用于电阻层析成像的快速自适应硬阈值迭代算法

A Fast Adaptive Iterative Hard Threshold Algorithm for Electrical Resistance Tomography

针对电阻层析成像技术图像重建具有严重病态性的问题,提出了一种稀疏重建算法——快速自适应硬阈值迭代算法,研究了噪声对该算法在电阻层析成像图像重建效果上的影响,并通过仿真和模型实验测试了该算法的性能.结果表明:一定强度范围内的噪声对硬阈值迭代算法、自适应硬阈值迭代算法和快速自适应硬阈值迭代算法的影响较小.快速自适应硬阈值迭代算法成像速度更快,且该算法重建图像的空间分辨率相对其他两种算法也有较大的提高.

In order to reduce the ill-posed problem of electrical resistance tomography,a new sparse reconstruction algorithm named fast adaptive iterative hard threshold algorithm was proposed. The performance of the algorithm was tested in simulation and model experiment. The effects of noise on the reconstructed results of this algorithm were also investigated. Results show that iterative hard threshold algorithm,adaptive iterative hard threshold algorithm and fast adaptive iterative hard threshold algorithm are robust to noise within low intensity range. The fast adaptive iterative hard threshold algorithm has better convergence speed and higher resolution than the other two algorithms.