Under dynamic conditions, the centroiding accuracy of the motion-blurred star image decreases and the number of identified stars reduces, which leads to the degradation of the attitude accuracy of the star sensor. To improve the attitude accuracy, a region-confined restoration method, which concentrates on the noise removal and signal to noise ratio (SNR) improvement of the motion-blurred star images, is proposed for the star sensor under dynamic conditions. A multi-seed-region growing technique with the kinematic recursive model for star image motion is given to find the star image regions and to remove the noise. Subsequently, a restoration strategy is employed in the extracted regions, taking the time consumption and SNR improvement into consideration simultaneously. Simulation results indicate that the region-confined restoration method is effective in removing noise and improving the centroiding accuracy. The identification rate and the average number of identified stars in the experiments verify the advantages of the region-confined restoration method.