Landuse classification is an important problem in the remote sensing field. It can be used in a wide range of applications. In this paper, we propose a hybrid method fusing edges and regions information for the landuse classification of multispectral images. It mainly includes the steps of image pre-processing, initial segmentation and region merging. Especially, a novel spatial mean shift procedure is proposed so that some information can be extracted and used in the successive steps. Aiming at the multispectral images processing, we also design a band weighting strategy that give a proper weight to each band adoptively according to the region to be processed. Experimental results on the Landsat TM and ETM+ images validate the performance of the proposed method.


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    Titel :

    A band-weighted landuse classification method for multispectral images


    Beteiligte:
    Chunhong Pan, (Autor:in) / Gang Wu, (Autor:in) / Prinet, V. (Autor:in) / Qing Yang, (Autor:in) / Songde Ma, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    671950 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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