Image reconstruction algorithm for electrical resistance tomography (ERT) based on regularized general inverse method

Ying Wei; Yu Haibin; Shi Wang

doi:10.1117/12.477143

31 July 2002 Image reconstruction algorithm for electrical resistance tomography (ERT) based on regularized general inverse method

Ying Wei, Yu Haibin, Shi Wang

Author Affiliations +

Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477143
Event: Second International Conference on Image and Graphics, 2002, Hefei, China

Abstract

Three kinds of image reconstruct algorithms for Electrical Resistance Tomography (ERT) has been researched, and a new ERT reconstruct algorithm-Regularized general inverse(RGI) ERT reconstruct algorithm is proposed, which is based on linearity ERT forward problem, and makes use of general inverse to confirm the minimum norm error solution of ERT inverse problem. Meanwhile, adopting regularized method to stabilized the numerical value. The observation operator is set up by multiple linear regression method. Three restriction conditions is brought to bear the optimum stabilization solution. The simulation result shows that reconstructed image can reflect the truth medium distribution in the field truly including different complex distributions. After filtering the images by unite bound for the same medium distribution, the average of CSIE image reconstructed by linear back project algorithm, sensitivity coefficient algorithm and regularized general inverse algorithm is 12%, 9% and 6% respectively. The result shows that the image quality reconstructed by regularized general inverse algorithm is improved in evidence than that of the other two algorithms. The calculate amount of regularized general inverse algorithm is same as one step sensitivity coefficient algorithm, the speed of reconstruction is fast.

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Ying Wei, Yu Haibin, and Shi Wang "Image reconstruction algorithm for electrical resistance tomography (ERT) based on regularized general inverse method", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477143

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