Astronomy and Astrophysics – Astrophysics
Scientific paper
Dec 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010agufmsh23c1873y&link_type=abstract
American Geophysical Union, Fall Meeting 2010, abstract #SH23C-1873
Astronomy and Astrophysics
Astrophysics
[1980] Informatics / Spatial Analysis And Representation, [1984] Informatics / Statistical Methods: Descriptive, [7509] Solar Physics, Astrophysics, And Astronomy / Corona, [7594] Solar Physics, Astrophysics, And Astronomy / Instruments And Techniques
Scientific paper
Automated coronal seismology will require measurements of the structure that supports an oscillatory signal; for example, a measurement of the loop length of a transversely oscillating loop can be used to estimate the coronal magnetic field (Nakariakov& Ofman 2001). One of the results from the recently published Bayesian probability based automated oscillation detection algorithm (Ireland et al., 2010) is a probability map. This is an image of the probability that each pixel from a set of images contains an oscillatory signal. A map from a significant detection contains one or more clusters of high probability pixels dispersed amongst mostly pixels of low probability. These low probability pixels amount to noise while the clusters of high probability are the desired signal. A visual inspection of the probability maps that contain significant signal reveal that the clusters of pixels contain structure that corresponds to physical regions in the original images i.e. oscillating loops. A necessary step for using these oscillation probability maps is to extract and characterize these high probability regions. A natural choice for an appropriate representation of these structures especially given their corresponds to real extended features such as loops is the curvelet transform (Candes and Donoho, 1999 and Candes et al., 2005). In this work we present a preliminary analysis of these probability maps using curvelets to isolate and characterize regions of high probability. The suitability of this technique for the pipeline processing of Solar Dynamics Observatory data is also discussed.
Ireland Jack
Young Carolynn
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