Images taken in foggy weather often suffer from low contrast and limited visibility due to the substantial presence of particles in the atmosphere, which absorb and scatter light during the propagation, and the efficiency of the visual system is limited and affected.Aiming at the degraded performance of the visual system in low-visibility weather, the foggy image degradation model is established, and an equation of transmittance is constructed by using the constraint relationship between the color distribution and the transmittance.Then, spatial-temporal continuous constraint to the atmospheric light and the transmittance is realized through online updating of atmospheric optical value and by use of Markov Random Field (MRF) model.The problem of adaptability and robustness of the visual system under complex environment or complex weather conditions is solved.Experimental result shows that, the proposed algorithm can effectively improve the imaging distance under low-visibility condition, and the dehazed video image keeps the color distribution of the original image without chromatic aberration, which can supply a fine image for the subsequent high-level vision mission.