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Multiscale Detection and Characterisation of CMEs

Multiscale Detection and Characterisation of CMEs. J. P. Byrne 1 , P. T. Gallagher 1 , C. A. Young 2 and R. T. J. McAteer 3 1 Astrophysics Research Group, School of Physics, Trinity College Dublin, Dublin 2, Ireland.

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Multiscale Detection and Characterisation of CMEs

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  1. Multiscale Detection and Characterisation of CMEs J. P. Byrne1, P. T. Gallagher1, C. A. Young2 and R. T. J. McAteer3 1 Astrophysics Research Group, School of Physics, Trinity College Dublin, Dublin 2, Ireland. 2 ADNET Systems Inc., NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA. 3 Catholic University of America, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA. STEREO/Cor1 24-Jan-07

  2. Overview • CME Models • Image Processing: Multiscale methods • CME Morphology & Kinematics • Application to LASCO and STEREO/SECCHI LASCO/C3 27-Feb-00

  3. CME Models • Magnetic Flux-Rope: • Forbes & Priest, 1990 • Chen & Krall, 2003 • Magnetic Break-out: • Antiochos et al. 1999 • Lynch et al. 2004

  4. Image Pre-Processing • Normalisation - exposure time - CCD bias - data dropouts • Background subtraction • Median filtering (de-noising) LASCO/C2 18-Apr-00

  5. Finding the CME Front Edge Detection:

  6. Our Algorithm Image Pre-Processing 1) Multiscale Decomposition Vector-Arrow Field 2) Gradient Space Information 3) Spatio-Temporal Filter 4) Non-Maxima Suppression 5) CME Front Characterisation Kinematics & Morphology

  7. Our Algorithm Image Pre-Processing 1) Multiscale Decomposition CME Vector Flow Field 2) Spatio-Temporal Filter 3) Non-Maxima Suppression 4) CME Front Characterisation Kinematics & Morphology

  8. 1) Multiscale Decomposition Wavelets: • Scaling / dilation factor (a) • Shifting / translation factor (b) • Suppress noise

  9. 1) Multiscale Decomposition Input: f Low pass: Approximation High pass: Detail LASCO/C2 24-Jan-07

  10. 1) Multiscale Decomposition Horizontal Direction: Scale 1 Scale 3 Scale 5 Vertical Direction: Scale 1 Scale 3 Scale 5

  11. 2) Gradient Space Information Consider the Gradient of an image:(which points in the direction of most rapid change) The gradient specifies: 1) Magnitude: 2) Direction: We have the Detail at a scale (N+1) resulting from the directional Derivative-of-Gaussian convolved with the Approximation at scale (N): So too can the Magnitude and Direction be taken from the multiscale decomposition as illustrated…

  12. 2) Gradient Space Information Original: Angle: Magnitude: (McAteer et al. 2007)

  13. 2) Gradient Space Information Vectors with magnitude: and inclination angle:

  14. Our Algorithm Image Pre-Processing 1) Multiscale Decomposition CME Vector Flow Field 2) Spatio-Temporal Filter 3) Non-Maxima Suppression 4) CME Front Characterisation Kinematics & Morphology

  15. 2) Spatio-Temporal Analysis Degrees of Freedom: Scale, Magnitude & Angle … in Space & Time

  16. Our Algorithm Image Pre-Processing 1) Multiscale Decomposition CME Vector Flow Field 2) Spatio-Temporal Filter 3) Non-Maxima Suppression 4) CME Front Characterisation Kinematics & Morphology

  17. 3) Non-Maxima Suppression Nearest-neighbour info. Criteria of angle and magnitude from gradients. Pixels chained along edges. (Image by C.A.Young)

  18. Our Algorithm Image Pre-Processing 1) Multiscale Decomposition CME Vector Flow Field 2) Spatio-Temporal Filter 3) Non-Maxima Suppression 4) CME Front Characterisation Kinematics & Morphology

  19. 4) CME Front Characterisation • Ellipse fit • Height, Width, Curvature, Orientation STEREO/Cor1 24-Jan-07 (H.E. Schrank, 1961)

  20. SOHO/LASCO CMEs C2 & C3 18-Jan-00

  21. SOHO/LASCO CMEs C2 & C3 19-Apr-00

  22. SOHO/LASCO CMEs C2 & C3 23-Apr-01

  23. STEREO/Cor1 CMEs SECCHI-A 9-Feb-07

  24. STEREO/Cor1 CMEs SECCHI-A 24-Jan-07

  25. STEREO/Cor1 CMEs SECCHI-B & SECCHI-A 24-Jan-07

  26. STEREO/Cor1 CMEs SECCHI-A 24-Jan-07

  27. CME Kinematics LASCO/C2 24-Jan-07

  28. Next Steps… • More data; distribution of CME kinematics. • Multiple view points (STEREO); triangulation / projection effects. • Automated front detection; space weather forecasting. STEREO illustration

  29. Thank You NRL: Angelos Vourlidas, Simon Plunkett. This work is supported by grants from Science Foundation Ireland & NASA’s Living with a Star Program. Acknowledgments jbyrne6@gmail.com

  30. SOHO/LASCO CMEs C2 & C3 23-Apr-01

  31. 2) Spatio-Temporal Analysis Degrees of Freedom: Scale, Magnitude & Angle … in Space & Time

  32. Vector Flow Field Vectors with magnitude: and inclination angle:

  33. remove Normalizing Radial Graded Filter • Radially the coronagraph image intensity drops off steeply. • The intensity is normalized by subtracting the mean and dividing by the standard deviation. (Huw et al. 2006)

  34. remove Scale Chaining / Masks Degrees of Freedom: Scale, Magnitude & Angle … in Space & Time => Spatio-Temporal Image Processing & Thresholding

  35. Method FlowChart Image preprocessing Multiscale decomposition scale chaining (denoising masks) Gradient space vector field (angle & magnitude) Spatio-temporal filter (noisy masks) NRGF: radial filter Combine scale chain & spatiotemp => filter masks Non-maxima suppression Ellipse characterization

  36. Remove Movie Scripts • http://www.maths.tcd.ie/~jaydog/Solar/canny_atrous/automation/20000118_arrows_combined_rebin.html • http://www.maths.tcd.ie/~jaydog/Solar/canny_atrous/automation/20000418_arrows_combined_rebin.html • http://www.maths.tcd.ie/~jaydog/Solar/canny_atrous/automation/20040401_arrows_combined_rebin.html • http://www.maths.tcd.ie/~jaydog/Solar/CME_ellipse_movies/24jan07/C2_movie_ell.html • http://www.maths.tcd.ie/~jaydog/Solar/CME_ellipse_movies/24jan07/C3_movie_ell.html • www.maths.tcd.ie/~jaydog/Solar/STEREO/pb/24jan07/Graphs_plots.html

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