Mathematics – Probability
Scientific paper
Dec 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agufmsh23b0372j&link_type=abstract
American Geophysical Union, Fall Meeting 2006, abstract #SH23B-0372
Mathematics
Probability
7529 Photosphere, 7538 Solar Irradiance, 7594 Instruments And Techniques
Scientific paper
Turmon, Pap, and Mukhtar (2002: Astrophysical Journal 568, 396) present a statistical method for identifying sunspots, faculae, and quiet Sun in SOHO/MDI magnetograms and intensity images. This paper describes progress toward an extension of this method for identifying more complete feature sets using the multidimensional images (magnetic flux, line-of-sight velocity, intensity, equivalent width, and central line depth) obtained from 1992-2003 with the NASA/NSO Spectromagnetograph (SPM) and since 2003 with the NSO/SOLIS Vector Spectromagnetograph (VSM). We discuss the selection of the feature set and training images, and the temporal and spatial consistency of the NSO data. We determine the class-conditional (Bayesian prior) probability densities using both Gaussian mixture models and direct histogram interpolation, and show projections of the multidimensional probability densities derived from SPM observations. Finally, we compare various feature identification methods driven by these two types of prior.
Jones Philip H.
Pap Judit M.
Turmon M. J.
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