Joint application of high-pass eigenimages and sparse blind deconvolution for improved reflectivity models of historic graves

PreviousNext No Access18th International Conference on Ground Penetrating Radar, Golden, Colorado, 14–19 June 2020Joint application of high-pass eigenimages and sparse blind deconvolution for improved reflectivity models of historic gravesAuthors: Christine DownsSajad JazayeriLori CollinsTravis DoeringChristine DownsUniversity of South Florida, United StatesSearch for more papers by this author, Sajad JazayeriUniversity of South Florida, United StatesSearch for more papers by this author, Lori CollinsUniversity of South Florida, United StatesSearch for more papers by this author, and Travis DoeringUniversity of South Florida, United StatesSearch for more papers by this authorhttps://doi.org/10.1190/gpr2020-089.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Sharpening ground-penetrating radar (GPR) images remains a persistent challenge. Two approaches in particular—singular value decomposition (SVD) and sparse blind deconvolution (SBD)—have been shown to effectively sharpen GPR images and resolve a reflectivity model, respectively though they have not been used together. To our knowledge, neither approach has been used to process GPR data from archaeological sites. SVD is capable of completely removing the direct wave without compromising the response it has overprinted. It can also remove user-specified, spatially-discontinuous components of the GPR image. SBD benefits from SVD by returning a physically meaningful reflectivity model of GPR data not possible from the original data. This paper highlights the treatment of a GPR profile acquired over two historic graves at Cape Canaveral, FL. The most dominant structures (a.k.a. the signal components with the highest trace-to-trace correlation and strongest energy) are the direct wave, horizontal banding, and ringing coming from surface features. The first five eigenimages from SVD, which capture these structures, define the threshold for an eigenimage high-pass. SBD on the SVD-filtered GPR data results in a reflectivity model that can better capture diffraction patterns produced by the burials as well as very shallow diffractions overprinted by the direct wave in the original data. Keywords: reflectivity, GPR, blind deconvolution, filtering, processingPermalink: https://doi.org/10.1190/gpr2020-089.1FiguresReferencesRelatedDetails 18th International Conference on Ground Penetrating Radar, Golden, Colorado, 14–19 June 2020ISSN (online):2159-6832Copyright: 2020 Pages: 455 publication data© 2020 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 11 Nov 2020 CITATION INFORMATION Christine Downs, Sajad Jazayeri, Lori Collins, and Travis Doering, (2020), "Joint application of high-pass eigenimages and sparse blind deconvolution for improved reflectivity models of historic graves," SEG Global Meeting Abstracts : 340-343. https://doi.org/10.1190/gpr2020-089.1 Plain-Language Summary KeywordsreflectivityGPRblind deconvolutionfilteringprocessingPDF DownloadLoading ...