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Multi-Scale Gaussian Normalization for Solar Image Processing.

Huw Morgan1, Miloslav Druckmüller2

  • 1Sefydliad Mathemateg a Ffiseg, Prifysgol Aberystwyth, Ceredigion, SY23 3BZ Wales.

Solar Physics
|July 23, 2016
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Summary
This summary is machine-generated.

This study introduces an efficient image processing method for solar corona data. The technique uses localized normalization across multiple scales to reveal fine details while preserving context and reducing noise.

Keywords:
CoronaImage processing

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Area of Science:

  • Solar physics
  • Plasma physics
  • Astrophysics

Background:

  • Extreme ultraviolet (EUV) images of the solar corona contain information across diverse spatial scales and brightness regimes.
  • Processing solar imagery is crucial for uncovering hidden details without introducing artifacts or bias.

Purpose of the Study:

  • To develop a computationally efficient image processing method for solar corona data.
  • To reveal fine-scale structures in solar images while maintaining larger-scale context.
  • To address the challenges posed by the high resolution of instruments like the Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO).

Main Methods:

  • A novel image processing technique based on localized normalization across multiple spatial scales.
  • Application of the method to extreme ultraviolet (EUV) solar corona images.
  • Testing the method on white-light coronagraph observations.

Main Results:

  • The method effectively reveals information at the finest spatial scales.
  • Larger-scale information is maintained, providing essential context.
  • Noisy regions are intrinsically flattened, and structure in off-limb regions is enhanced.
  • Successful application to both EUV and white-light coronagraph data.

Conclusions:

  • The described localized normalization method is a highly efficient and effective tool for processing solar corona imagery.
  • This technique is suitable for current and future high-resolution solar observations.
  • The method enhances the visibility of solar structures across various scales and observation types.