Moving dim point target detection with three-dimensional wide-to-exact search directional filtering

We assess the performance of a novel three-dimensional wide-to-exact search directional filtering (3DWESDF) algorithm for detecting and tracking a weak moving dim target against a cluttered background in real infrared (IR) image sequence. This paper proposed a novel 3DWESDF to decrease the 3D directional filter’s (3DDF) computational requirements and increase the target energy accumulation ability further. Prior to the filtering, a newly pre-whitening method termed three-dimensional spatial-temporal adaptive prediction filter (3DSTAPF) used here to suppress complex cluttered background. Extensive experimental results demonstrate the proposed algorithm’s ability in detecting weak dim point target against a complex cloud-cluttered background in real IR image sequence. Finally, performance comparisons of the proposed algorithm and 3DDF, on real IR image data, are presented in which the advantages of the proposed 3DWESDF filters are shown.