针对红外和可见光图像融合算法中存在背景模糊和目标不清晰等问题，提出一种基于目标增强的红外与可见光图像融合算法。首先，利用均值滤波的方法获得透射率的粗估计，通过图像统计信息实现粗透射率的细化，依据大气散射模型实现红外图像的目标增强；然后，对目标增强的红外图像和可见光图像采用改进的Prewitt 算子进行边缘检测，并将检测结果二值化，对边缘部分采用基于二值信息的融合规则，对非边缘部分采用比值加权分析的融合规则。实验结果表明，采用基于目标增强的图像融合算法不仅能凸显红外图像的目标信息，还能尽可能多的保留可见光图像丰富的细节信息，具有更好的视觉效果和更高的客观质量评价指标。

To resolve the issue of blurred backgrounds and fuzzy targets in using the infrared and visible image fusion algorithm, this paper proposes a new method for image fusion based on target-enhancement. First, average filtering is used to obtain rough estimation of the transmission rate, which is refined by calculating the images’ statistical information. Further, a final target-enhanced infrared image is obtained using the atmospheric scattering model. Then, the edge of the target-enhanced infrared image and the visible image is detected and binarized using the improved Prewitt operator. The fusion rule based on binary information is used for the edge part, and the fusion rule based on the ratio weighting analysis is used for the non-edge part. Experimental results show that the image fusion algorithm based on target-enhancement not only highlights the target information of an infrared image, but also retains the detailed information of the visible image as much as possible. Additionally, the fused image has better visual effects and higher objective quality evaluation indexes.