Skip to main content

Research Repository

Advanced Search

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

Authors

Haijiang Sun

Qiaoyuan Liu

Jiacheng Wang

Jinchang Ren

Yanfeng Wu

Huimin Zhao

Huakang Li



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
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

Files





You might also like



Downloadable Citations