Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (1): 111-116.doi: 10.3969/j.issn.1000-565X.2014.01.019

• Computer Science & Technology • Previous Articles     Next Articles

SoS Filter and Its Application to Industrial Ultrasound Imaging

Dai Guang- zhi1 Han Guo- qiang1 Lin Wei- yi2 OuYang Xian- yue3   

  1. 1.School of Computer Science and Engineering,South China University of Technology,Guangzhou 510006,Guangdong,China;2.School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China;3.Key Laboratory for Embedded and Network Computing of Hunan Province,Hunan University,Changsha 410082,Hunan,China
  • Received:2013-03-11 Revised:2013-09-30 Online:2014-01-25 Published:2013-12-01
  • Contact: 戴光智(1974-)，男，博士后，深圳职业技术学院副教授，主要从事超声无损检测以及压缩感知信号处理研究． E-mail:daiguangzhi@szpt.edu.cn
  • About author:戴光智(1974-)，男，博士后，深圳职业技术学院副教授，主要从事超声无损检测以及压缩感知信号处理研究．
  • Supported by:

    广东省自然科学基金资助项目(10451805501006279， S2011010004487);中国博士后科学基金资助项目(2012M511551)

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Abstract:

Although the FRI (Finite Rate of Innovation) model may be feasible in reducing the sampling data andsampling frequency of industrial ultrasound imaging systems,the existing FRI model cannot be well applied due tothe high frequency of reflected signals.In order to solve this problem,a new FRI acquisition method named Sum of Sinc (SoS) filter,which is very suitable for the processing of industrial ultrasound signals,is proposed on the basisof the FRI filter group.Afterwards，the necessary conditions for this method are deduced,and the structure of theSoS filter is presented.From the results of raw one- dimension ultrasound imaging data，the proposed method isfound to be effective and feasible.

Key words: signal processing, industrial ultrasound imaging, Sum of Sinc Filter, compressed sensing, finite rateof innovation, sampling data, sampling frequency