The Analysis Of The Influence Of Sequence Image Quality On The Object Tracking Accuracy

Along with the improvement of space technology, the quantity of object launched into space has become biger and biger. In order to improve the ability of space, we need the research on space object tracking that is based on gained data of image. On the process of object observation by satellite, there will be degeneration of image quality and error of object tracking because of error in imaging links and shaking of satellite-borne platform. In order to analyze the influence of image quality on tracking accuracy, scientific evaluation system for image quality is constructed and proposal analysis method about tracking accuracy is presented. And influence law about image quality and tracking accuracy is gained by way of numerical optimization. Specific research content include following aspects.First of all, the evaluation of sequence image quality is carried out. Construct index system of the image quality assessment and find 18 evaluation parameters that are easily extracted and quantitatively measured, such as grayscale, texture and energy. Aiming at the problems of correlation among parameters, the optimization of them is finished by principal component analysis. The three principal components whose accumulative contribution rate surpasses ninety percent are chosen as input parameters for next research on the influence of the object tracking accuracy of sequence image.Secondly, simulation analysis on object tracking accuracy is presented. According to the requirement of sequence image tracking, the analysis method for object tracking accuracy is presented based on the extracting and matching of image character. Through the character analysis of image source, image is matched by mature algorithms such as SIFT algorithm and Harris corner detection algorithm. Comparing the tracking accuracies of two algorithms, scientific evaluation for object tracking algorithms is presented. At the same time, the tracking accuracies are used as output parameters for next research on the influence of the object tracking accuracy of image quality.Finally, the analysis of tracking accuracy of image quality is carried out. Combing the characteristics of input and output parameters, the research about influence of image quality on the object tracking accuracy is regarded as black-box problem. BP neural network algorithm is adopted to construct the model of relationship between the input and output, and use the simulation generated image as example to gain the absolute influence coefficient about image quality and tracking accuracy.All in all, by research on influence of image quality on the object tracking accuracy, the evaluation model of image quality is constructed, analysis methods about object tracking accuracy is presented and absolute influence coffiicent about sequence image quality and object tracking accuracy is presented in this paper. The result of paper supply important theory basis and technical means for design and optimization in imaging detection system and for promotion and evaluation in image quality.