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.


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    Titel :

    Using attribute trees to analyse auroral appearance over Canada


    Beteiligte:
    Syrjasuo, M.T. (Autor:in) / Donovan, E.F. (Autor:in) / Peura, M. (Autor:in)


    Erscheinungsdatum :

    2002-01-01


    Format / Umfang :

    745890 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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