Increasingly, multi-sensor systems are being developed to collect, process, and disseminate image and non-image data. Applications include homeland security, monitoring of facilities, and military situation assessment. Fusion of image and non-image data has traditionally been performed with extensive human-in-the-loop involvement. Typically the image data are used as the "fundamental" data source with non-image data simply overlaid on the image data, or conversely the non-image data are treated as fundamental, and the image data are used to confirm the identity of observed entities. This paper discusses the problem of multi-sensor fusion and argues that new techniques are emerging that allows fusion of image and non-image data at multiple levels of inference from the "raw" data level, to the feature level, decision-level, and knowledge level.


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    Titel :

    Perspectives on the fusion of image and non-image data


    Beteiligte:
    Hall, D.L. (Autor:in)


    Erscheinungsdatum :

    2003-01-01


    Format / Umfang :

    287928 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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