows 7, Windows8, WinVista, WinVista x64, WinXP, Win10 x64, Win8 x64, Windows 8, Windows 10.
Super-resolution imaging: analysis, algorithms, and ~ Low-Cost Super-Resolution Algorithms Implementation Over a HW/SW Video Compression Platform. Two approaches are presented in this paper to improve the quality of digital images over the sensor resolution using super-resolution techniques: iterative super-resolution (ISR) and noniterative super-resolut.
[PDF] New Applications of Super-Resolution in Medical ~ DOI: 10.1201/9781439819319-13 Corpus ID: 18376289. New Applications of Super-Resolution in Medical Imaging @inproceedings{Robinson2017NewAO, title={New Applications of Super-Resolution in Medical Imaging}, author={M. D. Robinson and S. J. Chiu and C. A. Toth and J. Izatt and J. Lo and Sina Farsiu}, year={2017} }
Image Super-resolution via Sparse Representation ~ This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and
Is Image Super-resolution Helpful for Other Vision Tasks? ~ evaluate ISR methods also in real vision applications, and to adopt ISR as a pre-processing step of other vision tasks if the resolution of their input images is low. 1. Introduction Image super-resolution (ISR) aims to sharpen smooth rough edges and enrich missing textures in images that have been enlarged using a general up-scaling process .
Photo-Realistic Single Image Super-Resolution Using a ~ Image Super-Resolution FFHQ 1024 x 1024 - 4x upscaling SRGAN
Super-Resolution Imaging (Digital Imaging and Computer ~ Each detailed chapter provides coverage of the implementations and applications of super-resolution imaging. Its 14 sections span a wide range of modern super-resolution imaging techniques and includes variational, Bayesian, feature-based, multi-channel, learning-based, locally adaptive, and nonparametric methods.
Superresolution using Papoulis-Gerchberg Algorithm ~ Superresolution algorithms being implemented in digital cameras and/or as stand-alone software as they offer a wide variety of quality enhancement for images/video. Superresolution, on the most basic level, deals with construction of a high-resolution image given few low-resolution images with some motion between them. This
Markov Random Fields for Super-Resolution ~ [Download the package] This is an implementation of the example-based super-resolution algorithm of [1]. Although the applications of MSFs have now extended beyond example-based super resolution and texture synthesis, it is still of great value to revisit this problem, especially to share the source code and examplar images with the research community.
Super-resolution - UGR ~ The Matlab application implements the super-resolution methods described in the following papers, developed for the present project: S. Villena, M. Vega, D. Babacan, R. Molina, and A. Katsaggelos. "Bayesian combination of sparse and non sparse priors in image superresolution,"Digital Signal Processing, vol. 23, no. 2, 530-541, 2013.
New Applications of Super-resolution in Medical Imaging ~ the super-resolution framework to Optical Coherence Tomography (OCT). Fi-nally, we conclude in Section 1.4 with some thoughts about future applications of super-resolution in medical imaging. 1.2 The Super-Resolution Framework. The goal of super-resolution image processing is to extract a high-resolution
Image synthesis and superresolution in medical imaging ~ In physics-based image synthesis (in MR imaging), several images are acquired of the same anatomy with different pulse sequences and pulse sequence parameters so that one or more underlying physical parameters—e.g., T 1, T 2, and P D (proton density)—can be computed by inverting the so-called imaging equations, .Given the underlying physical parameters, these same imaging equations can .
Single-Image Super-Resolution: A Benchmark / SpringerLink ~ Single-image super-resolution is of great importance for vision applications, and numerous algorithms have been proposed in recent years. Despite the demonstrated success, these results are often generated based on different assumptions using different datasets and metrics.
Fast, Accurate, and Lightweight Super-Resolution with ~ Abstract. In recent years, deep learning methods have been successfully applied to single-image super-resolution tasks. Despite their great performances, deep learning methods cannot be easily applied to real-world applications due to the requirement of heavy computation.
Simultaneous Super-Resolution and Feature Extraction for ~ Face recognition degrades when faces are of very low resolution since many details about the difference between one person and another can only be captured in images of sufficient resolution. In this work, we propose a new procedure for recognition of low-resolution faces, when there is a high-resolution training set available. Most previous super-resolution approaches […]
Image super-resolution: Historical overview and future ~ N2 - In most digital imaging applications, high resolution images or videos are usually desired for later image processing and analysis. The desire for high resolution stems from two principal application areas: improvement of pictorial information for human interpretation; and helping representation for automatic machine perception.
