Clutter removal techniques for GPR images in structure inspection tasks

Branislav Vuksanovic*, Nurul Jihan Farhah Bostanudin

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    This document analyses the performance of subspace signal processing techniques applied to ground penetrating radar (GPR) images in order to reduce the amount of clutter and noise in the measured GPR image. Two methods considered in this work are Principal Component Analysis (PCA) and Independent Component Analysis (ICA). An approach to combine those two techniques to improve their effectiveness when applied to GPR data is proposed in this paper. The experiments performed to gather GPR data and evaluate proposed algorithms are also described. The aim of undertaken experiments is to replicate conditions found in water reservoirs where cracks and holes in the reservoir foundations and joints cause excessive water leakages and losses to water companies and the UK economy in general. Performance of implemented algorithms is discussed and compared to the results achieved by a highly skilled human - GPR image analyst.

    Original languageEnglish
    Title of host publicationFourth International Conference on Digital Image Processing, ICDIP 2012
    Number of pages7
    Publication statusPublished - 1 Dec 2012
    Event4th International Conference on Digital Image Processing - Kuala Lumpur, Malaysia
    Duration: 7 Apr 20128 Apr 2012


    Conference4th International Conference on Digital Image Processing
    Abbreviated titleICDIP 2012
    CityKuala Lumpur


    • clutter removal
    • eigenvalues
    • Ground penetrating radar
    • independent component analysis (ICA)
    • principal component analysis (PCA)


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