Noise Reduction Method for Ultrasonic TOFD Image Based on Image Registration

被引:9
|
作者
Gao, Xiao-rong [1 ,2 ,3 ]
Shen, Yan [1 ,2 ,3 ]
Luo, Lin [1 ]
机构
[1] Southwest Jiaotong Univ, Photoelect Engn Inst, Chengdu 610031, Peoples R China
[2] Southwest Jiaotong Univ, NDT Res Ctr, Chengdu 610031, Peoples R China
[3] Southwest Jiaotong Univ, Olympus NDT Joint Lab Nondestruct Testing, Chengdu 610031, Peoples R China
关键词
Time of flight diffraction; Ultrasonic imaging; Image registration; Shift-and-add;
D O I
10.1007/s10921-013-0185-9
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Influenced by random noises from inhomogeneous material scattering and fluctuation of detected electric signals, the signal-to-noise ratio (SNR) of ultrasonic time-of-flight-diffraction (TOFD) image decreases significantly. For the noise reduction of TOFD images, several D-scanned TOFD images with different distribution of noise characteristics are obtained through repeating detection and slightly and randomly changing the probe's initial position each time. The registered images then are processed by shift-and-add (SAA) technique to reduce the noise level of the TOFD images. Besides, correlation image registration algorithm based on optimization method was established to avoid the shift of TOFD images due to slight change of probe's initial position. Noises in the registered images show stochastic behavior at the same position. In order to verify reliability of the algorithm, an experimental TOFD detection system for weld defects has been designed to acquire and experiment with TOFD images. The experiment results have been evaluated in terms of cross correlation coefficient, SNR and standard variance of images. The results show that the proposed method could effectively enhance SNR of TOFD images and improve the ability to identify weld defects of materials.
引用
收藏
页码:325 / 330
页数:6
相关论文
共 50 条
  • [31] Method of image registration based on differential equations
    Peize, Li
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (11) : 127 - 140
  • [32] Image registration method based on rigid dynamics
    Zhang, Jian-Wei
    Han, Guo-Qiang
    Chen, Yang-Zhi
    Wo, Yan
    PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 3776 - +
  • [33] Efficient image reduction for image registration with evolutionary algorithm
    Maslov, IV
    Gertner, I
    APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION V, 2002, 4787 : 198 - 209
  • [34] Noise reduction of image based on wavelet transform
    Wu, Jun-Qiang
    He, Kun
    Zhou, Ji-Liu
    Lang, Fang-Nian
    WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING, VOL 1 AND 2, 2006, : 947 - +
  • [35] Noise Reduction and Enhancement of Contour for Median Nerve Detection in Ultrasonic Image
    Katayama, Koutaro
    Shibata, Keiji
    Horita, Yuukou
    2017 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING APPLICATIONS (ICSIPA), 2017, : 341 - 344
  • [36] Image noise reduction algorithms using nonparametric method
    Woo, Ho-young
    Kim, Yeong-hwa
    KOREAN JOURNAL OF APPLIED STATISTICS, 2019, 32 (05) : 721 - 740
  • [37] A METHOD OF NOISE-REDUCTION ON IMAGE-PROCESSING
    INAMORI, S
    YAMAUCHI, S
    FUKUHARA, K
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 1993, 39 (04) : 801 - 805
  • [38] Analysis on noise reduction method for interferometric SAR image
    Tang, Z
    Li, JW
    Zhou, YQ
    IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, : 4243 - 4246
  • [39] Noise Reduction in DEXA Image based on System Noise Modeling
    Kwon, J. W.
    Cho, S. I.
    Ahn, Y. B.
    Ro, Y. M.
    2009 INTERNATIONAL CONFERENCE ON BIOMEDICAL AND PHARMACEUTICAL ENGINEERING, 2009, : 167 - +
  • [40] A method of image noise reduction based on multiwavelet transform and multiscale data fusion
    Zheng Wu
    Chen Jianxun
    2007 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS, VOLS 1 AND 2, 2007, : 236 - 239