Dim small moving target detection and tracking method based on spatial-temporal joint processing model

Abstract

In order to solve the problem of weak target detection in complex moving background, a joint algorithm model of space-time domain is proposed in this paper. The algorithm first selects appropriate length of the time domain window and loop step size. In each time domain window: (1) In time domain processing stage, the algorithm fully considers the factors of background movement, and uses neighborhood similarity measure based on Pearson correlation coefficient to suppress most part of background area. (2) In space domain processing stage, a target detection method based on regional gray level (RGL) is proposed to suppress residual background and re-enhance the target. In each iteration, this joint detection model can obtain part of the trajectory of the target in real time. Therefore, after all iterations are completed (all images in the sequence have been processed), the target can be detected and the target trajectory can be efficiently extracted. The experimental results in this paper show that the proposed algorithm can effectively detect targets with maximum speed of 5 pixel/frame in the image sequence with average SCR ≤ 1 and background moving speed ≤0.8 pixel/frame.