Image Metrics for Deconvolution of Satellites in Low Earth Orbit

Sierra Hickman, Vishnu Anand Muruganandan, S. Weddell, R. Clare
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引用次数: 2

Abstract

Satellites and space debris clutter low Earth orbital paths, causing concern for future launches as the clutter increases the probability of in-orbit collisions. Therefore, it is important to track and characterise these objects. However, Earth’s atmosphere distorts images collected from ground-based telescopes, which can be reduced through post-processing deconvolution to improve images of satellites and space debris. A metric is needed to quantity the quality of the images and deconvolution of these extended objects at finite distances; as well as to characterise the structure and brightness for un-symmetrical satellites in low Earth orbit. This paper uses images of the International Space Station to investigate the use of the structural similarity metric and the regional properties as potential satellite imaging metrics. Our results show that the similarity metric can characterise the orientation of the satellite relative to the observer, while the regional properties serve to quantity the image quality and improvement due to deconvolution.
近地轨道卫星反卷积图像度量
卫星和太空碎片干扰近地轨道路径,引起对未来发射的担忧,因为这些干扰增加了在轨碰撞的可能性。因此,跟踪和描述这些物体是很重要的。然而,地球大气层会使地面望远镜收集到的图像失真,这可以通过后处理反褶积来改善卫星和太空碎片的图像,从而减少图像失真。需要一个度量来量化图像的质量和这些扩展对象在有限距离上的反卷积;以及表征低地球轨道上不对称卫星的结构和亮度。本文以国际空间站图像为例,研究了结构相似性度量和区域属性作为潜在的卫星成像度量。我们的研究结果表明,相似度度量可以表征卫星相对于观察者的方向,而区域属性用于量化图像质量和由于反卷积而得到的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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