To improve the preprocessing speed of star map and reduce the resource consumption of embedded system of star tracker, a parallel pipeline real-time preprocessing algorithm is presented. The two characteristics, the mean and the noise standard deviation of the background gray of a star map, are firstly obtained dynamically by the means that the intervene of the star image itself to the background is removed in advance. The criterion on whether or not the following noise filtering is needed is established, then the extraction threshold value is assigned according to the level of background noise, so that the centroiding accuracy is guaranteed. In the processing algorithm, as low as two lines of pixel data are buffered, and only 100 shift registers are used to record the connected domain label, by which the problems of resources wasting and connected domain overflow are solved. The simulating results show that the necessary data of the selected bright stars could be immediately accessed in a delay time as short as 10us after the pipeline processing of a 496×496 star map in 50Mb/s is finished, and the needed memory and registers resource total less than 80kb. To verify the accuracy performance of the algorithm proposed, different levels of background noise are added to the processed ideal star map, and the statistic centroiding error is smaller than 1/23 pixel under the condition that the signal to noise ratio is greater than 1. The parallel pipeline algorithm of real time star map preprocessing helps to increase the data output speed and the anti-dynamic performance of star tracker.