Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences | |
Xi, Jiangbo2; Xiang, Yaobing5; Ersoy, Okan K.1; Cong, Ming2; Wei, Xin3,4; Gu, Junkai2 | |
刊名 | IEEE ACCESS |
2020 | |
卷号 | 8页码:150864-150877 |
关键词 | Space debris Feature extraction Machine learning Signal to noise ratio Object detection Image sequences Optical imaging Space debris detection background estimation candidate region extraction deep learning |
ISSN号 | 2169-3536 |
DOI | 10.1109/ACCESS.2020.3016761 |
产权排序 | 4 |
英文摘要 | Space debris detection is important in space situation awareness and space asset protection. In this article, we propose a method to detect space debris using feature learning of candidate regions. The acquired optical image sequences are first processed to remove hot pixels and flicker noise, and the nonuniform background information is removed by the proposed one dimensional mean iteration method. Then, the feature learning of candidate regions (FLCR) method is proposed to extract the candidate regions and to detect space debris. The candidate regions of space debris are precisely extracted, and then classified by a trained deep learning network. The feature learning model is trained using a large number of simulated space debris with different signal to noise ratios (SNRs) and motion parameters, instead of using real space debris, which make it difficult to extract a sufficient number of real space debris with diverse parameters in optical image sequences. Finally, the candidate regions are precisely placed in the optical image sequences. The experiment is performed using the simulated data and acquired image sequences. The results show that the proposed method has good performance when estimating and removing background, and it can detect low SNR space debris with high detection probability. |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA |
WOS记录号 | WOS:000567056500001 |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/93699] |
专题 | 西安光学精密机械研究所_空间光学应用研究室 |
通讯作者 | Xi, Jiangbo; Gu, Junkai |
作者单位 | 1.Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA 2.Changan Univ, Sch Geol Engn & Geomat, Xian 710054, Peoples R China 3.Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 10039, Peoples R China 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 5.Nanjing Normal Univ, Sch Geog, Nanjing 210023, Peoples R China |
推荐引用方式 GB/T 7714 | Xi, Jiangbo,Xiang, Yaobing,Ersoy, Okan K.,et al. Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences[J]. IEEE ACCESS,2020,8:150864-150877. |
APA | Xi, Jiangbo,Xiang, Yaobing,Ersoy, Okan K.,Cong, Ming,Wei, Xin,&Gu, Junkai.(2020).Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences.IEEE ACCESS,8,150864-150877. |
MLA | Xi, Jiangbo,et al."Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences".IEEE ACCESS 8(2020):150864-150877. |
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