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l(0 )Sparse Approximation of Coastline Inflection Method on FY-3C MWRI Data
Li, Weifu1,2; Luo, Zhicheng1,2; Liu, Chengbo3; Liu, Jiazheng4; Shen, Lijun4; Xie, Qiwei5; Han, Hua4; Yang, Lei3
发表期刊IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN1545-598X
2019
卷号16期号:1页码:85-89
通讯作者Yang, Lei(yangl@cma.gov.cn)
摘要The microwave radiation imager (MWRI) located onboard the FengYun-3C (FY-3C) satellite provides a considerable amount of critical information for numerical weather predictions. Obtaining accurate geolocation results from the FY-3C MWRI data is of great importance. In this letter, we improve the traditional coastline inflection method (CIM) and propose an l(0) sparse approximation model for geolocation error estimation and correction. Specifically, we propose using the jump point of the step function to estimate the true coastline point. This approach can characterize the geolocation errors more accurately than the CIM, which further improves the geolocation accuracy. In the theoretical part, we provide a complete solution to obtain the step function through an iterative blind deconvolution. For a practical use, we demonstrate the effectiveness of the proposed method for geolocation error estimation through quantitative results obtained on the FY-3C MWRI data. The experimental results show that the proposed method can achieve an improvement of up to 33.33% in the standard deviation of geolocation errors (approximately 0.00030) compared to the traditional CIM (approximately 0.00045). Furthermore, we also apply the proposed method to the FY-3C satellite and improve the geolocation accuracy of the MWRI data through geolocation error correction.
关键词Coastline inflection method (CIM) FengYun-3C (FY-3C) geolocation l(0) sparse microwave radiation imager (MWRI)
DOI10.1109/LGRS.2018.2867738
关键词[WOS]ACCURACY
收录类别SCI
语种英语
资助项目National Key Research and Development Problem[2018YFB0504900] ; National Key Research and Development Problem[2018YFB0504905] ; National Science Foundation of China[11771130] ; National Science Foundation of China[41501392] ; National Science Foundation of China[61871177] ; National Science Foundation of China[61673381] ; National Science Foundation of China[61701497] ; National Science Foundation of China[91338109] ; National Science Foundation of China[61172113] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; Bureau of International Cooperation, CAS[153D31KYSB20170059] ; National Key Research and Development Problem[2018YFB0504900] ; National Key Research and Development Problem[2018YFB0504905] ; National Science Foundation of China[11771130] ; National Science Foundation of China[41501392] ; National Science Foundation of China[61871177] ; National Science Foundation of China[61673381] ; National Science Foundation of China[61701497] ; National Science Foundation of China[91338109] ; National Science Foundation of China[61172113] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; Bureau of International Cooperation, CAS[153D31KYSB20170059]
项目资助者National Key Research and Development Problem ; National Science Foundation of China ; Scientific Instrument Developing Project of Chinese Academy of Sciences ; Bureau of International Cooperation, CAS
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000455181800018
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类图像视频处理与分析
引用统计
被引频次:6[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/25320
专题类脑智能研究中心_微观重建与智能分析
通讯作者Yang, Lei
作者单位1.Hubei Univ, Fac Math & Stat, Wuhan 430062, Hubei, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China
4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
5.Beijing Univ Technol, Data Min Lab, Beijing 100124, Peoples R China
第一作者单位中国科学院自动化研究所
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Li, Weifu,Luo, Zhicheng,Liu, Chengbo,et al. l(0 )Sparse Approximation of Coastline Inflection Method on FY-3C MWRI Data[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2019,16(1):85-89.
APA Li, Weifu.,Luo, Zhicheng.,Liu, Chengbo.,Liu, Jiazheng.,Shen, Lijun.,...&Yang, Lei.(2019).l(0 )Sparse Approximation of Coastline Inflection Method on FY-3C MWRI Data.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,16(1),85-89.
MLA Li, Weifu,et al."l(0 )Sparse Approximation of Coastline Inflection Method on FY-3C MWRI Data".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 16.1(2019):85-89.
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