Automatic CME front edge detection from STEREO white‐light coronagraph images

Abstract

AbstractThe coronagraph images captured by a Solar Terrestrial Relations Observatory (STEREO) Ahead/Behind (A/B) spacecraft allow tracking of a coronal mass ejection (CME) from two different viewpoints and reconstructing its propagation in three‐dimensional space. The reconstruction can be done using a triangulation technique that requires a CME front edge location. There are currently no robust automatic CME front edge detection methods that can be integrated with the triangulation technique. In this paper, we propose a novel automatic method to detect the front edge of the CME using STEREO coronagraph 2 red‐colored Red, Green, Blue color model images. Our method consists of two modules: preprocessing and classification. The preprocessing module decomposes each coronagraph image into its three channels and uses only the red channel image for CME segmentation. The output of the preprocessing module is a set of segmented running‐difference binary images which is fed into the classification module. These images are then transformed into polar coordinates followed by CME front edge detection based on the distance that CME travels in the field of view. The proposed method was validated against a manual method using total 56 CME events, 28 from STEREO A and 28 from STEREO B, captured in the period from 1 January 2008 to 16 August 2009. The results show that the proposed method is effective for CME front edge detection. The proposed method is useful in quantitative CME processing and analysis and will be immediately applicable to assist automatic triangulation method for real‐time space weather forecasting.