Using attribute trees to analyse auroral appearance over Canada

• Published in: Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings pp. 289 - 295
• Main Authors: Syrjasuo, M.T., Donovan, E.F., Peura, M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2002
• Subjects: Classification tree analysis; Current; Displays; Extraterrestrial measurements; Image analysis; Image retrieval; Instruments; Ionosphere; Large-scale systems; Working environment noise
• ISBN: 9780769518589; 0769518583
• DOI: 10.1109/ACV.2002.1182196

Modern space research uses both satellite-born and ground-based instruments to measure the near-Earth space environment. Studying the auroral display provides information of the electric currents in the ionosphere, which is why automated imaging stations capture millions of auroral all-sky images every year. However, due to the nature of the aurora, these images are difficult to analyse automatically: photon-limited images are noisy, and objects are irregular and difficult to identify. We used hierarchical attribute trees in a large scale experiment with over 350,000 auroral all-sky images. Tree-to-tree distances were utilised in classifying images and in locating similar images in content-based image retrieval fashion.