Adaptive $L_{p}$ Regularization for Electrical Impedance Tomography
| Autor: | Huaxiang Wang, Ziqiang Cui, Shihong Yue, Jia Li, Mingliang Ding |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Physics
Pixel Linear programming 010401 analytical chemistry Field (mathematics) 01 natural sciences Regularization (mathematics) 0104 chemical sciences Range (mathematics) Applied mathematics Electrical and Electronic Engineering General frame Instrumentation Image resolution Electrical impedance tomography |
| Zdroj: | IEEE Sensors Journal. 19:12297-12305 |
| ISSN: | 2379-9153 1530-437X |
| DOI: | 10.1109/jsen.2019.2940070 |
| Popis: | Owing to its low cost, fast response, non-invasiveness, and non-radiation, electrical impedance tomography (EIT) has been applied to numerous fields. However, its spatial resolution is low due to the inherent ill-posed problem and the “soft field” effect. The $L_{p}$ regularization ( $0 ) is effective for overcoming these disadvantages, and efforts have been made to use regularization from the most popular $L_{2}$ to its variants $L_{1}$ and $ L_{1/2}$ . Nevertheless, $L_{p}$ regularization is generally difficult to be solved fast and efficiently, and the selection of p yielding the best result is also a problem. In this paper, an adaptive re-weighted (ARW) algorithm with a general frame is presented to solve the $L_{p}$ regularization for EIT, with p for each pixel determined adaptively in iterations. Experiments were carried out to validate the proposed algorithm. Results show that compared with other EIT algorithms, the ARW algorithm had a higher spatial resolution. Moreover, it can provide a wider range of selection for regularization parameter, which increases the practicality of the proposed algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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