Ultrasonic C-scan image restoration method using the Richardson-Lucy algorithm and a flaw measurement model

In ultrasonic imaging, blurred edges have a heavily negative impact on the accuracy of the flaw images. To improve ultrasonic C-scan image quality, this paper proposes a deconvolution-based ultrasonic C-scan image restoration method combining the Richardson-Lucy (RL) algorithm and a flaw measurement model. In order to implement an optimal restoration process, an ultrasonic C-scan imaging model is pre-sented and employed to simulate the C-scan images. By restoring the simulated images, a relationship between the optimal iteration number and the ratio of the flaw size to the sound wavelength is established. Furthermore, the equivalent sizes of the flaws are extracted from a flaw measurement model-based non-destructive approach and are used to calculate the optimal iteration number of the RL deconvolution algorithm. Finally, the experimental ultrasonic C-scan images are restored by using the RL iterative algorithm with the optimal iteration numbers, 1, 2, 6, and 14, respectively. The experi-mental results show that the flaw sizes, obtained by the 6 dB drop method in the original C-scan images, have errors larger than 26 %. After restoration, the maximum error of the flaw size in the C-scan image is only 10 % and the minimum is 2 %, indicating that the proposed restoration method effectively improves the accuracy of the ultrasonic C-scan imaging.(c) 2022 Elsevier Ltd. All rights reserved.