Restoration method for blurred star images based on region filters

Under the dynamic working conditions for a star sensor, motion blur will appear in a star because of its energy dispersion in the process of imaging, which leads to a decrease in the signal to noise ratio (SNR) and makes the blurred region difficult to extract. Meanwhile, this causes a degradation in star centroid positon accuracy and attitude accuracy in the star sensor. Therefore, a restoration method for blurred star images based on region filters is presented in this paper, which simultaneously concentrates on the improvement of SNR and star centroid accuracy. Firstly, the kinematic models of a star centroid under different conditions are set up based on the characteristics of star sensors. Secondly, the motion trail of star centroid is determined based on the kinematic model, allowing the star blurred region to be extracted. The images inside and outside the star blurred region are then preprocessed by image processing algorithm respectively. Finally, the blurred star image is restored by an image restoration algorithm. The experiment results indicate that under the dynamic condition of 2 degrees/s, the region filter algorithm can effectively improve the SNR of a blurred star image. In restored images, the error of star centroid is less than 0.1 pixels, which can satisfy the requirements for star sensor of high centroid accuracy.