Denoising method of X-ray phase contrast DR image for TRISO-coated fuel particles--颗粒学报PARTICUOLOGY

Yang, M., Zhang, J., Meng, F., Song, S.-J., Li, X., Liu, W., & Wei, D. (2013). Denoising method of X-ray phase contrast DR image for TRISO-coated fuel particles. Particuology, 11(6), 695–702. https://doi.org/10.1016/j.partic.2012.12.011

Denoising method of X-ray phase contrast DR image for TRISO-coated fuel particles

Min Yang ^a *, Jianhai Zhang ^b, Fanyong Meng ^c, Sung-Jin Song ^b *, Xingdong Li ^d, Wenli Liu ^d, Dongbo Wei ^a

a School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
b School of Mechanical Engineering, Sungkyunkwan University, 300 Chunchun-dong, Jangan-gu 440-746, South Korea
c State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
d National Institute of Metrology, Beijing 100013, China

10.1016/j.partic.2012.12.011

Volume 11, Issue 6, December 2013, Pages 695-702

Received 13 June 2012, Revised 18 October 2012, Accepted 1 December 2012, Available online 6 June 2013.

E-mail: yangminbuaa@163.com; sjsong@skku.edu

Highlights

• Modified P–M method possesses merits of P–M model and non-local means model.

• Modified P–M method was used to denoise X-ray phase contrast images of TRISO-coated fuel particles.

• The processed images exhibited continuous contours without noisy points or fake segments.

Abstract

TRISO (tristructural-isotropic) fuel is a type of micro fuel particles used in high-temperature gas-cooled reactors (HTGRs). Among the quality evaluation methods for such particles, in-line phase contrast imaging technique (PCI) is more feasible for nondestructive measurement. Due to imaging hardware limitations, high noise level is a distinct feature of PCI images, and as a result, the dimensional measurement accuracy of TRISO-coated fuel particles decreases. Therefore, we propose an improved denoising hybrid model named as NL P–M model which introduces non-local theory and retains the merits of the Perona–Malik (P–M) model. The improved model is applied to numerical simulation and practical PCI images. Quantitative analysis proves that this new anisotropic diffusion model can preserve edge or texture information effectively, while ruling out noise and distinctly decreasing staircasing artifacts. Especially during the process of coating layer thickness measurement, the NL P–M model makes it easy to obtain continuous contours without noisy points or fake contour segments, thus enhancing the measurement accuracy. To address calculation complexity, a graphic processing unit (GPU) is adopted to realize the acceleration of the NL P–M denoising.

Graphical abstract

Keywords

TRISO-coated fuel particle; X-ray phase contrast imaging; Image denoising; Partial differential equation; Non-local means

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