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Automated detection of Coronal Mass Ejections in Visible Emission Line Coronagraph (VELC) on-board ADITYA-L1

Published online by Cambridge University Press:  27 November 2018

Ritesh Patel Open the ORCID record for Ritesh Patel [Opens in a new window] ,
K. Amareswari ,
Vaibhav Pant ,
Dipankar Banerjee Open the ORCID record for Dipankar Banerjee [Opens in a new window]  and
K. Sankarasubramanian
Ritesh Patel
Affiliation:
Indian Institute of Astrophysics, Bengaluru, India; email: ritesh.patel@iiap.res.in
K. Amareswari
Affiliation:
ISRO Satellite Centre, Bengaluru, India;
Vaibhav Pant
Affiliation:
Indian Institute of Astrophysics, Bengaluru, India; email: ritesh.patel@iiap.res.in
Dipankar Banerjee
Affiliation:
Indian Institute of Astrophysics, Bengaluru, India; email: ritesh.patel@iiap.res.in CESSI, IISER, Kolkata, India
K. Sankarasubramanian
Affiliation:
Indian Institute of Astrophysics, Bengaluru, India; email: ritesh.patel@iiap.res.in ISRO Satellite Centre, Bengaluru, India;
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Abstract

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An onboard automated coronal mass ejections (CMEs) detection algorithm has been developed for Visible Emission Line Coronagraph (VELC) onboard ADITYA-L1. The aim of this algorithm is to reduce the load on telemetry by sending the high spatial (~ 2.51 arcsec pixel−1) and temporal (1 s) resolution images of corona from 1.05 R⊙ to 3 R⊙, containing CMEs and rejecting others. It is based on intensity thresholding followed by an area thresholding in successive running difference images which are re-binned to lower resolution to improve signal to noise. Here we present the results of application of the algorithm on synthetic corona images generated for the VELC field of view (FOV).

Keywords

SunCoronaCoronal Mass EjectionsData management
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 13 , Symposium S340: Long-term Datasets for the Understanding of Solar and Stellar Magnetic Cycles , February 2018 , pp. 171 - 172
Copyright
Copyright © International Astronomical Union 2018 

References

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