BSVOS: Background Interference Suppression Strategy for Satellite Video Multiobject Segmentation

Video satellites provide dynamic real-time monitoring of hotspot areas and objects by continuously imaging objects within a specified sequence, providing dynamic information over large areas. Satellite video object segmentation aims to separate foreground and background continuously. Compared with satellite video single-object segmentation, satellite video multiobject segmentation can separate multiple foreground objects of interest in the scene simultaneously. So far, the research on multiobject segmentation mainly focuses on extracting deeper informative features. However, this does not cope well with the problems of weak object texture information, foreground-background disproportion, and small object scale in satellite videos. Therefore, this article proposes an end-to-end semisupervised segmentation network named background interference suppression strategy for satellite video multiobject segmentation, which is the first research about satellite video multiobject segmentation. First, spatial and temporal matching templates integrate spatio-temporal information to enhance texture features within a sequence. Second, a novel matching strategy is also proposed to suppress complex background interference in satellite video. Finally, both intuitive and quantitative experimental results indicate that our proposed method outperforms other multiobject segmentation models.