Research On The Restoration Method Of Space Target Image

With the vigorous development of space science and technology,more and more spacecraft are sent into space.Space activities provide technical support and exploration direction for scientific research,national defense and energy developmen,so the national stategy for space is becoming more and more important.With the human space exploration,development and utilization,the number of space target in the continuous growth,but also led to the space debris gradually increased,so the identification and positioning of space targets is imminent.With the human exploration,development and utilization of space,the number of spacecrafts is constantly increasing,which also leads to the gradual increase of debris in space.The star image suffers inevitably from degradation due to the high-speed motion of the space target and the long exposure time of the camera.Combined with the influence of atmospheric turbulence,photons and electrons,the deterioration of the star map will be more serious.Therefore,it is more difficult to identify and locate the space target.Although the existing research on space target image restoration algorithms has made some achievements,there are still some problems:(1)The space target image preprocessing is stuck on the traditional image processing algorithm.And the effect is not very effective;(2)In the restoration of spatial objects,it is necessary to use multiple frames of images and prior knowledge to estimate the fuzzy core of fuzzy images;(3)The generally algorithm of adaptive optical image restoration is complex and difficult to satisfy the needs of real-time observationa,and most algorithms use gyroscope to obtain the motion blurred length and motion blurred angle of spacel targets,so the operation is complicated and inconvenient.Aiming at the existing problems,this paper carried out research on the restoration technology of space target images.The main innovation points are as follows:First,a saliency detection algorithm based on space target gray information is proposed.It is difficult to recognize and restore the image because of the background noise,uneven background distribution,and dim brightness of the space target.Aiming at the above problems,this paper proposes a saliency detection algorithm to preprocess astronomical images.Through saliency detection,the contrast between the space target and the background is enhanced.At the same time,the background noise is removed and only the space target is retained.Then,we put forward a method to recognize the space target based on Minimum Bounding Rectangle(MBR).In this paper,on the basis of analyzing the image characteristics of the space target,considering the shape of space target features,edge detection algorithm is utilized to extract the edge of space target first,then introduce the MBR to describe space target,by determining the major axis and the minor axis to get MBR of space target and space target recognition.Last,an image restoration algorithm based on the shape features of space target is proposed.Based on the study of image degradation model,the Point Spread Function(PSF)is estimated by using the MBR parameters of the space target.The length of the rectangle is the motion blurred length of the PSF,and the horizontal Angle of the rectangle is the motion blurred angle of the PSF.Finally,the regularization method is employed to restore the space target imageExperimental results on both simulation and real star images demonstrate that the proposed method reduces the error of point spread function estimation and decreases the error rate of identified space targets.At the same time,the accuracy of the star centroid extraction improves 0.2786 on average and the error of the star centroid location extraction reduces 0.059 comparing to the s state-of-art method.The proposed method is of great significance for positioning and recognition of space targets.