Using attribute trees to analyse auroral appearance over Canada


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 allsky images. Tree-to-tree distances were utilised in classifying images and in locating similar images in content-based image retrieval fashion.

DOI: 10.1109/ACV.2002.1182196

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@inproceedings{Syrjsuo2002UsingAT, title={Using attribute trees to analyse auroral appearance over Canada}, author={Mikko T. Syrj{\"a}suo and Eric F. Donovan and Markus Peura}, booktitle={WACV}, year={2002} }