电容层析成像图像重建的总变差正则化算法

Total variation regularization algorithm for electrical capacitance tomography

针对电容层析成像(ECT)逆问题解的不适定性,本文提出一种基于总变差(total variation,TV)正则化的图像重建算法。同传统的2范数Tikhonov正则化方法相比,该算法(基于1范数正则化)不仅保证了逆问题求解的稳定性,而且提高了对介质非连续分布的区域成像的分辨能力,具有良好的保边缘性。仿真及实验结果表明,该算法在重建图像质量和重建速度两方面均具有优势。

To solve the ill-posed problem in electrical capacitance tomography （ECT）, a new image reconstruction algorithm based on total variation （TV） regularization is proposed. Compared with conventional L^2 Tikhonov regularization, this algorithm （based on L^1 regularization） not only stabilizes the reconstruction, but also enhances the resolution of the reconstruction image in areas with discontinuous medium distribution. It possesses good edge-preserving property. Both simulation and experimental results show that this algorithm has advantages in terms of resolution and real-time performance.