- -

On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

  • Estadisticas de Uso

On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods

Show simple item record

Files in this item

dc.contributor.author Safont Armero, Gonzalo es_ES
dc.contributor.author Salazar Afanador, Addisson es_ES
dc.contributor.author Rodriguez, Alberto es_ES
dc.contributor.author Vergara Domínguez, Luís es_ES
dc.date.accessioned 2015-09-09T12:03:11Z
dc.date.available 2015-09-09T12:03:11Z
dc.date.issued 2014-08-14
dc.identifier.issn 2072-4292
dc.identifier.uri http://hdl.handle.net/10251/54436
dc.description.abstract Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four statistical interpolation methods for recovering these missing traces are compared in this paper: Kriging, Wiener structures, Splines and the expectation assuming an independent component analyzers mixture model (E-ICAMM). Kriging is an adaptation to the spatial context of the linear least mean squared error estimator. Wiener structures improve the linear estimator by including a nonlinear scalar function. Splines are a commonly used method to interpolate GPR traces. This consists of piecewise-defined polynomial curves that are smooth at the connections (or knots) between pieces. E-ICAMM is a new method proposed in this paper. E-ICAMM consists of computing the optimum nonlinear estimator (the conditional mean) assuming a non-Gaussian mixture model for the joint probability density in the observation space. The proposed methods were tested on a set of simulated data and a set of real data, and four performance indicators were computed. Real data were obtained by GPR inspection of two replicas of historical walls. Results show the superiority of E-ICAMM in comparison with the other three methods in the application of reconstructing incomplete B-scans. es_ES
dc.description.sponsorship This research was supported by Universitat Politecnica de Valencia (Vice-Rectorate for Research, Innovation and Transfer) under Grant SP20120646; Generalitat Valenciana under Grants PROMETEOII/2014/032, GV/2014/034 (Emergent Research Groups), and ISIC/2012/006; and the Spanish Administration and European Union FEDER Programme under Grant TEC2011-23403. en_EN
dc.language Inglés es_ES
dc.publisher MDPI es_ES
dc.relation.ispartof Remote Sensing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject GPR es_ES
dc.subject Independent component analysis es_ES
dc.subject Interpolation es_ES
dc.subject Missing data es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/rs6087546
dc.relation.projectID info:eu-repo/grantAgreement/UPV//SP20120646/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2014%2F032/ES/TÉCNICAS AVANZADAS DE FUSIÓN EN TRATAMIENTO DE SEÑALES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GV%2F2014%2F034/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//ISIC%2F2012%2F006/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TEC2011-23403/ES/ALGORITMOS PARA EL ANALISIS DE MODALIDAD DE SEÑAL: APLICACION EN EL PROCESADO AVANZADO DE SEÑALES ACUSTICAS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Safont Armero, G.; Salazar Afanador, A.; Rodriguez, A.; Vergara Domínguez, L. (2014). On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods. Remote Sensing. 6(8):7546-7565. https://doi.org/10.3390/rs6087546 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.3390/rs6087546 es_ES
dc.description.upvformatpinicio 7546 es_ES
dc.description.upvformatpfin 7565 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 6 es_ES
dc.description.issue 8 es_ES
dc.relation.senia 278545 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.description.references Le Bastard, C., Baltazart, V., Yide Wang, & Saillard, J. (2007). Thin-Pavement Thickness Estimation Using GPR With High-Resolution and Superresolution Methods. IEEE Transactions on Geoscience and Remote Sensing, 45(8), 2511-2519. doi:10.1109/tgrs.2007.900982 es_ES
dc.description.references Schafer, R. W., & Rabiner, L. R. (1973). A digital signal processing approach to interpolation. Proceedings of the IEEE, 61(6), 692-702. doi:10.1109/proc.1973.9150 es_ES
dc.description.references Salazar, A., Vergara, L., Serrano, A., & Igual, J. (2010). A general procedure for learning mixtures of independent component analyzers. Pattern Recognition, 43(1), 69-85. doi:10.1016/j.patcog.2009.05.013 es_ES
dc.description.references Vincent, E., Gribonval, R., & Fevotte, C. (2006). Performance measurement in blind audio source separation. IEEE Transactions on Audio, Speech and Language Processing, 14(4), 1462-1469. doi:10.1109/tsa.2005.858005 es_ES
dc.description.references Kullback, S., & Leibler, R. A. (1951). On Information and Sufficiency. The Annals of Mathematical Statistics, 22(1), 79-86. doi:10.1214/aoms/1177729694 es_ES
dc.description.references Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, 13(4), 600-612. doi:10.1109/tip.2003.819861 es_ES
dc.description.references Raghavan, R. S. (1991). A model for spatially correlated radar clutter. IEEE Transactions on Aerospace and Electronic Systems, 27(2), 268-275. doi:10.1109/7.78302 es_ES
dc.description.references Hyvärinen, A., Hoyer, P. O., & Inki, M. (2001). Topographic Independent Component Analysis. Neural Computation, 13(7), 1527-1558. doi:10.1162/089976601750264992 es_ES
dc.description.references Salazar, A., Safont, G., & Vergara, L. (2011). Application of Independent Component Analysis for Evaluation of Ashlar Masonry Walls. Lecture Notes in Computer Science, 469-476. doi:10.1007/978-3-642-21498-1_59 es_ES


This item appears in the following Collection(s)

Show simple item record