Automated Detection of EUV Prominences

Abstract

We present methods to detect automatically off-limb prominences in the extreme ultraviolet (EUV), using synoptic images taken by the extreme-ultraviolet imaging telescope (EIT) on board SOHO. The 304 A line is essential for the detection of EUV prominences, but the optimal detection is achieved through a combined image processing of the four synoptic EIT images. In addition, the difference between consecutive 304 A images serves to identify erupted prominences. Representation maps of the quiescent EUV prominences for a given Carrington rotation are generated and used for further analysis of the detected structures. Longitudinal profiles of long-lived prominences are investigated for three examples at different latitudes, in conjunction with on-disk intensity profiles in the EUV. The observations coincide with theoretically predicted apparent longitudinal profiles, which can be distinguished from the profile of a prominence rising before eruption. The developed algorithms may be relevant to study the 3D geometry of features seen in the EUV and may facilitate the analysis of data from the future STEREO mission.