A realtime fusion algorithm of visible and infrared videos based on spectrum characteristics

The fusion of visible and infrared videos can improve the perceptual quality of videos under severe environments, which is important for video surveillance. Since the infrared and visible videos have different spectrum characteristics, it is difficult to retain the hot targets in the fused videos and enhance the textures at the same time. Moreover, a real-time fusion algorithm is highly required in video surveillance. Therefore, this paper proposes a real-time fusion algorithm of visible and infrared videos by fully utilizing their different spectrum characteristics. A hot-target-oriented fusion based on the gray distribution is firstly proposed to retain the hot targets in the fused videos. Moreover, a texture-enhanced fusion is proposed to enhance the texture information of the fused videos based on the guided filter. Furthermore, the inter-frame correlations are employed to speed up fusion process. The experimental results demonstrate that the proposed algorithm can achieve real-time video fusion and improve both subjective and objective qualities compared with the state-of-the-art.