Filament and Flare Detection in H{\alpha} image sequences

TL;DR

This paper introduces a new method for detecting solar flares and filaments in H-alpha image sequences, aiding real-time alerts and data analysis for solar storms.

Contribution

The paper presents a novel segmentation and classification approach for solar events in H-alpha images, improving detection accuracy and processing efficiency.

Findings

Effective detection of flares and filaments demonstrated

Comparable results to expert annotations achieved

Potential for real-time solar storm alerts

Abstract

Solar storms can have a major impact on the infrastructure of the earth. Some of the causing events are observable from ground in the H{\alpha} spectral line. In this paper we propose a new method for the simultaneous detection of flares and filaments in H{\alpha} image sequences. Therefore we perform several preprocessing steps to enhance and normalize the images. Based on the intensity values we segment the image by a variational approach. In a final postprecessing step we derive essential properties to classify the events and further demonstrate the performance by comparing our obtained results to the data annotated by an expert. The information produced by our method can be used for near real-time alerts and the statistical analysis of existing data by solar physicists.