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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques

Extraction; Feature extraction; Image denoising; Image segmentation; Classification technique; Feature extraction and classification; Feature extraction techniques; Features extraction; Images processing; Machine learning algorithms; Machine learning methods; Research areas; Sensory system; Visual s...

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Main Authors: Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.
Other Authors: 57350531200
Format: Review
Published: John Wiley and Sons Inc 2023
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spelling my.uniten.dspace-269872023-05-29T17:38:25Z Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques Arif Z.H. Mahmoud M.A. Abdulkareem K.H. Mohammed M.A. Al-Mhiqani M.N. Mutlag A.A. Dama�evi?ius R. 57350531200 55247787300 57197854295 57192089894 57197853907 57203180481 6603451290 Extraction; Feature extraction; Image denoising; Image segmentation; Classification technique; Feature extraction and classification; Feature extraction techniques; Features extraction; Images processing; Machine learning algorithms; Machine learning methods; Research areas; Sensory system; Visual sensory; Image classification Images captured through a visual sensory system are degraded in a foggy scene, which negatively influences recognition, tracking, and detection of targets. Efficient tools are needed to detect, pre-process, and enhance foggy scenes. Machine learning (ML) has a significant role in image defogging domain for tackling adverse issues. Unfortunately, regardless of contributions that were made by ML, little attention has been attributed to this topic. This paper summarizes the role of ML methods and relevant aspects in the image defogging research area. Also, the basic terms and concepts are highlighted in image defogging topic. Feature extraction approaches with a summary of advantages and disadvantages are described. ML algorithms are also summarized that have been used for applications related to image defogging, that is, image denoising, image quality assessment, image segmentation, and foggy image classification. Open datasets are also discussed. Finally, the existing problems of the image defogging domain in general and, specifically related to ML which need to be further studied are discussed. To the best knowledge, this the first review paper which sheds a light on the role of ML and relevant aspects in the image defogging domain. � 2021 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology Final 2023-05-29T09:38:25Z 2023-05-29T09:38:25Z 2022 Review 10.1049/ipr2.12365 2-s2.0-85119670133 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119670133&doi=10.1049%2fipr2.12365&partnerID=40&md5=9197f42d86a00006521d4c3e44aa593a https://irepository.uniten.edu.my/handle/123456789/26987 16 2 289 310 John Wiley and Sons Inc Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Extraction; Feature extraction; Image denoising; Image segmentation; Classification technique; Feature extraction and classification; Feature extraction techniques; Features extraction; Images processing; Machine learning algorithms; Machine learning methods; Research areas; Sensory system; Visual sensory; Image classification
author2 57350531200
author_facet 57350531200
Arif Z.H.
Mahmoud M.A.
Abdulkareem K.H.
Mohammed M.A.
Al-Mhiqani M.N.
Mutlag A.A.
Dama�evi?ius R.
format Review
author Arif Z.H.
Mahmoud M.A.
Abdulkareem K.H.
Mohammed M.A.
Al-Mhiqani M.N.
Mutlag A.A.
Dama�evi?ius R.
spellingShingle Arif Z.H.
Mahmoud M.A.
Abdulkareem K.H.
Mohammed M.A.
Al-Mhiqani M.N.
Mutlag A.A.
Dama�evi?ius R.
Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
author_sort Arif Z.H.
title Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
title_short Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
title_full Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
title_fullStr Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
title_full_unstemmed Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques
title_sort comprehensive review of machine learning (ml) in image defogging: taxonomy of concepts, scenes, feature extraction, and classification techniques
publisher John Wiley and Sons Inc
publishDate 2023
_version_ 1806424395968675840
score 13.214268

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