Hyperspectral imagery (HSI) has high spectral dimensionality which presents a serious challenge to HSI processing, and so reduction of dimensionality is necessary. Band selection (BS) is one of the categories of dimensionality reduction methods. Existing BS methods have expensive cost, need prior information or only cater for classification. In order to get an efficient and unsupervised BS method for spectral unmixing, two aspects work are done. First, original N-FINDR algorithm is greatly improved by substituting volume calculation for distance test. Second, the improved N-FINDR algorithm is used to construct an unsupervised BS method for spectral unmixing. Both theory and experiments prove that the new unsupervised BS method is very effective.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unsupervised band selection method based on improved N-FINDR algorithm for spectral unmixing


    Beteiligte:
    Liguo Wang, (Autor:in) / Ye Zhang, (Autor:in) / Yanfeng Gu, (Autor:in)


    Erscheinungsdatum :

    2006-01-01


    Format / Umfang :

    2429328 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Spectral unmixing algorithms based on statistical models [2480-03]

    Endsley, N. H. / SPIE | British Library Conference Proceedings | 1995


    A novel hyperspectral image clustering method based on spectral unmixing

    Gholizadeh, Hamed / Zoej, Mohammad Javad Valadan / Mojaradi, Barat | IEEE | 2012


    Joint Blind Deconvolution and Spectral Unmixing of Hyperspectral Images

    Zhang, Q. | British Library Conference Proceedings | 2014


    CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

    Crist, Eric P. / Thelen, Brian J. / Carrara, David A. | SPIE | 1998


    Spectral-Spatial Joint Sparsity Unmixing of Hyperspectral Data using Overcomplete Dictionaries

    Bieniarz, Jakub / Aguilera, Esteban / Zhu, Xiao Xiang et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2014

    Freier Zugriff