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A Method of Water Body Extraction Based on Multiscale Feature and Global Context Information

文献类型：期刊论文

作者Miao, Ru4; Ren, Tongcan3; Zhou, Ke3; Zhang, Yanna2; Song, Jia1; Zhang, Guangyu3; Wang, Jiaqian3
刊名IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
出版日期2024
卷号17页码:12138-12152
关键词Global context information multiscale feature remote sensing image water body extraction Global context information multiscale feature remote sensing image water body extraction
ISSN号1939-1404
DOI10.1109/JSTARS.2024.3416623
产权排序4
英文摘要Water body extraction is an essential mission in the field of semantic segmentation of remote sensing images. It plays a significant role in natural disaster prevention, water resources utilization, hydrological monitoring, and other territories. In practice, the background of the majority of water remote sensing images is complicated. Owing to insufficient semantic mining and rough water body boundary extraction, traditional segmentation methods may be unable to adequately distinguish water bodies. We put forward a multiscale feature and global context fusion network (MSGFNet). In addition, multiscale feature extraction and fusion (MSEF) module based on UperNet and global context enhancement block (GCE Block) are designed. The MSEF module is capable of handling complex scenes by dynamically capturing multiscale semantic information and fusing different layers of features. The GCE Block can help the network to infer the location, shape and contextual information of the water bodies. The GF-1 dataset and Sentinel-2 dataset are used for model training simultaneously. The experimental results indicate that the extraction accuracy of the MSGFNet proposed are superior than other methods on GF-1 dataset and Sentinel-2 dataset, with overall accuracy of 98.60% and 98.22%, respectively. Compared to UperNet, the overall accuracy increases by 1.28% and 0.85%, respectively. In conclusion, the learning method build upon multiscale features and global context information can effectively prohibit noise, heighten the extraction accuracy of water bodies under intricate background, as well as ameliorate the matter of inaccurate water edge segmentation.
资助项目National Science and Technology Major Project of High-Resolution Earth Observation System[80-Y50G19-9001-22/23] ; Science and Technology Project of Henan Province[222102210061]
WOS研究方向Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001270275700015
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Science and Technology Major Project of High-Resolution Earth Observation System ; Science and Technology Project of Henan Province
源URL[http://ir.igsnrr.ac.cn/handle/311030/208886]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Zhou, Ke
作者单位1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Henan Univ, Sch Comp & Informat Engn, Kaifeng 475004, Peoples R China
3.Henan Univ, Henan Engn Res Ctr Spatial Informat Proc, Henan Technol Innovat Ctr Spatio Temporal Big Data, Sch Comp & Informat Engn, Kaifeng 475004, Peoples R China
4.Henan Univ, Henan Engn Res Ctr Spatial Informat Proc, Sch Comp & Informat Engn, Kaifeng 475004, Peoples R China
推荐引用方式
GB/T 7714		 Miao, Ru,Ren, Tongcan,Zhou, Ke,et al. A Method of Water Body Extraction Based on Multiscale Feature and Global Context Information[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2024,17:12138-12152.
APA Miao, Ru.,Ren, Tongcan.,Zhou, Ke.,Zhang, Yanna.,Song, Jia.,...&Wang, Jiaqian.(2024).A Method of Water Body Extraction Based on Multiscale Feature and Global Context Information.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,17,12138-12152.
MLA Miao, Ru,et al."A Method of Water Body Extraction Based on Multiscale Feature and Global Context Information".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17(2024):12138-12152.

入库方式： OAI收割

来源：地理科学与资源研究所

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