光学
投影(关系代数)
迭代重建
物理
计算机科学
人工智能
算法
作者
Junyao Wang,YongNing Zou,Qian Qin,Zexin Liu,Ying Chen
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2025-05-28
卷期号:33 (12): 25415-25415
摘要
X-ray computed laminography (CL), a widely employed nondestructive testing technique, holds significant potential for detecting micro-faults in laminated structure thin-plate parts (LSTP). However, thin plate components frequently exceed the field of view (FOV) of CL systems due to detector size constraints, leading to truncation artifacts as X-rays fail to encompass the entire imaging target. While projection weighting algorithms have been proven effective in recovering high-quality reconstructions for local computed tomography (CT) scans, their applicability to CL reconstruction from truncated projections remains underexplored. This paper proposes a novel two-step weighted filtered back-projection (TS-FBP) algorithm for CL truncation reconstruction. The methodology integrates the FBP algorithm with a cosine-weighted projection scheme, addressing projection edge discontinuities through smooth truncation to meet FBP reconstruction requirements without modifying the original scanning geometry. Additionally, a post-filtering quadratic weighting mechanism is implemented for image intensity normalization. Comprehensive validation through numerical simulations and physical experiments demonstrates that the proposed approach achieves artifact-suppressed cross-sectional reconstruction with high computational efficiency, while guaranteeing sufficient quality.
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