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 informa-tion 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 de-scribing the motion blur recovery process.And then,in order to reduce the calculation,the image sequence was sam-pled 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 oth-er 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 algo-rithm.The results basically meet the requirements of detection system in discovering targets and monitoring the air-space.%当前红外空域监测探测系统常用视频的形式存储和传输图像信号,但是视频图像在形成、传输和记录过程中,易受运动模糊和噪声的污染,为了使该系统适用于当前空域形势,提出基于该系统的视频运动模糊复原算法.首先构建基于视频流运动模糊复原模型,综合序列图像各帧之间的互信息,估计有效的点扩散函数,然后描述运动模糊复原流程,提出相应算法,构建各功能模块.操作中视频以降频采样的方式减少计算复杂度,提高图像质量,获取较高复原效果.最后,通过引入主、客观两套评价体系对使用的算法以及其他经典算法作对照,评估复原结果.实验结果表明:复原视频各帧的峰值信噪比达到37,均方误差在9以下,均优于对照算法.基本满足监测系统发现目标,监测空域的要求.
展开▼
