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Optical Engineering • Open Access • new

Robust and accurate star segmentation algorithm based on morphology
Author(s): Jie Jiang; Liu Lei; Zhang Guangjun

Paper Abstract

Star tracker is an important instrument of measuring a spacecraft’s attitude; it measures a spacecraft’s attitude by matching the stars captured by a camera and those stored in a star database, the directions of which are known. Attitude accuracy of star tracker is mainly determined by star centroiding accuracy, which is guaranteed by complete star segmentation. Current algorithms of star segmentation cannot suppress different interferences in star images and cannot segment stars completely because of these interferences. To solve this problem, a new star target segmentation algorithm is proposed on the basis of mathematical morphology. The proposed algorithm utilizes the margin structuring element to detect small targets and the opening operation to suppress noises, and a modified top-hat transform is defined to extract stars. A combination of three different structuring elements is utilized to define a new star segmentation algorithm, and the influence of three different structural elements on the star segmentation results is analyzed. Experimental results show that the proposed algorithm can suppress different interferences and segment stars completely, thus providing high star centroiding accuracy.

Paper Details

Date Published: 1 June 2016
PDF: 10 pages
Opt. Eng. 55(6) 063101 doi: 10.1117/1.OE.55.6.063101
Published in: Optical Engineering Volume 55, Issue 6
Show Author Affiliations
Jie Jiang, BeiHang Univ. (China)
Liu Lei, BeiHang Univ. (China)
Zhang Guangjun, BeiHang Univ. (China)


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