Laser & Optoelectronics Progress, Volume. 58, Issue 12, 1210025(2021)
Electrical Capacitance Tomography Sensitivity Field Optimization Algorithm Based on Approximate L0 Norm
Aiming at the under-qualitative problem in solving the inverse problem of electrical capacitance tomography, a sparse regularization algorithm that approximates the L0 norm is introduced to obtain the sparse solution vector. An iterable sensitivity gradient optimization method of the sensitive field is proposed to address the imaging quality problem caused by the uneven sensitivity distribution of the sensitive field. This method uses the finite elements of the sensitive field as the core to divide the sensitive field into several regions and the data of sensitivity in the region around the core finite element is extracted for mean filtering. And the filtered data is returned to the core finite elements and used as the parameters in the next filtering area. Cyclic filtering can gradually reduce the sensitivity gradient between the center area and edge area of the sensitive field. The sensitivity gradient optimization method is combined with the approximate L0 algorithm to verify the feasibility of the proposed algorithm. The results show that compared with the traditional Landweber algorithm, the proposed algorithm reduces the relative error of a reconstructed image to 0.24 and the correlation coefficient to 0.91. The actual static experiment also proves the effectiveness of the proposed algorithm.
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Min Ma, Yifei Liu, Shixi Wang. Electrical Capacitance Tomography Sensitivity Field Optimization Algorithm Based on Approximate L0 Norm[J]. Laser & Optoelectronics Progress, 2021, 58(12): 1210025
Category: Image Processing
Received: Jul. 6, 2020
Accepted: Dec. 3, 2020
Published Online: Jun. 22, 2021
The Author Email: Ma Min (mm5739@163.com)