针对单一的红外或被动毫米波图像在探测军事目标中存在的不足,提出一种基于拉普拉斯金字塔变换的融合方法。首先,对原始图像分别进行拉普拉斯金字塔分解;其次,取红外图像分解得到的顶层图像作为融合结果的顶层图像,其余层图像采用由红外和被动毫米波图像对应层像素绝对值取大的规则融合;最后,经拉普拉斯金字塔逆变换得到融合图像。实验仿真结果表明,该方法能有效的融合红外与被动毫米波图像中的重要信息,其融合结果较好的将军事目标和背景区分开,有助于改善复合探测器的目标识别能力并保持全天候工作。

In view of the problem that both infrared (IR) image and passive millimeter wave (PMMW) image have limitations in military target detection, a Laplacian pyramid transform-based fusion method was presented in this paper. First, s fusion method based on Laplacian pyramid decomposition was proposed; then, the top decomposed image of IR image was used as the top image of the fusion result and other images were fused by selecting their pixel with maximum absolute value on infrared and passive millimeter wave image corresponding to the layer. After that, the fusion image was obtained by taking the inverse Laplacian pyramid transform. The experiment indicates that the method can effectively fuse important information from IR and PMMW images. The fusion result can better distinguish military targets from the features, it helps to improve the identification ability of composite seeker and keeps it for all-weather operation.