  The detection and tracking of small targets in passive optical remote sensing
(PORS) has broad applications. However, most of the previously proposed methods
seldom utilize the abundant temporal features formed by target motion,
resulting in poor detection and tracking performance for low signal-to-clutter
ratio (SCR) targets. In this article, we analyze the difficulty based on
spatial features and the feasibility based on temporal features of realizing
effective detection. According to this analysis, we use a multi-frame as a
detection unit and propose a detection method based on temporal energy
selective scaling (TESS). Specifically, we investigated the composition of
intensity temporal profiles (ITPs) formed by pixels on a multi-frame detection
unit. For the target-present pixel, the target passing through the pixel will
bring a weak transient disturbance on the ITP and introduce a change in the
statistical properties of ITP. We use a well-designed function to amplify the
transient disturbance, suppress the background and noise components, and output
the trajectory of the target on the multi-frame detection unit. Subsequently,
to solve the contradiction between the detection rate and the false alarm rate
brought by the traditional threshold segmentation, we associate the temporal
and spatial features of the output trajectory and propose a trajectory
extraction method based on the 3D Hough transform. Finally, we model the
trajectory of the target and propose a trajectory-based multi-target tracking
method. Compared with the various state-of-the-art detection and tracking
methods, experiments in multiple scenarios prove the superiority of our
proposed methods.
