Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets.

Sun, Haijiang; Liu, Qiaoyuan; Wang, Jiacheng; Ren, Jinchang; Wu, Yanfeng; Zhao, Huimin; Li, Huakang

Abstract

Detection of the low-altitude and slow-speed small (LSS) targets is one of the most popular research topics in remote sensing. Despite of a few existing approaches, there is still an accuracy gap for satisfying the practical needs. As the LSS targets are too small to extract useful features, deep learning based algorithms can hardly be used. To this end, we propose in this article an effective strategy for determining the region of interest, using a multiscale layered image fusion method to extract the most representative information for LSS-target detection. In addition, an improved self-balanced sensitivity segment model is proposed to detect the fused LSS target, which can further improve both the detection accuracy and the computational efficiency. We conduct extensive ablation studies to validate the efficacy of the proposed LSS-target detection method on three public datasets and three self-collected datasets. The superior performance over the state of the arts has fully demonstrated the efficacy of the proposed approach.

Citation

SUN, H., LIU, Q., WANG, J., REN, J., WU, Y., ZHAO, H. and LI, H. 2021. Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 2971-2983. Available from: https://doi.org/10.1109/JSTARS.2021.3061496

• Journal Article Type: Article
• Acceptance Date: Feb 19, 2021
• Online Publication Date: Feb 24, 2021
• Publication Date: Dec 31, 2021
• Deposit Date: Apr 23, 2021
• Publicly Available Date: Apr 23, 2021
• Journal: IEEE journal of selected topics in applied earth observations and remote sensing
• Print ISSN: 1939-1404
• Electronic ISSN: 2151-1535
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Pages: 2971-2983
• DOI: https://doi.org/10.1109/jstars.2021.3061496
• Keywords: Background subtraction; Image fusion; Low-altitude and slow-speed small (LSS) target detection; Saliency detection
• Public URL: https://rgu-repository.worktribe.com/output/1269784