  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.
