Tomographic synthetic aperture radar (SAR) imaging has been recently formulated in a wavelet-based compressed sensing (CS) framework. This paper reviews the underlying sparsity-driven algorithms for single-channel as well as polarimetric tomography, and discusses its applicability in terms of ambiguity rejection, physical validity, acquisition geometry, and required a priori knowledge. In addition, we present a comparison with traditional nonparametric spectral estimators by using L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR).


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    Title :

    Wavelet-Based Compressed Sensing for Polarimetric SAR Tomography


    Contributors:

    Conference:

    2013 ; Frascati, Italy



    Publication date :

    2013-01-30


    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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