l(p)-ICP Coastline Inflection Method for Geolocation Error Estimation in FY-3 MWRI Data
文献类型：期刊论文
| 作者 | Zhao, Xinghui1,2; Chen, Na1 ; Li, Weifu1,2; Peng, Jiangtao1; Shen, Lijun2
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| 刊名 | REMOTE SENSING
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| 出版日期 | 2019-08-01 |
| 卷号 | 11期号:16页码:20 |
| 关键词 | MWRI FengYun-3 geolocation error coastline inflection method l(P) sparse regularization optimization iterative closest point |
| DOI | 10.3390/rs11161886 |
| 通讯作者 | Shen, Lijun(lijun.shen@ia.ac.cn) |
| 英文摘要 | Known as input in the Numerical Weather Prediction (NWP) models, Microwave Radiation Imager (MWRI) data have been widely distributed to the user community. With the development of remote sensing technology, improving the geolocation accuracy of MWRI data are required and the first step is to estimate the geolocation error accurately. However, the traditional method, such as the coastline inflection method (CIM), usually has the disadvantages of low accuracy and poor anti-noise ability. To overcome these limitations, this paper proposes a novel lp iterative closest point coastline inflection method (lp-ICP CIM). It assumes that the field of views (FOVs) across the coastline can degenerate into a step function and employs an lp(0 <= p<1) sparse regularization optimization model to solve the coastline point. After estimating the coastline points, the ICP algorithm is employed to estimate the corresponding relationship between the estimated coastline points and the real coastline. Finally, the geolocation error can be defined as the distance between the estimated coastline point and the corresponding point on the true coastline. Experimental results on simulated and real data sets show the effectiveness of our method over CIM. The accuracy of the geolocation error estimated by lp-ICP CIM is up to 0.1 pixel, in more than 90% of cases. We also show that the distribution of brightness temperature near the coastline is more consistent with the real coastline and the average geolocation error is reduced by 63% after geolocation error correction. |
| WOS关键词 | GO-ICP ; REGISTRATION ; ACCURACY ; ALGORITHM |
| 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[61871177] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] ; Bureau of International Cooperation, CAS[153D31KYSB20170059] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000484387600049 |
| 出版者 | MDPI |
| 资助机构 | 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 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27298]  |
| 专题 | 类脑智能研究中心_微观重建与智能分析 |
| 通讯作者 | Shen, Lijun |
| 作者单位 | 1.Hubei Univ, Fac Math & Stat, Hubei Key Lab Appl Math, Wuhan 430062, Hubei, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Xinghui,Chen, Na,Li, Weifu,et al. l(p)-ICP Coastline Inflection Method for Geolocation Error Estimation in FY-3 MWRI Data[J]. REMOTE SENSING,2019,11(16):20. |
| APA | Zhao, Xinghui,Chen, Na,Li, Weifu,Peng, Jiangtao,&Shen, Lijun.(2019).l(p)-ICP Coastline Inflection Method for Geolocation Error Estimation in FY-3 MWRI Data.REMOTE SENSING,11(16),20. |
| MLA | Zhao, Xinghui,et al."l(p)-ICP Coastline Inflection Method for Geolocation Error Estimation in FY-3 MWRI Data".REMOTE SENSING 11.16(2019):20. |
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