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D.1c Multiscale Gaussian Normalization

  • Tool name: Multiscale Gaussian Normalization (MGN)
  • Developers: Morgan (Aberystwyth) & Druckmuller (Brno)
  • Main Contact: Huw Morgan (hmorgan@aber.ac.uk)
  • Basic description: This package applies MGN processing to input image. The MGN is an image processing tool that enhances fainter & small-scale spatial structures in an efficient way. See method paper referenced below. The current version is slightly changed from the published method. Most important difference is the inclusion of a constant in the denominator (instead of dividing by std. dev., divide by std. dev. plus small constant to help reduce amplification of noise).
  • Language: IDL, Python (Erwin?)
  • Resource needed to use: Desktop
  • Host location:
  • Current status: Works well with most input images. Probably use of photospheric/chromospheric data needs some testing to determine values of some parameters.
  • 6-month plan to availability: (1) Test on photospheric & chromospheric data (2) Python version, Erwin?
  • Status of documentation: Method paper. More technical/practical documentation currently sparse (does not exist).
  • Test status: OK on AIA/SDO.
  • How to reference tool in publication: http://adsabs.harvard.edu/abs/2014SoPh..289.2945M