@inproceedings{5e937bf25c354106ad7ee676c95ff130,
title = "Research on image processing and intelligent recognition of space debris",
abstract = "The space debris may cause catastrophic damage to spacecraft. The detection, monitoring and identification of space debris can improve space situational awareness, and implement debris avoidance and debris removal tasks. Therefore, this topic has become the basis and premise to ensure the safety of spacecraft operation. In order to meet the requirements of space debris detection and removal, this paper proposed the space debris image processing algorithms including fixed-mode noise estimation and removal, random noise suppression, image enhancement and so on. By using which, the ability of image SNR improved more than 10\%, while the image detail resolution improved 10\%. On the basis of image processing, the deep neural network mode has been established and combined with the artificial marker semi-supervised training method. The research of space debris feature extraction and automatic detection has been preliminarily carried out.",
keywords = "Space debris, artifical intelligence, image processing, spacecraft",
author = "Linghua Guo and Haopeng Zhang and Hua Zhai and Cheng Gong and Bin Song and Shoufeng Tong and Zhicheng Cao and Xuan Xu",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Automatic Target Recognition XXIX 2019 ; Conference date: 15-04-2019 Through 18-04-2019",
year = "2019",
doi = "10.1117/12.2525058",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Hammoud, \{Riad I.\} and Overman, \{Timothy L.\}",
booktitle = "Automatic Target Recognition XXIX",
address = "美国",
}