Shadow detection and removal for remote sensing images via multi-feature adaptive optimization and geometry-aware illumination compensation
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DOI number:
10.1016/j.eswa.2025.127769
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Affiliation of Author(s):
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China
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Journal:
EXPERT SYSTEMS WITH APPLICATIONS
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Funded by:
This work is supported by the National Science and Technology Major Project of China (2024ZD1002006)
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Key Words:
Shadow detection and removal,Multi-feature adaptive optimization,Geometry-aware,Illumination compensation
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Abstract:
Shadows in remote sensing images degrade quality and obscure ground details, posing challenges in their accurate detection and removal. The biggest challenge in shadow removal is accurately detecting the shadow while restoring normal illumination. Therefore, this paper proposes a novel approach combining multi-feature adaptive optimization and geometry-aware illumination compensation for shadow detection and removal. The method introduces a novel multi-feature adaptive optimization algorithm, which simulates dynamic interaction behavior of snakes to obtain optimal shadow thresholds from multi-
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Co-author:
Wu, Hongting,Sheng, Rui,Cao, Liang
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Indexed by:
Journal paper
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Correspondence Author:
Mingqiang,Guo, Zhenfeng,Shao
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Document Type:
Article
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Volume:
282
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ISSN No.:
0957-4174
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Translation or Not:
no
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Date of Publication:
2025-07-05
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