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Proceedings Paper

Maximum projection and velocity estimation algorithm for small moving target detection in space surveillance
Author(s): Dalei Yao; Desheng Wen; Jianru Xue; Zhi Chen; Yan Wen; Baotan Jiang; Junyong Ma
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Paper Abstract

The article presents a new method to detect small moving targets in space surveillance. Image sequences are processed to detect and track targets under the assumption that the data samples are spatially registered. Maximum value projection and normalization are performed to reduce the data samples and eliminate the background clutter. Targets are then detected through connected component analysis. The velocities of the targets are estimated by centroid localization and least squares regression. The estimated velocities are utilized to track the targets. A sliding neighborhood operation is performed prior to target detection to significantly reduce the computation while preserving as much target information as possible. Actual data samples are acquired to test the proposed method. Experimental results show that the method can efficiently detect small moving targets and track their traces accurately. The centroid locating precision and tracking accuracy of the method are within a pixel.

Paper Details

Date Published: 8 October 2015
PDF: 10 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96752H (8 October 2015); doi: 10.1117/12.2202360
Show Author Affiliations
Dalei Yao, Xi'an Jiaotong Univ. (China)
Xi'an Institute of Optics and Precision Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Desheng Wen, Xi'an Institute of Optics and Precision Mechanics (China)
Jianru Xue, Xi’an Jiaotong Univ. (China)
Zhi Chen, Xi'an Institute of Optics and Precision Mechanics (China)
Yan Wen, Xi'an Institute of Optics and Precision Mechanics (China)
Baotan Jiang, Xi'an Institute of Optics and Precision Mechanics (China)
Junyong Ma, Xi'an Institute of Optics and Precision Mechanics (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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