This paper discusses a technique that will enhance man-made features in SAR images. The technique uses a metric called fractal error. Developed by Cooper, et al. (1994) for aiding photointerpreters in detecting man-made features in aerial reconnaissance images, this metric is based upon the observed propensity of natural image features to fit a fractional Brownian motion (fBm) model. Natural scene features fit this model well, producing a small fractal error. Man-made features, on the other hand, usually do not fit the fBm model well and produce a relatively large fractal error. Therefore the fractal error is useful as a discriminant function for detecting man-made features in SAR imagery. The fractal error metric is defined, an approach to segmentating man-made objects in SAR images is discussed, and the results are presented.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Feature detection in synthetic aperture radar images using fractal error


    Beteiligte:
    Jansing, E.D. (Autor:in) / Chenoweth, D.L. (Autor:in) / Knecht, J. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.01.1997


    Format / Umfang :

    987168 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Feature Detection in Synthetic Aperture Radar Images Using Fractal Error

    Jansing, E. D. / Chenoweth, D. L. / Knecht, J. et al. | British Library Conference Proceedings | 1997



    3-D Terrain from Synthetic Aperture Radar Images

    Bors, A. / Hancock, E. / Wilson, R. et al. | British Library Conference Proceedings | 2000


    3-D terrain from synthetic aperture radar images

    Bors, A.G. / Hancock, E.R. / Wilson, R.C. | IEEE | 2000


    Synthetic Aperture Radar

    Doerry, A. W. / Dickey, F. M. | British Library Online Contents | 2004