针对红外偏振和光强图像现有融合算法无法随着图像差异特征的变化而优化选择的问题，提出了图像差异特征和融合算法的集值映射关系的建立方法。通过图像差异特征的分析与提取构建了差异特征集，将典型融合算法构建为融合算法集，利用数据包络分析法计算每个差异特征对各融合算法的融合有效度并构造融合有效度分布，通过对多组图像的融合有效度分布合成，建立差异特征与融合算法的集值映射关系。实验证明，所建立的集值映射关系可以优化选择融合算法，将互补性强的差异特征有效融合。

To solve the problem that infrared polarization and intensity image fusion algorithm is not optimal selection along with the change of difference characteristics, a method of establishing the set-valued mapping between difference characteristics set and fusion algorithms set was presented. Different characteristics set was formed with difference characteristics which was obtained by the analysis and extraction of image characteristics, and fusion algorithm set consisted of typical fusion algorithms. Fusion effective measure of each characteristic corresponding to fusion algorithms was calculated by data envelopment analysis and then constructed to be a distribution. Multi-group fusion effective measure distributions were synthesized in order to establish the set-valued mapping of difference characteristics and fusion algorithms set. Experimental results show that the set-valued mapping can select the optimal fusion algorithm, and have the highly complementary characteristics fused effectively.