It is expected, that ship detection and classification in SAR satellite imagery will be part of future downstream services for various applications, e.g. surveillance of fishery zones or tracking of cargo ships. Due to the requirements of operational services and due to the potential of high resolution SAR (e.g. TerraSAR-X), there is a need for composing, optimization, and validation of specific fully automated image processing chains. The presented processing chain covers all steps from land masking, screening, object segmentation, feature extraction to classification and parameter estimation. The chain is base for experiments with both open sea and harbor scenes for ship detection and monitoring. Within this chain, a classification component for SAR ship and non-ship decision is investigated. Based on many extracted image features and numerous image chips for training and test, some promissing results are presented and discussed. Since the classification can reduce the false alarms of the screening component, the processing chain is expected to work on images with less good weather and signal conditions and to extract ships with lower reflexions.


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    Titel :

    SAR signature analysis for TerraSAR-X-based ship monitoring


    Beteiligte:
    Saur, G. (Autor:in) / Teutsch, M. (Autor:in)

    Kongress:

    2010


    Erscheinungsdatum :

    2010



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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