维数差异对模糊积分融合多FasART网络影响的研究

The Influences of Different Feature Dimension on Multi-FasART Networks Fusion Based on Fuzzy Integral

基于软决策的并行分布式融合系统能融合不同类型的特征,且最终决策结果与前期决策器输出的数值大小相关.当不同类型矢量的维数不等时,维数差异是否对最终融合决策有影响对设计融合算法和分类器的选择具有重要意义.本文分析了维数差异对模糊积分融合多FasART网络算法的影响原因,提出了解决办法,用遥感图像的光谱和纹理特征进行了融合实验,结果表明维数差异对该算法有影响.模糊积分融合多FasART网络是一种典型的基于软决策的并行分布式融合决策系统的算法,因此,基于上述融合系统的算法存在维数差异问题.

The parallel-distributed fusion system based on soft-decision can fuse the different feature class, and the fusion result is correlatiw; to these output of classifiers, When the vector dimension to different classifiers isn＇t equal, whether the dimension difference affects the last result, it＇s important to design algorithm and select classifier in the fusion system, To the system of fuzzy integral fusion multi-FasART networks, this paper analyses the causation of dimension difference influence, presents a way to settle the problem. Experimenting with spectrum and texture feature of remote sensing image, the results show that the dimension difference has influences on the fusion algorithm. The fuzzy integral fuse multi-FasART networks that is a typical algorithm of paralleldistributed fusion system based on soft-decision, so algorithms based on this fusion system have the problem of dimension difference.