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University of Illinois at Urbana-Champaign

Techniques for automated classification of nighttime ionospheric images

Abstract

dc:description

A large database of images of the night sky above Hawaii and Chile is being collected in order to study ionospheric structures. The images of interest are those that contain equatorial plasma bubbles (EPB) or medium-scale traveling ionospheric disturbances (MSTID). However the majority of the images collected contain neither EPBs nor MSTIDs, or are contaminated by other light sources or clouds. In order to identify the images of interest, discriminative classification models are considered for determining the relationship between measured image features and labels for a sequence of images. To provide features that enable this modeling, the use of texture, difference, object motion, correlation, and long-term variation measurements are explored. Additionally, the Local Fisher Discriminant Analysis (LFDA) algorithm is considered as a means to reduce the computational complexity of the classification process through dimensional reduction. It was found that a conditional random field (CRF) model provides the best classification accuracy. Accuracies of 80% - 90% were achieved for classification of EPBs, clear images and cloudy images. Classification of MSTIDs had accuracy of 65%, possibly due to the limited size of the test and training sets. The LFDA technique for dimensional reduction of the feature vector proved effective. When the classification accuracy using this data was compared to that which was dimensionally reduced using principal component analysis (PCA), the LFDA performed equally well or better for all feature vector lengths tested.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Electrical & Computer Engr
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gehrels, Thomas
Contributors dc:contributor
  • Makela, Jonathan J.

Subjects

dc:subject × 9

Rights

dc:rights
Statement dc:rights
  • Copyright 2013 Thomas Gehrels
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/44234
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/44234

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Gehrels, Thomas. Techniques for automated classification of nighttime ionospheric images. Thesis thesis, University of Illinois at Urbana-Champaign, 2013. http://hdl.handle.net/2142/44234