针对红外强度图和红外偏振度图融合问题，提出了基于烟花算法优化空域加权平均法的智能图像融合方法。在构建优化问题模型的基础上，确定了烟花算法的边界条件。通过引入相对熵权值建立了基于综合相对熵的适应度函数。最后，与6种典型的传统融合方法在“ground”、“truck”、“car”3组红外强度和偏振度图像数据上进行了融合实验，对融合结果进行了客观评价和视觉效果评价。实验结果表明：所提方法可以有效实现红外强度图和红外偏振度图的融合，较好保留了红外强度和红外偏振特征。综合视觉效果和客观评价结果，在相对熵、总结构相似性、总互信息指标上优于比较算法。

Aiming at the fusion of infrared intensity-polarization image, an intelligent fusion method based on spatially weighted averaging method optimized by fireworks algorithm is proposed. Based on the optimization model, the boundary conditions of fireworks algorithm are determined. The fitness function based on comprehensive relative-entropy is established by introducing the weight of relative-entropy. Finally, the fusion experiments on three groups of infrared image “ground”, “truck” and “car” are carried out with six typical traditional fusion methods, and the fusion results are evaluated objectively and compared with the visual effects. The experimental results show that the proposed method can effectively achieve the fusion of infrared intensity map and polarization map, and retain the infrared intensity and polarization characteristics. Combining the visual effect and objective evaluation results, the method in this paper is superior to the comparison algorithm in relative-entropy, similarity of summary structure and total mutual information index.