基于快速局部对比度和目标特征的星图弱小目标检测算法OACSTPCD

In order to solve the problems of large amount of computation and difficulty in removing background noise when the local contrast method is used in star map spatial target detection,a method based on fast local contrast and target features is proposed to detect the target.Through three steps of before,during and after contrast calculation,the real-time performance of the algorithm is improved,the complex background is suppressed and the noise is removed.Firstly,high frequency noise is removed by median filtering.Then,the target region is determined by fast local maximum filtering,and the background is suppressed by local contrast calculation to highlight the imaging features of the target.Finally,according to the imaging features of the target,three feature functions are set,namely target energy distribution,target energy concentration and target energy transfer.By setting the feature threshold,noise is removed and the real target is extracted.The experimental results show that the proposed method has advantages in detection rate and time consumption.For the target with a signal-to-clutter ratio of 1.5,the detection rate is 95%,and the average time is only about 1/30～1/6 of some comparison methods.The method proposed in this paper is more suitable for rapid target detection under complex star map background conditions,and meets the requirements of strong robustness and high real-time performance of the spatial target detection algorithm of star map.