Bayesian Automatic Classification Of HMI Images

Details Bayesian Automatic Classification Of HMI Images Bayesian Automatic Classification Of HMI Images

May 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011spd....42.2134u&link_type=abstract

American Astronomical Society, SPD meeting #42, #21.34; Bulletin of the American Astronomical Society, Vol. 43, 2011

Astronomy and Astrophysics

Astronomy

Scientific paper

The Bayesian automatic classification system known as "AutoClass" finds a set of class definitions based on a set of observed data and assigns data to classes without human supervision. It has been applied to Mt Wilson data to improve modeling of total solar irradiance variations (Ulrich, et al, 2010). We apply AutoClass to HMI observables to automatically identify regions of the solar surface. To prevent small instrument artifacts from interfering with class identification, we apply a flat-field correction and a rotationally shifted temporal average to the HMI images prior to processing with AutoClass. Additionally, the sensitivity of AutoClass to instrumental artifacts is investigated.

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