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Taking a large amount of images, the Cassini Imaging Science Subsystem (ISS)has been routinely used in astrometry. In ISS images, disk-resolved objectsoften lead to false detection of stars that disturb the camera pointingcorrection. The aim of this study was to develop an automated processing methodto remove the false image stars in disk-resolved objects in ISS images. Themethod included the following steps: extracting edges, segmenting boundaryarcs, fitting circles and excluding false image stars. The proposed method wastested using 200 ISS images. Preliminary experimental results show that it canremove the false image stars in more than 95% of ISS images with disk-resolvedobjects in a fully automatic manner, i.e. outperforming the traditional circledetection based on Circular Hough Transform (CHT) by 17%. In addition, itsspeed is more than twice as fast as that of the CHT method. It is also morerobust (no manual parameter tuning is needed) when compared with CHT. Theproposed method was also applied to a set of ISS images of Rhea to eliminatethe mismatch in pointing correction in automatic procedure. Experiment resultsshowed that the precision of final astrometry results can be improve by roughly2 times than that of automatic procedure without the method. It proved that theproposed method is helpful in the astrometry of ISS images in fully automaticmanner.

Automatic removal of false image stars in disk-resolved images of the Cassini Imaging Science Subsystem