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Video fusion is a process that combines visual data from different sensors toobtain a single composite video preserving the information of the sources. Theavailability of a system, enhancing human ability to perceive the observedscenario, is crucial to improve the performance of a surveillance system. Theinfrared (IR) camera captures thermal image of object in night-timeenvironment, when only limited visual information can be captured by RGBcamera. The fusion of data recorded by an IR sensor and a visible RGB cameracan produce information otherwise not obtainable by viewing the sensor outputsseparately. In this paper we consider the problem of fusing two video streamsacquired by an RGB camera and an IR sensor. The pedestrians, distinctlycaptured by IR video, are separated and fused with the RGB video. Thealgorithms implemented involve estimation of the background, followed bydetection of object from the IR Video, after necessary denoising. Finally asuitable fusion algorithm is employed to combine the extracted pedestrians withthe visual output. The obtained results clearly demonstrate the effectivenessof the proposed video fusion scheme, for night vision.

Visual Infrared Video Fusion for Night Vision using Background Estimation