Automated coronal hole segmentation from Solar EUV Images using the watershed transform

After the seed is indicated, the segmentation process progresses automatically.A new algorithm for merging regions into the output mask of the coronal hole.The average time of segmentation of a single coronal hole is 342ms.Based on the experiments completed, Dice's index averages 89%.High accuracy of segmentation results for coronal holes of irregular shape. Region of interest segmentation in solar images is the subject of frequent research in solar physics. This study outlines watershed by immersion segmentation to identify coronal hole areas in solar images acquired using the Extreme UV Imaging Telescope (EIT). Solutions presented here produce highly accurate segmentation results of coronal holes of irregular shape, and what is more, they do so for images representing varied solar activity, recorded in different years and months. In addition, the solutions presented here make all the methods used operate very quickly. These methods include: the preprocessing step before the watershed segmentation, the watershed segmentation itself, and also the postprocessing of solar images after the watershed segmentation. The mean duration of the entire segmentation process of solar images amounts to 342ms for a single coronal hole, without the parallel implementation of the methods used. The experiments were carried out on a computer with an Intel Core i7 CPU @ 2GHz and 4GB RAM. After the seed point is identified inside the coronal hole, the segmentation runs automatically.