The defogging algorithm developed for fix scenes can not achieve the best effects for videos shot by unmanned aerial vehicles(UAVs) since the locations, scenes and environments of UAVs keep varying. The video defogging algorithm based on receding horizon particle swarm optimization is proposed for adaptive defogging. The defogging parameter can be optimized by combining the particle swarm optimization(PSO) algorithm and the receding horizon strategy driven by time and events. The PSO algorithm is started to optimize the defogging parameter when environment or scene changes, or frame interval is over the threshold. The proposed video defogging algorithm is verified in experiments and compared with the fixed parameter video defogging algorithm for UAV videos. The experimental results show that the proposed algorithm has better contrast and visual effect than the fixed parameter algorithm for videos with environment variations.