Automatic detection of prominence eruption using consecutive solar images

Document Type

Article

Publication Date

1-1-2007

Abstract

Prominences are clouds of relatively cool and dense gas in the solar atmosphere. In this paper, we present a new method to detect and characterize the prominence eruptions. The input is a sequence of consecutive H α solar images, and the output is a list of prominence eruption events detected. We extract the limb events and measure their associated properties by applying image processing techniques. First, we perform image normalization and noise removal. Then, we isolate the limb objects and identify the prominence features. Finally, we apply pattern recognition techniques to classify the eruptive prominences. The characteristics of prominence eruptions, such as brightness, angular width, radial height and velocity are measured. The method presented can lead to automatic monitoring and characterization of solar events. © 2007 IEEE.

Identifier

33846284470 (Scopus)

Publication Title

IEEE Transactions on Circuits and Systems for Video Technology

External Full Text Location

https://doi.org/10.1109/TCSVT.2006.887084

ISSN

10518215

First Page

79

Last Page

85

Issue

1

Volume

17

Grant

ATM 05-36921

Fund Ref

National Science Foundation

This document is currently not available here.

Share

COinS