一种空间目标在轨检测图像预处理算法

Image Preprocessing Algorithm for Space Target Space-Based Detection

通过对美国天基可见相机(SBV)在轨检测算法(Moving target indicator,MTI)算法进行改进,使其更加快速有效地检测出淹没在噪声杂波中的目标条纹。MTI改进算法使用了一种新的二维图像检测预处理算法——依概率加窗检测算法。依概率加窗检测算依据同一大小检测窗口内,目标所在检测窗内出现的非零点比纯噪声检测窗内多的特性,通过检测窗门限滤波,在可能剔除部分目标点的同时,极大地抑制噪声。接着使用三点共线条纹检测算法,剔除可疑目标条纹,进一步降低虚警概率,提高检测概率。通过算法性能分析可知,MTI改进算法的虚警概率降低15倍,检测概率99%时所需信噪比从6降低为3,并且总体计算量降低6个数量级。MTI改进算法减少计算量的同时,降低虚警概率并提高检测概率,在工程应用中更有利于算法的实时实现。

Space-based detection algorithm in American SBV named moving target indicator（MTI） algorithm was improved. The improved algorithm could detect target streak ‘submerged＇ in noise and clutter more quickly and more effectively. MTI improved algorithm used a new two-dimensional image detection preprocessing algorithm named windowed detection in probability algorithm. There were more the non-zero points in target detection window than in pure noise detection window with the same size. According to the characteristic, windowed detection in probability algorithm used threshold filter in detection window. The threshold filter extremely suppressed noise along with eliminating portion target points. Then, doubtful target streak was eliminated by three-point collinear streak detection algorithm. The streak detection algorithm reduced false-alarm probability and increased detection probability. By algorithm was performance analysis, false-alarm probability of MTI improved algorithm was reduced fifteen times than MTI algorithm, and needed signal-to-noise ratio （SNR） was reduced from 6 to 3 when detection probability equals to 99 %. Furthermore, the calculation amount of MTI improved algorithm was reduced six order of magnitude than MTI algorithm. According to algorithm performance, MTI improved algorithm avails real-time processing in engineering application.