基于改进粒子群优化的电容层析成像图像重建算法

Landweber电容层析成像ECT图像重建算法与粒子群优化算法PSO结合后能够进一步提高成像质量，但标准粒子群优化算法用于图像重建优化时存在陷入局部最优的现象。针对该问题，提出一种基于改进粒子群优化结合Landweber算法的电容层析成像图像重建算法。新算法在Landweber算法的基础上加入改进的惯性权值指数衰减粒子群优化策略，通过增加以指数规律衰减的粒子速度更新公式的约束因子，以保证算法在开始阶段具有较强的全局寻优能力，而在后期具有较强的局部寻优能力，从而实现对Landweber算法初始重建结果的进一步优化，以提高重建图像的质量。为验证新算法的有效性，选取较典型的LBP、改进Tikhonov迭代算法及Landweber图像重建算法，完成了ECT图像重建的对比实验。仿真结果表明，相对于其他算法，对于常见的几种流型，新算法在重建图像的主观及客观质量方面均有明显提高。

An image reconstruction algorithm for electrical capacitance tomography images based on improved particle swarm optimization

The Landweber image reconstruction algorithm for electrical capacitance tomography (ECT) images combining with the particle swarm optimization (PSO) can improve image quality. However, the PSO is easy to fall into local optimum when it is used for image reconstruction. Aiming at the problem, we propose an image reconstruction algorithm based on the improved PSO and Landweber algorithm. The new algorithm adds the PSO with exponentially decayed inertial weights，and adds the exponentially decayed restraint factors in particle speed updating formula, so that the algorithm has strong global search ability in prophase and strong local search ability in later stage, which further optimizes the initial reconstruction result of the Landweber algorithm to improve the quality of reconstructed images. We compare the ECT image reconstruction results of our algorithm with those of the typical LBP, the improved Tikhonov iterative algorithm and Landweber image reconstruction algorithm, and the comparison results verify the proposal’s effectiveness. Experimental results also show that the new algorithm outperforms the other algorithms in terms of subjective and objective qualities of reconstructed images.