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Data set reduction for ultrasonic TFM imaging using the effective aperture approach and virtual sources

Abstract : The Total Focusing Method (TFM) is sometimes described in the literature as the "gold standard" compared to conventional imaging techniques. TFM is an algorithm that usually post-processes the full matrix of data, also called Full Matrix Capture (FMC). Real-time piloting of such an algorithm is heavy due to the large number of firings (N for a N-element array) and the large number of signals (N×N) to process that tend to decrease the frame rate and, consequently, the inspection speed. This problem can be overcome to some extent if only a few elements are activated which is equivalent to using a sparse array in transmit. The PSF (Point Spread Function) provides information about important images parameters: lateral resolution and contrast. An algorithm based on PSF optimization is proposed to obtain both the number of transmit pulses and the location of the active elements. However, reducing the number of emissions induces a loss in transmitted energy. To compensate it, each transmit pulse is carried out by multiple transmit elements that emulate a single "virtual" element. The method is evaluated on experimental data in a realistic NDT configuration by comparison of images obtained with FMC and SMC (Sparse Matrix Capture) acquisitions.
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https://hal-cea.archives-ouvertes.fr/cea-01820757
Contributor : Léna Le Roy <>
Submitted on : Friday, June 22, 2018 - 9:50:13 AM
Last modification on : Saturday, September 26, 2020 - 11:44:09 PM

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S. Bannouf, S. Robert, O. Casula, C. Prada. Data set reduction for ultrasonic TFM imaging using the effective aperture approach and virtual sources. Journal of Physics: Conference Series, 2013, 457, ⟨10.1088/1742-6596/457/1/012007⟩. ⟨cea-01820757⟩

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