ITERATIVE FILTERING RECONSTRUCTION ALGORITHM FOR GAMMA COMPUTERIZED TOMOGRAPHY: APPLICATION TO TWO-PHASE FLOW VISUALIZATION

Abstract

Considering the influence of the limited measurement data on the effectiveness of the image reconstruction algorithms in industrial multiphase flow tomography, an iterative filtering reconstruction algorithm is proposed by redefining inverse problem in this article. In order to improve the image quality in iterative reconstruction algorithm, Wiener filter and soft-threshold algorithm are employed as constraints for the reconstructed image. The developed algorithm is applied to gamma-CT based two-phase flow measurements, both simulated and experimental. The results demonstrate that the proposed method cannot only realize the flow regime identification on horizontal pipe, but also improve the iterative reconstruction process, i.e., the reconstructed image quality is enhanced and the iteration number is reduced.

Keywords:

• computerized tomography (CT)
• image reconstruction algorithm
• two-phase flow

ACKNOWLEDGMENT

This work was supported by the National Natural Science Foundation of China (Grant Nos. 60820106002, 60532020, and 60672170).