Infrared target segmentation is very valuable to infrared target detection and tracking. The research proposes an effective infrared target segmentation based on background and target gray character. The method avoids gray instability in the interior of the targets caused by temperature instability. Firstly, two-dimensional MCC based on gray-salience was proposed to segment targets. Then, improved region-growing algorithm based on random reed points was presented to extract background. Finally, morphological operation improved the segmentation performance. Compared with the traditional algorithms of target segmentation, this algorithm has better anti-jamming and robust. The method can be used not only for target segmentation but also for other similar segmentation.