双色中波红外图像差异特征驱动的融合模型

A Fusion Model Driven by Discrepant Features Based on Dual-color MWIR Images

针对图像融合中不能对未知图像自适应地找到最佳融合规则的问题,本文以双色中波红外图像为例,提出了一种差异特征驱动的融合模型。该模型首先在选定最佳融合评价指标的基础上,找到与融合规则相对应的图像特征,然后利用可能性理论构造图像特征分布的隶属度函数,建立差异特征与融合规则的映射关系,进而构建差异特征驱动的融合模型。实验结果表明,该模型与传统融合方法相比较,在主观认知上更能反映真实场景的信息,在客观评价中约有95%的指标参数优于其他方法。

In order to overcome the difficulty that unknown images can not find best fusion rules adaptively, a new fusion model driven by discrepant features is presented based on dual-color MWIR images. The model firstly finds best image features corresponding with fusion rules on the basis of selecting best fusion evaluation index. Then it uses possibility theory to construct membership function describing the distribution of image features, and establish mapping relationship between discrepant features and fusion rules. Finally, a fusion model driven by discrepant features is established. The experiment results show this model can reflect the true scene better in subjective perception and about 95% of index parameter is superior to others in objective evaluation.