Infrared small target segmentation network with contextual semantic information based on area features

Qingwen Li

doi:10.1117/12.3021281

25 March 2024 Infrared small target segmentation network with contextual semantic information based on area features

Qingwen Li

Proceedings Volume 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023); 130890J (2024) https://doi.org/10.1117/12.3021281
Event: Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 2023, Suzhou, China

Abstract

Infrared Small Target Detection (IRSTD), widely implemented in both military and civilian contexts, stands as a pivotal technology within the realm of target detection. Yet, the accurate extraction of small target regions is often hampered by the interference from complex backgrounds. To overcome this issue, we introduce a novel approach: a Contextual Semantic Information Network founded on region features. As an initial step, we develop a target region retention backbone network. This innovation aids in preserving more potential target regions, thereby resolving the issue of small targets being lost as the deepening of the network. Next, we devise a regional feature enhancement module, specifically tailored for the potentially targeted area. This module is designed to effectively boost the region's target characterization capabilities. Finally, we employ a global context module to excavate the inherent feature information, thereby compensating for any missing details within the target region. When tested on the SIRST dataset, our experimental results unequivocally demonstrate that the proposed methodology substantially augments both the accuracy and robustness of IRSTD in complex settings, exceeding the performance of existing detection methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qingwen Li "Infrared small target segmentation network with contextual semantic information based on area features", Proc. SPIE 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 130890J (25 March 2024); https://doi.org/10.1117/12.3021281

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