针对红外与可见光的融合图像存在对比度低、场景细节信息不清晰的问题，提出基于整体变分的红外和可见光图像融合方法。该方法将每次迭代后的融合图像分别与可见光和红外图像进行差分运算，作为整体变分模型的正则项和保真项。同时，引入关于红外图像的非增扩散函数来引导扩散，抑制红外图像边缘信息的平滑，从而把图像融合问题转化为图像去噪问题，最终转化为一个泛函求极值问题。实验结果从视觉质量及客观评价上验证了该方法的有效性。

Aiming at the problems of low contrast and unclear scene details in infrared and visible image fusion, an infrared and visible image fusion method based on total variation is proposed. In this method, the difference between the fusion image after each iteration and the visible and infrared images is used as the regular and fidelity terms of the total variational model. At the same time, a non-incremental diffusion function about infrared images is introduced to guide the diffusion and suppress the smoothness of the edge information of the infrared images, so that the image fusion problem can be transformed into an image denoising problem, and finally it is transformed into a functional problem of finding extreme values. The experimental results verify the effectiveness of the method from visual quality and objective evaluation.