We present an algorithm for identifying linear mixtures of a specified set of materials in 0.4-2.5 /spl mu/m airborne imaging spectrometer data. The algorithm is invariant to the illumination and atmospheric conditions and the relative amounts of the specified materials within a pixel. Only the spectral reflectance functions for the specified materials are required by the algorithm. Invariance over illumination and atmosphere conditions is achieved by incorporating a physical model for scene variability in the constrained optimization formulation. The algorithm also computes estimates of the amounts of the specified materials in identified mixtures. We demonstrate the effectiveness of the algorithm using real and synthetic HYDICE imagery acquired over a range of conditions and altitudes.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Invariant mixture recognition in hyperspectral images


    Beteiligte:
    Pei-Hsiu Suen, (Autor:in) / Healey, G. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    835353 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Invariant Mixture Recognition in Hyperspectral Images

    Suen, P. / Healey, G. / IEEE | British Library Conference Proceedings | 2001


    Face Recognition in Hyperspectral Images

    Pan, Z. / Healey, G. / Prasad, M. et al. | British Library Conference Proceedings | 2003


    Face recognition in hyperspectral images

    Zhihong Pan, / Healey, G.E. / Prascad, M. et al. | IEEE | 2003



    Invariant Methods of the Recognition of Binary Images

    Vasin, Y. G. / Lebedev, L. I. | British Library Online Contents | 1998