Temporal filtering for target detection algorithm based on static background elimination

A new temporal based target detection algorithm was presented by using static background elimination to deal with the drawback of large scale data processing and real-time implementation in temporal filtering.Firstly,a uniform model was developed based on the temporal behavior of different types of pixels.And the parameter of the model was estimated by introducing least square method.Using the new model,static background pixels could be eliminated.Secondly,a minimum filer was designed to obtain the baseline of the temporal profile.Finally,the deviation of the temporal profile and its baseline was analyzed,which led to a detection criterion.Since the target signal was well preserved during the static background elimination and large sale tracking data was eliminated,the method could have higher speed and computational efficiency.Experiments with real image sequences have proved the validity of the new approach.