Satellites and space debris clutter low Earth orbital paths. This causes concerns for future launches as the clutter increases the probability of in-orbit collisions. Therefore, it is important to track and characterise these objects. However, the Earth’s atmosphere distorts images collected from ground-based telescopes. The blurring effects of the atmosphere can be reduced through post-processing deconvolution to improve the images of satellites and space debris. Yet, a metric is needed to quantify 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 collected 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 is useful to characterise the orientation of the satellite relative to the observer, while the regional properties serve to quantify the image quality and improvement due to deconvolution.