In view of the problem of automatic and high accuracy detection of space moving targets for space surveillance system, an algorithm of complementary enhancement by salience computation with optical flow detection is presented, in which the elementary detecting result by mean shift is taken as a guidance to realize high accuracy detection and segmentation through the complementary enhancement of salience computation and optical flow detection. Firstly, the salience computation by complementary enhancement of frequency tuned filter with gradient information is carried out for the whole frame of video image and various regions produced by mean shift segmentation separately so as to obtain their respective salient regions, then a proper threshold value is determined based on the mean salience of whole frame image to detect candidate targets. Meanwhile, in a concurrent way, another set of candidate targets are acquired by threshold based optical flow detection. Afterwards, a conjunction operation is used to obtain an intersection of two different distributed maps of candidate targets as confirmatory detection result, then the morphological filter is employed to enhance the confirmatory targets to achieve a high accuracy detection and segmentation of space moving targets. A series of experimental results with video images demonstrate that the proposed algorithm can accurately detect and segment space moving targets with neither priori knowledge of scene and targets nor manual intervention, which qualifies well performance of adaptability to illumination changes and noise disturbance.