Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l1 regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan—about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR).
Abstract-Ultrasound testing techniques, either nondestructive (NDT) or medical, suffer from spatial signal attenuation, where equivalent scatterers at different distances from the transducer will display different signal amplitudes. If not corrected, these differences may lead to erroneously interpretation.In NDT, Time Corrected Gain (TCG) compensates for spatial attenuation by increasing input gain according to the expected attenuation. Because TCG does not consider noise, signals coming from far scatterers are highly amplified, and so is noise. Wiener filter, on the other hand, deal with noise optimally, but does not compensate for spatial attenuation.In this paper, we propose an Adaptive TCG that combines the amplitude correction of the TCG with the optimality of the Wiener filter. We present simulations to evaluate the robustness of the proposed technique, as well as real-word results showing the the proposed method is superior to both Wiener filter and classical TCG independently.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.