Feature Exploration for Mining Coronal Loops from Solar Images

Coronal loops are especially important in analyzing some important phenomena related to the Sun such as the controversial coronal heating problem. The analysis requires astrophysicists to manually sift through thousands of images in order to acquire images containing coronal loops. Thus, the motivation to detect these loops automatically. Since coronal loops do not have a perfect shape and are easy to confuse with other solar events, feature selection to learn characteristics of loops requires special care. In this study, we explore standard image features as well as specialized image features considering coronal loop characteristics. Our experiments confirm the success of our explored features in coronal loop detection.