Small Infrared Aerial Target Detection Using Spatial and Temporal Cues

Abstract

Due to rapidly relative motion between target and infrared imaging platform, clutter background, etc., robust small infrared aerial target detection is still an open problem. A novel small infrared aerial target detection method using spatial and temporal cues is proposed in this paper. First, using spatial cues, we take target candidate detection as a binary classification problem. Target candidates in each single frame are detected via interesting pixel detection and a trained LightGBM model. Then, using temporal cues, we model the local smoothness and global continuous characteristic of the target trajectory as short-strict and long-loose constraints. The trajectory constraints within image sequence are used in detecting the true small infrared aerial targets from numerical target candidates. Experiment results on the public dataset SIATD show that the proposed method performs better than other existing methods in detecting small infrared aerial target and shows great robustness toward clutter backgrounds.