TY - JOUR
T1 - Automatic Detection and Tracking of Coronal Mass Ejections. II. Multiscale Filtering of Coronagraph Images
AU - Byrne, Jason P.
AU - Morgan, Huw
AU - Habbal, Shadia Rifai
AU - Gallagher, Peter T.
PY - 2012/6/1
Y1 - 2012/6/1
N2 - Studying coronal mass ejections (CMEs) in coronagraph data can be
challenging due to their diffuse structure and transient nature, and
user-specific biases may be introduced through visual inspection of the
images. The large amount of data available from the Solar and
Heliospheric Observatory (SOHO), Solar TErrestrial RElations Observatory
(STEREO), and future coronagraph missions also makes manual cataloging
of CMEs tedious, and so a robust method of detection and analysis is
required. This has led to the development of automated CME detection and
cataloging packages such as CACTus, SEEDS, and ARTEMIS. Here, we present
the development of a new CORIMP (coronal image processing) CME detection
and tracking technique that overcomes many of the drawbacks of current
catalogs. It works by first employing the dynamic CME separation
technique outlined in a companion paper, and then characterizing CME
structure via a multiscale edge-detection algorithm. The detections are
chained through time to determine the CME kinematics and morphological
changes as it propagates across the plane of sky. The effectiveness of
the method is demonstrated by its application to a selection of
SOHO/LASCO and STEREO/SECCHI images, as well as to synthetic coronagraph
images created from a model corona with a variety of CMEs. The
algorithms described in this article are being applied to the whole
LASCO and SECCHI data sets, and a catalog of results will soon be
available to the public.
AB - Studying coronal mass ejections (CMEs) in coronagraph data can be
challenging due to their diffuse structure and transient nature, and
user-specific biases may be introduced through visual inspection of the
images. The large amount of data available from the Solar and
Heliospheric Observatory (SOHO), Solar TErrestrial RElations Observatory
(STEREO), and future coronagraph missions also makes manual cataloging
of CMEs tedious, and so a robust method of detection and analysis is
required. This has led to the development of automated CME detection and
cataloging packages such as CACTus, SEEDS, and ARTEMIS. Here, we present
the development of a new CORIMP (coronal image processing) CME detection
and tracking technique that overcomes many of the drawbacks of current
catalogs. It works by first employing the dynamic CME separation
technique outlined in a companion paper, and then characterizing CME
structure via a multiscale edge-detection algorithm. The detections are
chained through time to determine the CME kinematics and morphological
changes as it propagates across the plane of sky. The effectiveness of
the method is demonstrated by its application to a selection of
SOHO/LASCO and STEREO/SECCHI images, as well as to synthetic coronagraph
images created from a model corona with a variety of CMEs. The
algorithms described in this article are being applied to the whole
LASCO and SECCHI data sets, and a catalog of results will soon be
available to the public.
KW - Sun: activity
KW - Sun: corona
KW - Sun: coronal mass ejections (CMEs)
KW - techniques: image processing
UR - http://hdl.handle.net/2160/9110
U2 - 10.1088/0004-637X/752/2/145
DO - 10.1088/0004-637X/752/2/145
M3 - Article
SN - 0004-637X
VL - 752
SP - 145
JO - Astrophysical Journal
JF - Astrophysical Journal
IS - 2
ER -