| Image Reconstruction Using a Genetic Algorithm for Electrical Capacitance Tomography |
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| 作者姓名： | 牟昌华 彭黎辉 姚丹亚 萧德云 |
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| 作者单位： | Department of Automation, Tsinghua University, Beijing 100084, China |
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| 基金项目： | Supported by the National Natural Science Foundation of China （No. 60204003） and the National High-Tech Research and Development （863） Program of China （No. 2001AA413210） |
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| 摘 要： | Electrical capacitance tomography （ECT） has been used for more than a decade for imaging dielectric processes. However, because of its ill-posedness and non-linearity, ECT image reconstruction has always been a challenge. A new genetic algorithm （GA） developed for ECT image reconstruction uses initial results from a linear back-projection, which is widely used for ECT image reconstruction to optimize the threshold and the maximum and minimum gray values for the image. The procedure avoids optimizing the gray values pixel by pixel and significantly reduces the search space dimension. Both simulations and static experimental results show that the method is efficient and capable of reconstructing high quality images. Evaluation criteria show that the GA-based method has smaller image error and greater correlation coefficients. In addition, the GA-based method converges quickly with a small number of iterations.
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| 关 键 词： | 电容断层摄影术 图象重建 遗传算法 图象处理 |
| 收稿时间： | 2004-03-16 |
| 修稿时间： | 2004-03-162004-06-08 |
Image Reconstruction Using a Genetic Algorithm for Electrical Capacitance Tomography |
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| Changhua Mou, , Lihui Peng, ý໎, Danya Yao, Úê,Deyun Xiao, &#x;û.Image Reconstruction Using a Genetic Algorithm for Electrical Capacitance Tomography[J].Tsinghua Science and Technology,2005,10(5):587-592. |
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| Authors: | Changhua Mou Lihui Peng ý໎ Danya Yao Úê Deyun Xiao &#x;û |
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| Institution: | Department of Automation, Tsinghua University, Beijing 100084, China |
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| Abstract: | Electrical capacitance tomography (ECT) has been used for more than a decade for imaging dielectric processes. However, because of its ill-posedness and non-linearity, ECT image reconstruction has always been a challenge. A new genetic algorithm (GA) developed for ECT image reconstruction uses initial results from a linear back-projection, which is widely used for ECT image reconstruction to optimize the threshold and the maximum and minimum gray values for the image. The procedure avoids optimizing the gray values pixel by pixel and significantly reduces the search space dimension. Both simulations and static experimental results show that the method is efficient and capable of reconstructing high quality images. Evaluation criteria show that the GA-based method has smaller image error and greater correlation coefficients. In addition, the GA-based method converges quickly with a small number of iterations. |
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| Keywords: | electrical capacitance tomography image reconstruction genetic algorithm |
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