Data fusion on remote sensing is one of important problems in current image processing. The key of a successful image fusion is to find effective and practical image fusion algorithm. To eliminate image data redundancy for two different remote sensing images, a new approach using the constrained nonnegative matrix factorization for remote image fusion between Landsat ETM+ panchromatic and CBERS multi-spectral images is proposed. Visual and statistical analyses prove that the concept of fusion based on constrained nonnegative matrix factorization is promising, and it does significantly increasing the signal-to-noise ratio and improve the fusion quality compared to conventional IHS and wavelet fusion techniques.


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    Titel :

    A Remote Sensing Image Fusion Algorithm Based on Constrained Nonnegative Matrix Factorization


    Beteiligte:
    Wang, Zhongni (Autor:in) / Yu, Xianchuan (Autor:in) / Zhang, Libao (Autor:in)


    Erscheinungsdatum :

    01.05.2008


    Format / Umfang :

    1460570 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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