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