基于阵列旋转和改进证据理论的平面EMT图像融合算法

Image fusion algorithm of planar electromagnetic tomography based on array rotation and improved evidence theory

为了提高平面电磁层析成像(EMT)重建图像的质量,本文提出了一种阵列旋转和改进D-S证据理论相结合的平面EMT图像融合算法。首次将传感器阵列旋转应用于平面EMT领域,提高独立测量值个数,并利用旋转阵列的测量信息实现EMT图像融合。针对Dempster规则在处理冲突证据上存在不足的问题进行改进,利用数据聚类获取自适应阈值设置冲突和不冲突两种证据,分别对应不同的融合规则。仿真研究了旋转次数和成像效果之间的关系,利用不同旋转角度的信息和改进D-S证据理论进行图像融合,有效去除图像伪影,提高图像质量。设计了8线圈平面电磁传感器,并应用于铝板缺陷检测,结果验证了方法的有效性。新方法较传统方法的图像相对误差下降17.0%,相关系数提升22.7%。

To improve the quality of images reconstructed by planar electromagnetic tomography(EMT), a planar EMT image fusion algorithm is proposed, which is based on array rotation and improved evidence theory. For the first time, the sensor array rotation is applied to the field of planar EMT to increase the number of independent measurement. The measurement information of different rotation angles are used to achieve EMT image fusion. To address the problem that Dempster′s rule is insufficient in dealing with conflicting evidence, the data are clustered for all evidences to be fused to obtain an adaptive threshold. According to this threshold, all evidences are divided into two types, which are conflicting and non-conflicting. The different fusion rules are applied separately. The relationship between the number of rotation and the imaging effect is studied by simulation. Based on the array rotation and an improved D-S evidence theory, the artifacts are removed. The planar electromagnetic sensor with eight coils is developed. The aluminum plate fake detection shows the algorithm is effective. The relative image error of new method is reduced by 17.0% and the correlation coefficient is increased by 22.7% compared with traditional method.