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Spatial-Spectral Fusion of HY-1C COCTS/CZI Data for Coastal Water Remote Sensing Using Deep Belief Network

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成果类型:
期刊论文
作者:
Ji, Hongren;Tian, Liqiao*;Li, Jian;Tong, Ruqing;Guo, Yulong;...
通讯作者:
Tian, Liqiao
作者机构:
[Tian, Liqiao; Ji, Hongren; Tong, Ruqing] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.
[Li, Jian] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China.
[Guo, Yulong] Henan Agr Univ, Coll Resources & Environm Sci, Zhengzhou 450002, Peoples R China.
[Guo, Yulong] Henan Agr Univ, Henan Engn Res Ctr Land Consolidat & Ecol Restora, Zhengzhou 450002, Peoples R China.
[Zeng, Qun] Cent China Normal Univ, Editorial Dept Journal, Wuhan 430079, Peoples R China.
通讯机构:
[Tian, Liqiao] W
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Coastal water;deep belief network (DBN);fusion;HaiYang-1C (HY-1C);remote sensing
期刊:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
ISSN:
1939-1404
年:
2021
卷:
14
页码:
1693-1704
基金类别:
Manuscript received August 7, 2020; revised October 5, 2020 and November 12, 2020; accepted December 7, 2020. Date of publication December 17, 2020; date of current version January 13, 2021. This work was supported in part by the National Key R&D Program of China under Grant 2018YFB0504900, Grant 2018YFB0504904, and Grant 2016YFC0200900, in part by the National Natural Science Foundation of China under Grant 42071325, Grant 41571344, Grant 41701379, and Grant 41701422, and in part by LIESMARS Special Research Funding. (Corresponding author: Liqiao Tian.) Hongren Ji, Liqiao Tian, and Ruqing Tong are with the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China (e-mail: jihongren@whu.edu.cn; tianliqiao@whu.edu.cn; tongruqing@whu.edu.cn).
机构署名:
本校为其他机构
院系归属:
城市与环境科学学院
新闻传播学院
摘要:
The remote sensing monitoring of coastal waters with dramatic changes requires images with high spatial and temporal resolutions and adequate spectral bands. However, a single sensor is limited to meet these requirements. Image fusion is, therefore, widely adopted. In this article, a deep belief network (DBN) is developed to fuse images from the Chinese ocean color and temperature scanner (1000 m, eight bands) and coastal zone imager (50 m, four bands) onboard HaiYang-1C satellite to generate 50-m, eight-band, and three-day observations for coa...

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