The current infrared detection systems usually use the video to memory and transfer image signals,but when the videos are in the process of formation,transmission and storage,they are easily polluted by motion blur and noise.To solve this problem,a video motion blur restoration algorithm was proposed based on the infrared detection system.Firstly,the video motion blur restoration model was built based on video streaming,and then mutual information of every frame in sequence images is integrated and the effective point spread function(PSF) is estimated.Secondly,the corresponding algorithm is put forward and all the function modules are created through describing the motion blur recovery process.And then,in order to reduce the calculation,the image sequence was sampled with equal interval from the original video,which can enhance the image quality and achieve better restoration effect.Finally,a subjective and an objective evaluation system were introduced to compare this algorithm with two other classical algorithms and evaluate results.The experimental results show that the peak signal-to-noise ratio of each frame in restored video reached 37,and mean square error was below 9,which was superior to the contrast algorithm.The results basically meet the requirements of detection system in discovering targets and monitoring the airspace.