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Activity Number: 411
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2007 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #310239
Title: Multiscale Solar Image Processing
Author(s): C. Alex Young*+ and Jack Ireland and R.T. James McAteer and Peter T. Gallagher
Companies: National Aeronautics and Space Administration and ADNET Systems, Inc. and Catholic University of America and Trinity College Dublin
Address: Goddard Space Flight Center, Greenbelt, MD, 20771,
Keywords: wavelets ; curvelets ; image processing ; astrophysics

Wavelets have been successfully used as a tool for noise reduction and general processing of images to view CMEs. Coronal Mass Ejections (CMEs) are large eruptions of plasma from the Sun. When CMEs travel to the Earth they can have hazardous effects including disrupting satellites and crippling electric power grids on the grounds. Because of this it is important to detect, track and understand CMEs to better predict their occurrence and impact on the Earth. The detection challenge is primarily because CMEs are extremely faint when compared to background. Wavelets have proved useful but have limitations. Wavelets are well suited for describing point singularities but edges or curves describe much of the interesting information in these images. The curvelet transform has promise as an optimal representation for CME images. We present a preliminary study of the use of these transforms.

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