Knowledge Based Infrared Image Background Suppression

When suppressing the background, pixels of presumable surface or ground features are first marked. Extensive bulks of cloud clusters, surface features and differences in the distribution of atmospheric temperature are then removed by subtracting the mean greyness of the row (neighboring row). The ground and surface features are suppressed when recognized, through pattern recognition. The paper presents a knowlede based algorithm for background suppression. It uses lesser amount of operands and is capable of suppressing the most part of the background. Experimental results show that it can be used to suppress the background very effectively.