目的 由于照相机不能采集到很宽的亮度范围，过度曝光和曝光不足现象普遍存在，尤其对于高动态（HDR）场景。图像融合技术能够解决这一问题，但是由于算法大多过于复杂，难以实现高效的处理速度，只适合对静态图像做处理。针对图像融合算法进行了多种优化，并提出使用图像融合技术来解决视频中的曝光问题。方法 对图像融合算法进行测试，对块融合的方法进行有效的优化来提升算法效率，并且将优化后的算法嵌入到实时监控系统中，通过曝光控制模块与融合技术相结合，实现了实时融合的视频采集系统。结果 对高动态场景的测试表明，视频中的每一帧均能采集到整个场景中的所有信息，并且不会存在曝光问题。结论 针对图像融合方法提出了多种优化和加速策略，并独创性地将其应用于实时视频采集中。实验结果表明，即使是高动态场景中，也可以将几乎所有信息都保留下来，不受曝光问题的干扰。

Objective Since cameras are not able to capture a very wide range of brightness, the phenomenon of overexposure or underexposure is widespread, especially for high dynamic range (HDR) scenes. Image fusion technology aims to solve this problem. However, most of image fusion algorithms are too complex and time-consuming, Therefore, they are only suitable for processing static images. In order to solve this problem, many methods are used to optimize the original image fusion algorithm, which is introduced to deal with the exposure problems of video. Method We test the image fusion algorithms and make practical optimization for block-based image fusion to accelerate the original algorithm. Furthermore, the optimized algorithm is embedded in real-time monitoring system. Through combining the exposure control module with fusion technology, we design a video capture system with real-time image fusion. Result As it is illustrated by experiments in HDR scenarios, each frame of the video can maintain all the information of the scene without exposure problems. Conclusion In this paper, many strategies for optimizing and accelerating the image fusion are proposed and the improved image fusion method is utilized to the real-time video capture ingeniously. The experimental results show that almost all the details are remained without exposure errors, even in HDR scenarios.