Ultrasonic data for nondestructive testing is traditionally processed with algorithms based on the time-domain delay-and-sum approach. However, this method requires interpolation of the raw ultrasonic data, and processing algorithms based on the delay-and-sum technique are commonly implemented with either nearest-neighbor or linear interpolation. In this paper, we evaluate image reconstruction and execution time for three delay-and-sum-based algorithms employing nearest-neighbor and linear interpolation, at sampling rates of 20 MHz and 125 Mhz for the raw ultrasonic signals. We evaluate the Synthetic Aperture Focusing Technique (SAFT) for the post-processing of ultrasonic data acquired from sweeping inspections with monostatic transducers, the Total Focusing Method (TFM) for the post-processing of data acquired from a full-matrix capture with a linear array and the Coherent Plane-Wave Compounding (CPWC) algorithm for the post-processing of data acquired via plane-wave imaging. Using simulated ultrasonic data obtained with the CIVA software, we find that the SAFT algorithm is the most sensitive to the interpolation method when the sampling rate is 20 MHz. In this case, a 2 dB loss in contrast-to-noise ratio is obtained when comparing the image reconstructed using nearest-neighbor interpolation to the image obtained with linear interpolation. The TFM and CPWC algorithms are less sensitive to the interpolation kernel regardless of the sampling rate. In addition, reconstruction with nearest-neighbor interpolation shows lower execution times. For an image with 200 x 200 pixels, execution time as reduced by a factor of two, whereas reconstruction of an image with 800 x 800 pixels attained a three-fold reduction in execution time.


Comparison of Nearest-Neighbor and Linear Interpolation for Time-Domain Ultrasonic Imaging

No proceedings papers in 2020. Video only.

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