Robust and accurate star segmentation algorithm based on morphology

Jie Jiang; Liu Lei; Zhang Guangjun

doi:10.1117/1.OE.55.6.063101

1 June 2016 Robust and accurate star segmentation algorithm based on morphology

Jie Jiang, Liu Lei, Zhang Guangjun

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Optical Engineering, Vol. 55, Issue 6, 063101 (June 2016). https://doi.org/10.1117/1.OE.55.6.063101

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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Jie Jiang, Liu Lei, and Zhang Guangjun "Robust and accurate star segmentation algorithm based on morphology," Optical Engineering 55(6), 063101 (1 June 2016). https://doi.org/10.1117/1.OE.55.6.063101

Published: 1 June 2016

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