Small space target detection based on feature stability algorithm

The detecting technology is very important for the discovery of space objects. The target is submerged by the complex background noise which is the environment of outer space and the device produced. The difficulty of the detection is increased. The detect system mainly has three kinds of working patterns including the fixed tracking pattern, the fixed star tracking pattern and the target tracking pattern. Theses pattern differences perform as moving target in moving background, moving target in static background and static target in moving background in the images. We bring up a new framework for detecting target in three kinds of working patterns based on the feature stability difference. The first step is preprocess. Secondly, we extract features from image sequence. Then we construct a stability function about features for every pixel. Finally, we can detect the position of target according to the value of stability function, then map the position of target in the feature domain to the original image, and search in original image for the accurate centroid of the target. Qualitative and quantitative results prove that the proposed algorithm has strong anti-noise performance and fit for kinds of working pattern of detection system for target detection conveniently.