Existing classification methods which are based on the homogeneous-region mostly involve the best segmentation scale choice. Using the so-called best segmentation scale to respond the subjective defined objects, it would not be the best way for classification. Therefore we propose a simple classification method with high precision. It is a new kind of multi-scale homogeneous-region model, fully uses the longitudinal information which the homogeneous-region model provides, and adopts the scale-span classification method based on decision tree to improve the accuracy, rather than directly carrying on the best scale choice. The experimental result proves the scale-span method is more accurate than sole scale lassification.


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    Titel :

    The Scale-Span Classification Research for Multispectral Images Based on the Homogeneous-Region


    Beteiligte:
    Lin, Liqun (Autor:in) / Shu, Ning (Autor:in) / Gong, Yan (Autor:in) / Xiao, Jun (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    2590801 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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