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From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)

The removal of shadows from images is a classic problem in computer vision, aiming to restore the lighting in shadowed areas, thereby reducing the information interference and loss caused by the presence of shadows. In recent years, numerous excellent shadow removal algorithms have emerged, particul...

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Main Authors: Zhu, Xiujin, Chow, Chee-Onn, Chuah, Joon Huang
Format: Article
Published: Elsevier 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.um.edu.my/46899/
https://doi.org/10.1016/j.imavis.2024.105100
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spelling my.um.eprints.468992025-01-15T08:31:44Z http://eprints.um.edu.my/46899/ From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023) Zhu, Xiujin Chow, Chee-Onn Chuah, Joon Huang TK Electrical engineering. Electronics Nuclear engineering The removal of shadows from images is a classic problem in computer vision, aiming to restore the lighting in shadowed areas, thereby reducing the information interference and loss caused by the presence of shadows. In recent years, numerous excellent shadow removal algorithms have emerged, particularly with the rapid development of deep learning technology, which has disrupted traditional physics-based approaches and significantly improved the effectiveness of shadow removal. In this paper, we conduct a comprehensive survey of shadow removal methods published from 2017 to the present. We first introduce background knowledge about image shadow removal, providing detailed explanations of both physics-based and learning-based shadow removal methods. We analyze and compare these algorithms from both quantitative and qualitative perspectives, reassessing all models that provided open-source result sets according to uniform criteria. Additionally, we introduce commonly used datasets and evaluation metrics in the field. Finally, we discuss applications of shadow removal in specific scenarios, along with research challenges and opportunities in this domain. Elsevier 2024-08 Article PeerReviewed Zhu, Xiujin and Chow, Chee-Onn and Chuah, Joon Huang (2024) From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023). Image and Vision Computing, 148. p. 105100. ISSN 0262-8856, DOI https://doi.org/10.1016/j.imavis.2024.105100 <https://doi.org/10.1016/j.imavis.2024.105100>. https://doi.org/10.1016/j.imavis.2024.105100 10.1016/j.imavis.2024.105100
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zhu, Xiujin
Chow, Chee-Onn
Chuah, Joon Huang
From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
description The removal of shadows from images is a classic problem in computer vision, aiming to restore the lighting in shadowed areas, thereby reducing the information interference and loss caused by the presence of shadows. In recent years, numerous excellent shadow removal algorithms have emerged, particularly with the rapid development of deep learning technology, which has disrupted traditional physics-based approaches and significantly improved the effectiveness of shadow removal. In this paper, we conduct a comprehensive survey of shadow removal methods published from 2017 to the present. We first introduce background knowledge about image shadow removal, providing detailed explanations of both physics-based and learning-based shadow removal methods. We analyze and compare these algorithms from both quantitative and qualitative perspectives, reassessing all models that provided open-source result sets according to uniform criteria. Additionally, we introduce commonly used datasets and evaluation metrics in the field. Finally, we discuss applications of shadow removal in specific scenarios, along with research challenges and opportunities in this domain.
format Article
author Zhu, Xiujin
Chow, Chee-Onn
Chuah, Joon Huang
author_facet Zhu, Xiujin
Chow, Chee-Onn
Chuah, Joon Huang
author_sort Zhu, Xiujin
title From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
title_short From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
title_full From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
title_fullStr From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
title_full_unstemmed From darkness to clarity: A comprehensive review of contemporary image shadow removal research (2017-2023)
title_sort from darkness to clarity: a comprehensive review of contemporary image shadow removal research (2017-2023)
publisher Elsevier
publishDate 2024
url http://eprints.um.edu.my/46899/
https://doi.org/10.1016/j.imavis.2024.105100
_version_ 1825160606300241920
score 13.244413

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