Reconstruction Algorithm of Ultrasonic CT Based on Matching Pursuit

Iterative ultrasonic computed tomography (UCT) based on ray theory uses the initial straight line paths to iterate that will lead to error diffusion. In this paper, we focus on the application of industrial flaw detection via UCT, in which the material to be detected is often a collection of a background area and a small amount of defect areas. An effective two-step algorithm is developed to reduce the cumulative error in the image reconstruction. In the first step, a threshold-based method is designed to roughly distinguish defect fuzzy area from background area according to the differences between measured ray travel-times and calculated ray travel-times. In the second step, the Matching Pursuit (MP) is utilized to search defect cells more accurately. Furthermore, in each iteration boundary linear travel-time interpolation (BLTI), a new algorithm proposed by us recently, is applied as the forward algorithm to further reduce the cumulative error and the amount of calculation. Simulated results show that the proposed algorithm outperforms two other methods: SL+SIRT and LTI+SIRT.