介绍了一种通过提取红外与可见图像高频信息形成矢量模型的方法，该模型可用于可见和红外两种不同波段相同场景图像的配准。分析了红外与可见图像的共同特性，即边缘高频特性，并在作为模板的图像中提取这类高频信息。利用人工干预的方法形成矢量模型，该矢量模型可通过实时姿态信息进行实时三维变换，并重新投影为二维图形，据此可在另一图像中进行特征搜索，达到两者匹配的目的。利用实际数据进行了实验分析，结果显示，利用本文算法提取的矢量模型，经变换后能可靠地实现异源目标自动识别；实验证明此方法有效可行，并可推广应用于各种异源图像间的自动目标识别和配准处理。

This article proposes a construction method of vector model based on high frequency information of infrared and visible images, which can be applied to the image alignment between different wave bands(visible and infrared) to the same scene. First, the high frequency characteristic, that is a common characteristic of infrared and visibility images, is analyzed, and it is picked up from a model image. A vector model is constructed by manual interposing. Then, the vector model is performed a 3D transform by the real-time attitude information, and is projected into a 2D graph again, which can be used to carry out the characteristic searching, and achieve the image matching. Finally, matching experiments are performed, and the vector model after transform can complete the image target automatic recognition for different sources. The theoretical analysis and experiment results prove the efficiency and feasibility of this method, and show it popular to all kinds of image alignments that come from different image sources.