关键词: 二维主成分分析, 特征融合, 弱小目标, 图像匹配

Abstract: From researching on the universal principle of feature fusion of image，a new algorithm was proposed which based on the 2 dimension principal component analyses（for short 2DPCA）.First，choose the multi-feature of target image which includes fractal feature，multi-direction and multi-scale gradient feature，local gray probability feature to construct a characteristic vector.Get a transforming matrix from using 2 dimension principal component analyses to the characteristic vector.And multiply the transforming matrix and characteristic vector to get a new syntheses feature.This syntheses feature is the feature from fusion.Simulation on image matching of small-weak target shows that this algorithm is more effective than conventional methods of matching based on gray and methods based on PCA，and has minor difference of time to the last method.

Key words: 2DPCA, feature fusion, small-weak target, image matching