Far-Focused Pixel-Based Imaging Algorithm for Multi-Layered Media Defect Defection and its GPU Implementation

When applied to multilayer media inspection, ultrasonic phased array technology often faces challenges with low signal-to-noise ratio (SNR) in echo signals. In this study, an improved far-focused pixel-based (FPB) imaging method for detecting defects in multilayer media is proposed. First, the shortest path searching method is used to correct the time delay calculation. Second, the base-band delay multiply and sum (BB-DMAS) beamforming is utilized to replace traditional delay and sum (DAS) beamforming to fully exploit the spatial coherence of the captured data in the receiving and transmitting apertures, thereby effectively suppressing the noise and clutter in the signal. Finally, the proposed algorithm is implemented on graphics processing unit (GPU) to improve imaging efficiency. The experimental results show that the proposed method improves the average SNR by 55.0% and reduces the average resolution by 28.2% compared to DAS-FPB, while achieving a GPU-based acceleration ratio exceeding 100 times that of CPU computation.