TY - JOUR
T1 - Automatic detection of magnetic flux emergings in the solar atmosphere from full-disk magnetogram sequences
AU - Fu, Gang
AU - Shih, Frank
AU - Wang, Haimin
N1 - Funding Information:
Manuscript received January 21, 2007; revised July 20, 2008. Current version published October 10, 2008. This work was supported by the National Science Foundation (NSF) under Grants IIS 03-24816, ATM 05-48952, ATM 05-36921, and ATM 03-13591. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Minh N. Do.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - Circular harmonic filter
KW - Emerging Flux Region (EFR)
KW - Kalman filter
KW - Michelson Doppler Imager (MDI)
KW - Solar features
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U2 - 10.1109/TIP.2008.2004616
DO - 10.1109/TIP.2008.2004616
M3 - Article
C2 - 18972657
AN - SCOPUS:54949155132
SN - 1057-7149
VL - 17
SP - 2174
EP - 2185
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 11
ER -