Publication detail

Role of Image Processing in Solar Coronal Research

HABBAL, S. DRUCKMÜLLER, M. MORGAN, H.

Original Title

Role of Image Processing in Solar Coronal Research

Type

journal article in Web of Science

Language

English

Original Abstract

The wealth of information regarding the structure and distribution of magnetic fields and plasmas embedded in images of the solar corona taken in the visible wavelength range and/or the extreme ultraviolet (EUV), covers several orders of magnitude in brightness, in the radial and azimuthal directions. As such, they present serious visualization challenges. These can only be revealed with the use of image processing tools. This presentation will focus on results from two recently developed approaches: (1) The Adaptive Circular High-pass Filter, ACHF, and the Normalized Radial Gradient Filter, NRGF, which are ideal for limb observations of the corona made in the visible wavelength range during total solar eclipses or with coronagraphs. (2) The Noise Adaptive Fuzzy Equalization (NAFE) and the multi-scale Gaussian normalization process (MGN), suitable for the visualization of fine structures in EUV images. These methods yield artifact-free images and uncover details that are hidden in the original unprocessed images. Such details have led to the discovery of new features that are essential for exploring the dynamics and thermodynamics of structures in the solar corona.

Keywords

image processing

Authors

HABBAL, S.; DRUCKMÜLLER, M.; MORGAN, H.

RIV year

2014

Released

1. 5. 2014

Publisher

Springer

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Year of study

2014(8466)

Number

5

State

Federal Republic of Germany

Pages from

17

Pages to

24

Pages count

13

BibTex

@article{BUT107601,
  author="Shadia Rifai {Habbal} and Miloslav {Druckmüller} and Huw {Morgan}",
  title="Role of Image Processing in Solar Coronal Research",
  journal="Lecture Notes in Computer Science",
  year="2014",
  volume="2014(8466)",
  number="5",
  pages="17--24",
  doi="10.1007/978-3-319-07148-0\{_}3",
  issn="0302-9743"
}