Abstract
In this paper, we present a novel method to detect Emerging Flux Regions (EFRs) in the solar atmosphere from consecutive full-disk Michelson Doppler Imager (MDI) magnetogram sequences. To our knowledge, this is the first developed technique for automatically detecting EFRs. The method includes several steps. First, the projection distortion on the MDI magnetograms is corrected. Second, the bipolar regions are extracted by applying multiscale circular harmonic filters. Third, the extracted bipolar regions are traced in consecutive MDI frames by Kalman filter as candidate EFRs. Fourth, the properties, such as positive and negative magnetic fluxes and distance between two polarities, are measured in each frame. Finally, a feature vector is constructed for each bipolar region using the measured properties, and the Support Vector Machine (SVM) classifier is applied to distinguish EFRs from other regions. Experimental results show that the detection rate of EFRs is 96.4% and of non-EFRs is 98.0%, and the false alarm rate is 25.7%, based on all the available MDI magnetograms in 2001 and 2002.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2174-2185 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Image Processing |
| Volume | 17 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2008 |
All Science Journal Classification (ASJC) codes
- Software
- Computer Graphics and Computer-Aided Design
Keywords
- Circular harmonic filter
- Emerging Flux Region (EFR)
- Kalman filter
- Michelson Doppler Imager (MDI)
- Solar features
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