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. 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

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

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

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

Finding the CME Front Edge Detection:

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

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

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

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

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

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

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

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

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

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

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

3) Non-Maxima Suppression 1)Nearest-neighbour info. 2)Criteria of angle and magnitude from gradients. 3)Pixels chained along edges. (Image by C.A.Young)

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

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

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

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

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

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

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

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

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

LASCO/C2 24-Jan-07 CME Kinematics

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

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

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

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

Vector Flow Field Vectors with magnitude: and inclination angle:

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) remove

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

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

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