汽车夜间会车滥用远光灯会造成晕光现象，对逆向车辆司机的视野造成干扰，导致无法看清路况极易诱发交通事故。本文从视觉观察角度出发，利用可见光和红外图像成像特点的互补性，提出HSV 色彩空间变换结合小波变换的方法对图像进行融合，解决夜间行车晕光问题，提高行车安全性。通过对融合结果的主客观分析，本文算法有效消除了晕光，同时图像均值接近120，信息熵为7.1768，基本达到最佳视觉观察效果。

When cars pass each other at night, halation phenomena may result from the abuse of high-beam lights, which could affect the vision of approaching drivers, preventing them from obtaining clear traffic information and leading to traffic accidents. Using visual observations, we take advantage of the complementarity of visible and infrared imaging features, to propose a method of fusing two images using HSV color space transformation combined with a wavelet transform, thus solving the problem of driving at night and improving traffic safety. Subjective and objective analyses of the fusion results indicate that our algorithm effectively eliminates halos; the mean value of the resulting image is close to 120, and its information entropy is 7.1768, which achieves a superiorvisual effect.