Multiscale Edge Detection in the Corona

TL;DR

This paper introduces a multiscale edge detection technique to objectively identify and analyze the morphology and kinematics of Coronal Mass Ejections (CMEs), reducing observer bias and providing error estimates.

Contribution

The paper presents a novel multiscale edge detection method for automated CME front detection, improving objectivity and accuracy over manual methods.

Findings

CME front heights are approximately 10% smaller with the new method using LASCO data.

CME front heights are approximately 20% smaller with TRACE data.

The method provides associated error estimates for CME front positions.

Abstract

Coronal Mass Ejections (CMEs) are challenging objects to detect using automated techniques, due to their high velocity and diffuse, irregular morphology. A necessary step to automating the detection process is to first remove the subjectivity introduced by the observer used in the current, standard, CME detection and tracking method. Here we describe and demonstrate a multiscale edge detection technique that addresses this step and could serve as one part of an automated CME detection system. This method provides a way to objectively define a CME front with associated error estimates. These fronts can then be used to extract CME morphology and kinematics. We apply this technique to a CME observed on 18 April 2000 by the Large Angle Solar COronagraph experiment (LASCO) C2/C3 and a CME observed on 21 April 2002 by LASCO C2/C3 and the Transition Region and Coronal Explorer (TRACE). For the two examples in this work, the heights determined by the standard manual method are larger than those determined with the multiscale method by approximately 10% using LASCO data and approximately 20% using TRACE data.