Segmenting Chromospheric Images with Markov Random Fields

  • Michael J. Turmon
  • Judit M. Pap
Conference paper


The solar chromosphere roughly consists of three types of region: plage, network, and background. Thresholding individual pixel intensities is typically used to identify these regions in solar images. We have incorporated spatial information by using a Bayesian setup with an image prior that prefers spatially coherent labelings; resulting segmentations are more physically reasonable. These priors are a first step in developing an appropriate model for chromospheric images.


Convection Cell Individual Pixel Solar Image Markov Random Solar Chromosphere 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Michael J. Turmon
    • 1
  • Judit M. Pap
    • 2
  1. 1.Jet Propulsion LaboratoryPasadenaUSA
  2. 2.Department of AstronomyUCLALos AngelesUSA

Personalised recommendations