Automatic target recognition (ATR) in hyperspectral imagery is a challenging problem due to recent advances of remote sensing instruments which have significantly improved sensor's spectral resolution. As a result, small and subtle targets can be uncovered and extracted from image scenes, which may not be identified by prior knowledge. In particular, when target size is smaller than pixel resolution, target recognition must be carried out at subpixel level. Under such circumstance, traditional spatial-based image processing techniques are generally not applicable and may not perform well if they are applied. The work presented here investigates this issue and develops spectral-based algorithms for automatic spectral target recognition (ASTR) in hyperspectral imagery with no required a priori knowledge, specifically, in reconnaissance and surveillance applications. The proposed ASTR consists of two stage processes, automatic target generation process (ATGP) followed by target classification process (TCP). The ATGP generates a set of targets from image data in an unsupervised manner which will subsequently be classified by the TCP. Depending upon how an initial target is selected in ATGP, two versions of the ASTR can be implemented, referred to as desired target detection and classification algorithm (DTDCA) and automatic target detection and classification algorithm (ATDCA). The former can be used to search for a specific target in unknown scenes while the latter can be used to detect anomalies in blind environments. In order to evaluate their performance, a comparative and quantitative study using real hyperspectral images is conducted for analysis.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic spectral target recognition in hyperspectral imagery


    Beteiligte:
    Hsuan Ren, (Autor:in) / Chein-I Chang, (Autor:in)


    Erscheinungsdatum :

    2003-10-01


    Format / Umfang :

    10782937 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Automatic target recognition for hyperspectral imagery using high-order statistics

    Hsuan Ren, / Qian Du, / Jing Wang, et al. | IEEE | 2006



    Kernel Spectral Matched Filter for Hyperspectral Imagery

    Kwon, H. / Nasrabadi, N. M. | British Library Online Contents | 2007


    Dynamics of Target Detection Using Drone Based Hyperspectral Imagery

    Jha, Sudhanshu Shekhar / Nidamanuri, Rama Rao | Springer Verlag | 2020