Correcting X-ray CT ring artefacts via adaptive stripe removal and structure restoration

X-ray computed tomography (CT) is a crucial non-destructive testing technique that plays an essential role in fields such as biomedicine and industrial inspection. However, ring artefacts generated during imaging severely compromise the interpretation of image structures and the accuracy of quantitative analysis, thereby restricting the reliability of non-destructive testing. Existing single-step correction methods generally suffer from limitations including incomplete artefact removal, susceptibility to image structural damage, and excessive reliance on manual parameter tuning. This paper proposes a combined three-step ring artefact correction algorithm that integrates stripe detection, stripe correction, and structure restoration, maximising the preservation of the image’s original structural information and ensures the integrity of details required for non-destructive testing. Validation results based on simulated and experimental data demonstrate that the algorithm effectively eliminates complex and diverse ring artefacts. Compared with traditional algorithms, it offers advantages of broader applicability, lower risk of structural damage, and reduced probability of introducing additional artefacts. This study provides an integrated solution for ring artefact correction in X-ray CT non-destructive testing and holds promise for extension to a wider range of artefact removal tasks in non-destructive testing images, such as CT reconstructed slices.