基于背景估计的夜视红外视频融合
Visual Infrared Video Fusion for Night Vision using Background Estimation
摘要：
视频融合是将来自不同传感器的视觉数据进行组合，以获得保留源信息的单个复合视频的过程。一个系统的可用性，提高人类感知所观察到的场景的能力，是至关重要的，以提高监控系统的性能。红外（IR）摄像机在夜间环境中捕获物体的热图像，而RGB摄像机只能捕获有限的视觉信息。由IR传感器和可见RGB相机记录的数据的融合可以产生通过单独查看传感器输出而无法获得的信息。在本文中，我们考虑的问题，融合由RGB摄像机和红外传感器获得的两个视频流。红外视频清晰地捕捉到的行人被分离出来，并与RGB视频融合。实现的算法涉及估计的背景，然后从红外视频检测对象，必要的去噪后。最后采用合适的融合算法将提取的行人与视觉输出相结合。所得到的结果清楚地表明，所提出的视频融合方案的有效性，夜视。
英文摘要：
Video fusion is a process that combines visual data from different sensors to obtain a single composite video preserving the information of the sources. The availability of a system, enhancing human ability to perceive the observed scenario, is crucial to improve the performance of a surveillance system. The infrared (IR) camera captures thermal image of object in night-time environment, when only limited visual information can be captured by RGB camera. The fusion of data recorded by an IR sensor and a visible RGB camera can produce information otherwise not obtainable by viewing the sensor outputs separately. In this paper we consider the problem of fusing two video streams acquired by an RGB camera and an IR sensor. The pedestrians, distinctly captured by IR video, are separated and fused with the RGB video. The algorithms implemented involve estimation of the background, followed by detection of object from the IR Video, after necessary denoising. Finally a suitable fusion algorithm is employed to combine the extracted pedestrians with the visual output. The obtained results clearly demonstrate the effectiveness of the proposed video fusion scheme, for night vision.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
