Feasibility Study for Application of Total-Variation-Based Noise-Removal Algorithm with 450-kVp High-Energy Industrial Computed-Tomography Imaging System for Non-destructive Testing
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Several important technological trends for the detection of faults in the internal structure of a material utilize industrial computed-tomography (CT) X-ray imaging systems in non-destructive testing (NDT). In this system, the total-variation-(TV)-based noise-removal algorithm is a powerful method for denoising with a high edge-information preservation. In this study, we confirm the application feasibility of the TV-based noise-removal algorithm with an established 450-kVp high-energy industrial CT imaging system for NDT. The results obtained using two phantoms (SEDENTEX cone-beam CT image-quality phantom and pressure-head phantom) with our established imaging system reveal excellent normalized noise power spectrum, contrast–to–noise ratio, and coefficient of variation of the images obtained using the TV-based noise-removal algorithm. Therefore, this study reveals that the TV-based noise-removal algorithm can improve the noise characteristics in an industrial CT imaging system for NDT.
KeywordsHigh-energy industrial computed-tomography imaging system Non-destructive testing Total-variation-based noise-removal algorithm Image-quality evaluation
This research was supported by the National Research Foundation of Korea (NRF-2016R1D1A1B03930357).
- 6.Kim SH, Seo K, Kang SH, Bae S, Kwak H, Hong JW, Hwang Y, Kang SM, Choi HR, Kim GY, Lee Y (2017) Study on feasiblity for artificial intelligence (AI) noise reduction algorithm with various parameters in pediatric abdominal radio-magnetic computed tomography (CT). J Magn 22:570–578CrossRefGoogle Scholar
- 8.Lee D, Kim YS, Choi S, Lee H, Choi S, Kim HJ (2016) A feasibility study for anatomical noise reduction in dual-energy chest digital tomosynthesis. J. Instrum 11. https://doi.org/10.1088/1748-0221/11/01/P01016
- 10.Kwak HJ, Lee SJ, Lee Y, Lee DH (2018) Quantitative study of total variation (TV) noise reduction algorithm with chest X-ray imaging. J. Instrum. 13. https://doi.org/10.1088/1748-0221/13/01/T01006
- 12.Dongmin L, Lijuan Z (2011) Study on image denoising method based on an adaptive total variation model. TMEE:2270–2273Google Scholar