Space objects in Geostationary Earth Orbit (GEO) present significant detection challenges in optical imaging due to weak signals, complex stellar backgrounds, and environmental interference. In this paper, we enhance high-frequency features of GEO targets while suppressing background noise at the single-frame level through wavelet transform. Building on this, we propose a multi-frame temporal trajectory completion scheme centered on the Hungarian algorithm for globally optimal cross-frame matching. To effectively mitigate missing and false detections, a series of key steps including temporal matching and interpolation completion, temporal-consistency-based noise filtering, and progressive trajectory refinement are designed in the post-processing pipeline. Experimental results on the public SpotGEO dataset demonstrate the effectiveness of the proposed method, achieving an F_1 score of 90.14%.

翻译：地球静止轨道（GEO）空间目标在光学成像中因信号微弱、恒星背景复杂及环境干扰而面临显著的检测挑战。本文首先通过小波变换在单帧层面增强GEO目标的高频特征，同时抑制背景噪声。在此基础上，我们提出一种以匈牙利算法为核心、实现全局最优跨帧匹配的多帧时序轨迹补全方案。为有效缓解漏检与误检，后处理流程中设计了一系列关键步骤，包括时序匹配与插值补全、基于时序一致性的噪声滤除以及渐进式轨迹优化。在公开SpotGEO数据集上的实验结果表明，所提方法取得了90.14%的F_1分数，验证了其有效性。