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BAIDet: remote sensing image object detector based on background and angle information

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Abstract

Remote sensing object detection, with large differences in object size, arbitrary orientation and tight arrangement, leads to difficulties in object recognition and localization. Therefore, a remote sensing image object Detector (BAIDet) based on Background and Angle Information is proposed in this paper. Firstly, a large convolutional kernel global attention module is designed to fully utilize the global information of remote sensing images by expanding the receptive field. And obtain the edge information of ground objects through deformable convolution. Secondly, an angle-sensitive probabilistic intersection-over-union loss function (AS-ProbIoU Loss) is developed for bounding box regression for oriented object detection. Finally, experimental results on four remote sensing image datasets, DOTA, HRSC 2016, UCAS-AOD, and DIOR-R, demonstrated the effectiveness of this method.

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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Funding

This study was supported by the National Key R &D Porgram of China(2021YFD13000500, 2023YFB3904905, 2022YFC3301605); the project of Zhanjiang Science and Technology Bureau(2021A05040).

Author information

Author notes

  1. Lin Sun, Shuhua Song, Guolong Guo and Kai Chen have contributed equally to this work.

Authors and Affiliations

  1. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China

    Jiangfeng Yu, Lin Sun & Shuhua Song

  2. GEOVIS Wisdom Technology Co., Ltd., Qingdao, 266100, China

    Jiangfeng Yu, Shuhua Song & Guolong Guo

  3. School of Geosciences, Yangtze University, Street, Wuhan, 430000, China

    Shuhua Song

  4. School of Mathematics and Statistics, Lingnan Normal University, Zhanjiang, 524048, China

    Shuhua Song

  5. 91001 Troops, Beijing, 100309, China

    Kai Chen

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  1. Jiangfeng Yu
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  2. Lin Sun
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  3. Shuhua Song
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  5. Kai Chen
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Contributions

Jiangfeng Yu wrote the main manuscript text and designed the oriented object detection model. Song Shuhua and Sun Lin provided constructive suggestions and revised the manuscript. Guo Guolong, Chen Kai provided suggestions for the design of the detector.

Corresponding author

Correspondence to Shuhua Song.

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Yu, J., Sun, L., Song, S. et al. BAIDet: remote sensing image object detector based on background and angle information. SIViP 18, 9295–9304 (2024). https://doi.org/10.1007/s11760-024-03546-x

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