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Intelligent processing of satellite video focuses on extracting specific information of ground objects and scenes from Earth observation videos through intelligent image/video processing technology, which has important applications in fields such as traffic monitoring, resource and environmental monitoring. The integration of deep learning technology in satellite video processing has led to significant advancements in tasks like object detection and object tracking, expanding into emerging research areas such as satellite video scene classification, object segmentation. However, there is no comprehensive review and summary in the intelligent processing of satellite video. This paper presents a systematic review and quantitative analysis of the results published over the last decade, intending to further promote the development of various intelligent processing tasks for satellite video. It analyzes the current difficulties, challenges and the methodological system for each task. Additionally, it provides an in-depth analysis and summary of publicly available datasets and evaluation benchmarks for each task, as well as classic algorithm performance and application scenarios. Finally, this paper summarizes the current research status and looks forward to the future development trend, hoping to inspire researchers in related fields and jointly promote the development of intelligent processing of satellite video.
Li et al. (Sun,) studied this question.