Experimental performance analysis of clutter removal techniques in IR images

This work deals with the problem of background removal in infra-red (IR) image sequences. Background removal is a basic step to detect small targets in surveillance systems based on IR images. The paper refers to a general background removal procedure that consists in estimating and subtracting the background in each frame of the IR sequence. The estimation step is accomplished by means of linear and non linear filters. The focus of this work is on techniques adopting four different filters: 1) the 2D window average filter; 2) the 2D MEDIAN filter; 3) the max/median filter; 4) the max/mean filter. In the paper a methodology to experimentally compare the performance of the different techniques is described and the results obtained over real IR data are discussed.