A CME Automatic Detection Method Based on Adaptive Background Learning Technology

Joint Authors

Zhang, Qinghui
Qiang, Zhenping
Bai, Xianyong
Lin, Hong

Source

Advances in Astronomy

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-11-07

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Astronomy

Abstract EN

In this paper, we describe a technique, which uses an adaptive background learning method to detect the CME (coronal mass ejections) automatically from SOHO/LASCO C2 image sequences.

The method consists of several modules: adaptive background module, candidate CME area detection module, and CME detection module.

The core of the method is based on adaptive background learning, where CMEs are assumed to be a foreground moving object outward as observed in running-difference time series.

Using the static and dynamic features to model the corona observation scene can more accurately describe the complex background.

Moreover, the method can detect the subtle changes in the corona sequences while filtering their noise effectively.

We applied this method to a month of continuous corona images, compared the result with CDAW, CACTus, SEEDS, and CORIMP catalogs and found a good detection rate in the automatic methods.

It detected about 73% of the CMEs listed in the CDAW CME catalog, which is identified by human visual inspection.

Currently, the derived parameters are position angle, angular width, linear velocity, minimum velocity, and maximum velocity of CMES.

Other parameters could also easily be added if needed.

American Psychological Association (APA)

Qiang, Zhenping& Bai, Xianyong& Zhang, Qinghui& Lin, Hong. 2019. A CME Automatic Detection Method Based on Adaptive Background Learning Technology. Advances in Astronomy،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1114435

Modern Language Association (MLA)

Zhang, Qinghui…[et al.]. A CME Automatic Detection Method Based on Adaptive Background Learning Technology. Advances in Astronomy No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1114435

American Medical Association (AMA)

Qiang, Zhenping& Bai, Xianyong& Zhang, Qinghui& Lin, Hong. A CME Automatic Detection Method Based on Adaptive Background Learning Technology. Advances in Astronomy. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1114435

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1114435