摘要
电容层析成像图像重建是一个典型的病态问题,它的解是不稳定的.为了对这个不适定问题进行求解,在分析电容层析成像基本原理的基础上,提出了一种自适应权重粒子群的电容层析成像边界灰度补偿算法.该算法通过引入粒子群的平均绝对速度与理想速度,自适应调整粒子群优化算法中的参数,对成像后图像边界周围的灰度进行补偿.数值实验结果表明,同线性反投影和共轭梯度算法相比,进行边界灰度补偿后的图像兼备成像质量高、边界均匀稳定等优点,为ECT图像重建算法的研究提供了一个新思路.
Electrical capacitance tomography（ECT） image reconstruction is a typical problem,and its solution is unstable.In order to solve this ill-posed problem,in the analysis of the basic principles of electrical capacitance tomography,a novel gray boundary compensation algorithm for electrical capacitance tomography system based on adaptive particle swarm weight is presented.The algorithm,through the introduction of the average absolute speed and the ideal speed in particle swarm,adaptively adjusts the parameters of particle swarm optimization algorithm and compensates for the gray border around the image.Experimental results and simulation data indicate that the compensated image of gray border can provide high quality images and favorable stabilization compared with LBP,conjugate gradient algorithms in simple flow pattern and this new algorithm presents a feasible and effective way to research an image reconstruction algorithm for Electrical Capacitance Tomography System.
出处
《哈尔滨理工大学学报》
CAS
北大核心
2010年第3期44-49,共6页
Journal of Harbin University of Science and Technology
基金
国家自然科学基金(60572153)
高等学校博士学科点专项科研基金(2008-2011)
黑龙江省自然科学基金(F200609)
中央高校基本科研业务费专项资金资助(DL09AB02)
东北林业大学大学生创新基金(091022559)
关键词
电容层析成像
图像重建
自适应粒子群
electrical capacitance tomography
image reconstruction
adaptive particle swarm
