Regularization-based multi-frame super-resolution: A systematic review

High-resolution is generally required and preferred for producing more detailed information inside the digital images; therefore, this leads to improve the pictorial information for human analysis and interpretation and to enhance the automatic machine perception. However, the real imaging systems...

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Main Authors:	Khattab, Mahmoud, Zeki, Akram M., Alwan, Ali Amer, Badawy, Ahmed
Format:	Article
Language:	English English
Published:	King Saud University 2018
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/7/67940%20Regularization-based%20multi-frame%20super-resolution-in-press.pdf http://irep.iium.edu.my/67940/8/67940%20Regularization-based%20multi-frame%20super-resolution%20SCOPUS-in-press.pdf

id	iium-67940
recordtype	eprints
spelling	iium-679402018-12-05T01:57:17Z http://irep.iium.edu.my/67940/ Regularization-based multi-frame super-resolution: A systematic review Khattab, Mahmoud Zeki, Akram M. Alwan, Ali Amer Badawy, Ahmed QA75 Electronic computers. Computer science QA76 Computer software High-resolution is generally required and preferred for producing more detailed information inside the digital images; therefore, this leads to improve the pictorial information for human analysis and interpretation and to enhance the automatic machine perception. However, the real imaging systems may introduce some degradation or artifacts in the digital images. These distortions in the images are caused by a variety of factors such as blurring, aliasing, and noise, which may affect the resolution of imaging systems and produce low-resolution images. Numerous strategies like frequency and spatial domain approaches have been proposed in the literature. Spatial domain approaches are classified as one of the most popular approaches and split into interpolation-based approaches and regularization-based approaches. Nevertheless, these techniques still suffer from artifacts. Regularization-based approaches are a challenging in image super-resolution in the last decade. This paper attempts to investigate the current regularization-based super-resolution approaches which are commonly used for reconstructing the high-resolution image in the last decade. Furthermore, the focus is given on highlighting the strengths and limitations of these approaches aiming at determining their effectiveness and quality in reconstructing high-resolution images. King Saud University 2018-11-16 Article PeerReviewed application/pdf en http://irep.iium.edu.my/67940/7/67940%20Regularization-based%20multi-frame%20super-resolution-in-press.pdf application/pdf en http://irep.iium.edu.my/67940/8/67940%20Regularization-based%20multi-frame%20super-resolution%20SCOPUS-in-press.pdf Khattab, Mahmoud and Zeki, Akram M. and Alwan, Ali Amer and Badawy, Ahmed (2018) Regularization-based multi-frame super-resolution: A systematic review. Journal of King Saud University - Computer and Information Sciences. ISSN 1319-1578 (In Press) https://www.sciencedirect.com/science/article/pii/S1319157818307407 10.1016/j.jksuci.2018.11.010
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software Khattab, Mahmoud Zeki, Akram M. Alwan, Ali Amer Badawy, Ahmed Regularization-based multi-frame super-resolution: A systematic review
description	High-resolution is generally required and preferred for producing more detailed information inside the digital images; therefore, this leads to improve the pictorial information for human analysis and interpretation and to enhance the automatic machine perception. However, the real imaging systems may introduce some degradation or artifacts in the digital images. These distortions in the images are caused by a variety of factors such as blurring, aliasing, and noise, which may affect the resolution of imaging systems and produce low-resolution images. Numerous strategies like frequency and spatial domain approaches have been proposed in the literature. Spatial domain approaches are classified as one of the most popular approaches and split into interpolation-based approaches and regularization-based approaches. Nevertheless, these techniques still suffer from artifacts. Regularization-based approaches are a challenging in image super-resolution in the last decade. This paper attempts to investigate the current regularization-based super-resolution approaches which are commonly used for reconstructing the high-resolution image in the last decade. Furthermore, the focus is given on highlighting the strengths and limitations of these approaches aiming at determining their effectiveness and quality in reconstructing high-resolution images.
format	Article
author	Khattab, Mahmoud Zeki, Akram M. Alwan, Ali Amer Badawy, Ahmed
author_facet	Khattab, Mahmoud Zeki, Akram M. Alwan, Ali Amer Badawy, Ahmed
author_sort	Khattab, Mahmoud
title	Regularization-based multi-frame super-resolution: A systematic review
title_short	Regularization-based multi-frame super-resolution: A systematic review
title_full	Regularization-based multi-frame super-resolution: A systematic review
title_fullStr	Regularization-based multi-frame super-resolution: A systematic review
title_full_unstemmed	Regularization-based multi-frame super-resolution: A systematic review
title_sort	regularization-based multi-frame super-resolution: a systematic review
publisher	King Saud University
publishDate	2018
url	http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/ http://irep.iium.edu.my/67940/7/67940%20Regularization-based%20multi-frame%20super-resolution-in-press.pdf http://irep.iium.edu.my/67940/8/67940%20Regularization-based%20multi-frame%20super-resolution%20SCOPUS-in-press.pdf
first_indexed	2023-09-18T21:36:27Z
last_indexed	2023-09-18T21:36:27Z
_version_	1777412852582187008

Regularization-based multi-frame super-resolution: A systematic review

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