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 m...

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Main Authors: Khattab, Mahmoud, Zeki, Akram M., Alwan, Ali Amer, Badawy, Ahmed S.
Format: Article
Language:English
English
Published: King Saud University 2020
Subjects:
Online Access:http://irep.iium.edu.my/67940/
http://irep.iium.edu.my/67940/19/67940_Regularization-based%20multi-frame%20super-resolution.pdf
http://irep.iium.edu.my/67940/20/67940_Regularization-based%20multi-frame%20super-resolution_Scopus.pdf
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author Khattab, Mahmoud
Zeki, Akram M.
Alwan, Ali Amer
Badawy, Ahmed S.
author_facet Khattab, Mahmoud
Zeki, Akram M.
Alwan, Ali Amer
Badawy, Ahmed S.
author_sort Khattab, Mahmoud
building IIUM Repository
collection Online Access
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.
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spelling iium-679402024-04-09T03:45:08Z 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 S. 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 2020-09 Article PeerReviewed application/pdf en http://irep.iium.edu.my/67940/19/67940_Regularization-based%20multi-frame%20super-resolution.pdf application/pdf en http://irep.iium.edu.my/67940/20/67940_Regularization-based%20multi-frame%20super-resolution_Scopus.pdf Khattab, Mahmoud and Zeki, Akram M. and Alwan, Ali Amer and Badawy, Ahmed S. (2020) Regularization-based multi-frame super-resolution: a systematic review. Journal of King Saud University - Computer and Information Sciences, 32 (7). pp. 755-762. ISSN 1319-1578 E-ISSN 2213-1248 https://www.sciencedirect.com/science/article/pii/S1319157818307407 10.1016/j.jksuci.2018.11.010
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Khattab, Mahmoud
Zeki, Akram M.
Alwan, Ali Amer
Badawy, Ahmed S.
Regularization-based multi-frame super-resolution: a systematic review
title 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_short Regularization-based multi-frame super-resolution: a systematic review
title_sort regularization-based multi-frame super-resolution: a systematic review
topic QA75 Electronic computers. Computer science
QA76 Computer software
url http://irep.iium.edu.my/67940/
http://irep.iium.edu.my/67940/
http://irep.iium.edu.my/67940/
http://irep.iium.edu.my/67940/19/67940_Regularization-based%20multi-frame%20super-resolution.pdf
http://irep.iium.edu.my/67940/20/67940_Regularization-based%20multi-frame%20super-resolution_Scopus.pdf