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An improved Richardson-Lucy iterative algorithm for C-scan image restoration and inclusion size measurement.

Authors :
Chen, Dan
Xiao, Huifang
Xu, Jinwu
Source :
Ultrasonics. Jan2019, Vol. 91, p103-113. 11p.
Publication Year :
2019

Abstract

Highlights • An improved RL iterative algorithm is proposed to measure inclusion size. • The spectral characteristics of transducer are considered to calculate the PSF. • The function to determine the final iteration number is established and calibrated. • The inclusion size measured from the restored C-scan images is more accurate. Abstract The accuracy of measuring inclusion size in direct C-scan image of immersion ultrasonic testing is restricted by the lateral resolution of the focused transducer, even if a high frequency is used, and the blurred edge due to scattering of sound waves at inclusions. In this work, an improved image restoration method that is based on the Richardson-Lucy (RL) iterative algorithm is proposed, which is used to restore the C-scan image and improve the accuracy of inclusion size measurement in immersion ultrasonic testing. For the improved RL iterative algorithm, the point spread function (PSF) is derived based on the multi-Gaussian beam model and Kirchhoff approximation, which considers the propagation properties of sound waves at water-steel interface and the spectral characteristics of the transducer with high frequency. In order to determine the final iteration number, the relationship between final iteration number and size of the inclusion in the image is established by restoring the simulated C-scan image and further calibrated with size correction factor. The size correction factor considers the effect of sound attenuation and electro-mechanical transformation encountered in practical testing equipment. Experimental results show that the inclusion sizes measured in restored C-scan images agree well with the optical micrograph results, which prove the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0041624X
Volume :
91
Database :
Academic Search Index
Journal :
Ultrasonics
Publication Type :
Academic Journal
Accession number :
131590925
Full Text :
https://doi.org/10.1016/j.ultras.2018.07.021