A multispectral and multiscale view of the Sun

TL;DR

This paper reviews advanced image processing techniques like Blind Source Separation and multiscale analysis for analyzing ultraviolet solar images, aiding real-time space weather prediction.

Contribution

It highlights the potential of BSS and multiscale analysis for extracting meaningful information from large volumes of solar images in space weather research.

Findings

BSS can condense multispectral solar image data.

Multiscale analysis captures scale-invariant structures.

Applications include feature recognition and image tracking.

Abstract

The emergence of a new discipline called space weather, which aims at understanding and predicting the impact of solar activity on the terrestrial environment and on technological systems, has led to a growing need for analysing solar images in real time. The rapidly growing volume of solar images, however, makes it increasingly impractical to process them for scientific purposes. This situation has prompted the development of novel processing techniques for doing feature recognition, image tracking, knowledge extraction, etc. Here we focus on two particular concepts and list some of their applications. The first one is Blind Source Separation (BSS), which has a great potential for condensing the information that is contained in multispectral images. The second one is multiscale (multiresolution, or wavelet) analysis, which is particularly well suited for capturing scale-invariant structures in solar images. This article provides a brief overview of existing and potential applications to solar images taken in the ultraviolet.