Support Vector Machine (SVM) is characteristic of processing complex data and high dimensional data. In this paper, a new approach of image decision-level fusion based on SVM and the corresponding fusion rule based on consensus theoretic were presented. Then to select a test area in Shaoxing City, Zhejiang Province, China, a fusion experiment was conducted using Landsat TM multispectral data (30 m) and IRS-C Pan data (5.8 m). Finally an evaluation on the fusion image was given. The results show that the overall classification accuracy of the fusion image reached 81.05%. The new fusion method could satisfy the requirement of land cover classification automatically.


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    Titel :

    A new method of remote sensing image decision-level fusion based on Support Vector Machine


    Beteiligte:
    Shuhe Zhao, (Autor:in) / Xiuwan Chen, (Autor:in) / Shandong Wang, (Autor:in) / Juliang Li, (Autor:in) / Wenbai Yang, (Autor:in)


    Erscheinungsdatum :

    2003-01-01


    Format / Umfang :

    338734 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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