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  • 标题:A Novel Image Reconstruction Algorithm Based on Compressed Sensing for Electrical Capacitance Tomography
  • 本地全文:下载
  • 作者:Chen Deyun ; Li Zhiqiang ; Gao Ming
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2013
  • 卷号:6
  • 期号:4
  • 出版社:SERSC
  • 摘要:According to the image reconstruction accuracy influenced by the “soft field” nature and the limited projection data in electrical capacitance tomography, based on the working principle of the electrical capacitance tomography system, a Novel image reconstruction algorithm based on compressed sensing is proposed in the paper. The method based on ART (algebra reconstruction technique) organically combines the gradient sparse of image and ART, and reduces the norm of image gradient with full-variational method, and improves the accuracy and speed of image reconstruction. Experimental results and simulation data indicate that the imaging accuracy is markedly improved, and the image is closed to the prototype. This new algorithm presents a feasible and effective way to research on image reconstruction algorithm for Electrical Capacitance Tomography System
  • 关键词:electrical capacitance tomography; image reconstruction; ART algorithm; compressed sensing
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