Frequency Domain and Cross‐Frame Connections for Multi‐Object Tracking of Small Targets in Satellite Imagery

ABSTRACT Satellite‐based video surveillance, sometimes known as “gazing,” is extremely useful for viewing, evaluating, and dynamically tracking developments on Earth. However, the tiny size and density of objects, overlapping targets, and unclear surroundings with variable illumination and complex backdrops make multi‐object tracking in satellite movies particularly difficult. Limitations in bandwidth and computational capacity made accurate tracking and real‐time processing increasingly challenging. Applications, including disaster response, traffic monitoring, defense, and security operations, depend on overcoming these obstacles. This work offers a novel framework to address these difficulties by merging sophisticated cross‐frame connection techniques with frequency domain analysis using wavelet transform analysis. By separating high‐frequency components and reducing noise, the wavelet transform improves the identification of small targets and makes it possible to recover fine‐grained spatial and frequency data that are essential for reliable tracking. The system uses motion models and data association techniques to guarantee trajectory correctness and consistency, and it integrates cross‐frame connections to create temporal continuity and preserve target identities over successive frames. The experimental results show significant increases in tracking performance, outperforming state‐of‐the‐art methods in terms of multiple object tracking accuracy (MOTA), multiple object tracking precision (MOTP), and high tracking accuracy. These results demonstrate this proposed model's resilience and effectiveness in accurately identifying and following small targets in challenging satellite imagery settings. The accuracy achieved by the proposed method for the VISO, SATMTB, and Skysat‐1 datasets is 96.82%, 95.26%, and 95.90%, respectively.