SATDark: A Satellite Video Low-Light Tracking Benchmark for Dark and Weak Vehicles

Satellite video single object tracking (SVSOT) stands as a pivotal research area. However, it faces significant challenges in low-light environments, particularly when dealing with dark and weak vehicles. Previous studies have predominantly focused on tracking methods under favorable lighting conditions, neglecting the complexities introduced by inadequate illumination. The difficulty in extracting features from targets in low-light environments, coupled with the susceptibility of dark and weak targets to background noise, exacerbates these challenges. In low-light environments, dark and weak vehicles exhibit less distinctive features and are more susceptible to background interference due to the reduced contrast. To tackle the above challenges, this work proposes an innovative correlation filter (CF)-based tracker (RETrack) that incorporates a retinex-inspired target enhancement. This enhancer integrates an effective low-light enhancement within the CF-based tracker, enhancing target visibility by reallocating target energy based on the characteristics of target motion. Moreover, to mitigate background interference and leverage background information efficiently, an adaptive label update mechanism is developed to suppress background disturbance. Furthermore, this work constructs a satellite video low-light tracking benchmark SATDark, which comprises 120 sequences of dark and weak vehicles. Comprehensive experiments show that RETrack surpasses current leading trackers on the SATDark, providing innovative insights and advancing the field of satellite video object tracking. Additionally, RETrack achieves real-time processing speeds exceeding 30 frames/s on a single CPU, underscoring its practical applicability and efficiency.