Abstract:

A large number of stars in the driftscanning star image interfer with the detection of small targets. An  adaptive linear filtering method is proposed to achieve the small target detection by suppressing the stars. Firstly, the  characteristics of three different representative objects, i.e., stars, interest targets and noise, in the star image are  analyzed, then the standardized linear filter is constructed to filter the driftscanning star image so as to achieve  the gray value amplification of different stars with the reduction of small targets. Meantime, for the purpose of  suppressing the stars adaptively, a gradient linear filter is constructed to modify the effect with the standardized 
linear filter. The residual processing between the original star image and final filtering result suppresses the drift scanning stars. Secondly, theoretical analysis is done to give the filter parameter selection strategy. Finally, with the  processing results of different methods on the real driftscanning data, it is shown that the proposed method for 
suppressing stars with different lengths and lean angles has a better effect and easier application than the others.