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

被引:18
作者
Chen, Dan [1 ,2 ]
Xiao, Huifang [1 ]
Xu, Jinwu [2 ]
机构
[1] Univ Sci & Technol Beijing, Sch Mech Engn, Beijing 100083, Peoples R China
[2] Univ Sci & Technol Beijing, Collaborat Innovat Ctr Steel Technol, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Inclusion size; C-scan image; Richardson-Lucy algorithm; Point spread function; Final iteration number; DECONVOLUTION;
D O I
10.1016/j.ultras.2018.07.021
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
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.
引用
收藏
页码:103 / 113
页数:11
相关论文
共 43 条
[1]   Characterization of Grain Size and Yield Strength in AISI 301 Stainless Steel Using Ultrasonic Attenuation Measurements [J].
Aghaie-Khafri, M. ;
Honarvar, F. ;
Zanganeh, S. .
JOURNAL OF NONDESTRUCTIVE EVALUATION, 2012, 31 (03) :191-196
[2]   Characterization of inclusions in clean steels: a review including the statistics of extremes methods [J].
Atkinson, HV ;
Shi, G .
PROGRESS IN MATERIALS SCIENCE, 2003, 48 (05) :457-520
[3]   A method for observing the three-dimensional morphologies of inclusions in steel [J].
Bao, Yan-ping ;
Wang, Min ;
Jiang, Wei .
INTERNATIONAL JOURNAL OF MINERALS METALLURGY AND MATERIALS, 2012, 19 (02) :111-115
[4]   Assessment of inclusion analysis via manual and automated SEM and total oxygen content of steel [J].
Bartosiaki, Bruna Goulart ;
Morales Pereira, Julio Anibal ;
Bielefeldt, Wagner Viana ;
Faria Vilela, Antonio Cezar .
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, 2015, 4 (03) :235-240
[5]   Scatterer size estimation in pulse-echo ultrasound using focused sources: Theoretical approximations and simulation analysis [J].
Bigelow, TA ;
O'Brien, WD .
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2004, 116 (01) :578-593
[6]   DIFFRACTION THEORY [J].
BOUWKAMP, CJ .
REPORTS ON PROGRESS IN PHYSICS, 1954, 17 :35-100
[7]  
CHATILLON S, 2003, AIP C P, V20, P93
[8]   A study on the inclusion sizing using immersion ultrasonic C-scan imaging [J].
Chen, D. ;
Xiao, H. F. ;
Li, M. ;
Xu, J. W. .
12TH INTERNATIONAL CONFERENCE ON DAMAGE ASSESSMENT OF STRUCTURES, 2017, 842
[9]   Compressive Deconvolution in Medical Ultrasound Imaging [J].
Chen, Zhouye ;
Basarab, Adrian ;
Kouame, Denis .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 35 (03) :728-737
[10]   Measurement of the point-spread function of a noisy imaging system [J].
Claxton, Christopher D. ;
Staunton, Richard C. .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2008, 25 (01) :159-170