Data reconstruction for sparse scans and arrays

Authors: Thomas Heckel (Bundesanstalt für Materialforschung und -prüfung) , Rainer Boehm (Bundesanstalt für Materialforschung und -prüfung) , Arno Volker (TNO) , Paul van Neer (TNO)

  • Data reconstruction for sparse scans and arrays


    Data reconstruction for sparse scans and arrays

    Authors: , , ,


Using Matrix Phased Probes and manipulator steered scans allow to get best data basis for synthetic aperture focusing technique (SAFT) or similar total focusing methods (TFM). The drawbacks are the high amount concerning the data volume and high costs of the hardware capable of recording many signals at the same time. This paper explores how well data can be reconstructed in a sparsely sampled data sets where the sampling theorem is not fulfilled. The objective is to quantify the degradation of an image due to sparse sampling. For future array design, this insight helps to make a better trade-off between array aperture and sampling density. We follow two strategies to reach the goal. The first one is to optimize the geometric distribution of the matrix elements and/or the scan area, and the second is the reconstruction of omitted signals e.g. to increase the quality of a subsequent imaging.

How to Cite:

Heckel, T., Boehm, R., Volker, A. & van Neer, P., (2019) “Data reconstruction for sparse scans and arrays”, Review of Progress in Quantitative Nondestructive Evaluation .

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Published on
03 Dec 2019
Peer Reviewed